Editorial

Article Type
Changed
Mon, 01/02/2017 - 19:34
Display Headline
One year done & moving onward

One year of the Journal of Hospital Medicine is done, and we now embark on our second with this first issue of volume 2. Before moving on, I heartily thank all the authors who contributed their manuscripts to the Journal of Hospital Medicine (JHM), bravely investing in this new academic periodical. A remarkable 284 manuscripts have been submitted since we first opened the JHM Web site, 197 of them during 2006. This clearly reflects the robust demand by hospitalists and their colleagues for original research and relevant clinical reviews about our evolving specialty of hospital medicine. I probably should not be surprised that this demand exists among the 15,000‐plus hospitalists in America and the 6000‐plus members of the Society of Hospital Medicine. Regardless, I am ineffably humbled by the enthusiasm and energy of all the contributors.

Understandably, this volume of submissions, exceeding our projections by nearly 50%, required yeoman's work by our associate editors and reviewers. On page 55 we list the 203 reviewers who donated their time and acumen to assure the quality of our publication. Many reviewed more than 4 articles during the year. Our associate editors deserve particular appreciation and gratitude for their willingness to donate extraordinary amounts of time and effort to ensure the success of JHMVincent Chang from Boston Children's Hospital, Scott Flanders from the University of Michigan, Karen Hauer from the University of California, San Francisco, Jean Kutner from the University of Colorado, James Pile from Cleveland MetroHealth, and Kaveh Shojania from the University of Ottawa. Additionally, the energetic assistant editors have supported them and me with frequent reviews, article submissions, and creative ideas for improving the journal. Finally, our auspicious editorial board has proffered sage guidance, and many of its members have also submitted manuscripts and participated in reviewing articles.

Moving forward we expect continued growth, as both the submitted articles and demand for the journal are being recognized. At 7:29 a.m. on November 30, 2006, Vickie Thaw (Vice President and Publisher, John Wiley & Sons, Inc.) called me to report that the National Library of Medicine validated all our efforts. The Journal of Hospital Medicine had been selected for indexing and inclusion in the National Library of Medicine's MEDLINE (Medical Literature Analysis and Retrieval System Online). The primary component of PubMed, MEDLINE is a bibliographic database containing approximately 13 million references to journal articles on medicine, nursing, dentistry, veterinary medicine, health care systems, and preclinical sciences dating to the mid‐1960s. With this approval, hospital medicine has achieved another milestone in its evolution into a new specialty.

We now hope to respond to the robust interest in clinical materials as well as to continue publication of original research. To achieve our aim of increasing the amount of clinically relevant content for practicing hospitalists, authors are encouraged to submit to JHM case reports, clinical updates, and clinical images that convey novel or underappreciated teaching points. Teaching points may be purely clinical and may focus on clinical pearls or unusual presentations of well‐known diseases, although submission of straightforward presentations of rare diseases is discouraged. Alternatively, manuscripts may involve succinct case‐based descriptions of innovations, quality improvementrelated issues, or medical errors. Submitted case reports should be less than 800 words and should contain a maximum of 5 references and no more than 1 table or figure. Case reports should not include an abstract. Submission of the case report and review type should be avoided. Instead, we seek formal clinical updates of no more than 2000 words that present important aspects of a case along with new research findings and citations from the literature that change what has historically been the standard of delivery of care. Finally, we continue to seek cases most appropriate for the Hospital Images Dx section, edited by Paul Aronowitz. They should be submitted with that designation and have fewer than 150 words. These 3 categories are identified on our Manuscript Central website (http://mc.manuscriptcentral.com/jhm).

Again, thanks to all of you for making the launch of the Journal of Hospital Medicine an unqualified success. We look forward to your continued participation as we grow as the premier journal for the specialty of hospital medicine.

P.S. Sadly, one of our superstar associate editors, Kaveh Shojania, is stepping aside, and we sincerely express thanks for his terrific contributions. We welcome suggestions for an alternative to fulfill his responsibilities.

Article PDF
Issue
Journal of Hospital Medicine - 2(1)
Page Number
1-2
Sections
Article PDF
Article PDF

One year of the Journal of Hospital Medicine is done, and we now embark on our second with this first issue of volume 2. Before moving on, I heartily thank all the authors who contributed their manuscripts to the Journal of Hospital Medicine (JHM), bravely investing in this new academic periodical. A remarkable 284 manuscripts have been submitted since we first opened the JHM Web site, 197 of them during 2006. This clearly reflects the robust demand by hospitalists and their colleagues for original research and relevant clinical reviews about our evolving specialty of hospital medicine. I probably should not be surprised that this demand exists among the 15,000‐plus hospitalists in America and the 6000‐plus members of the Society of Hospital Medicine. Regardless, I am ineffably humbled by the enthusiasm and energy of all the contributors.

Understandably, this volume of submissions, exceeding our projections by nearly 50%, required yeoman's work by our associate editors and reviewers. On page 55 we list the 203 reviewers who donated their time and acumen to assure the quality of our publication. Many reviewed more than 4 articles during the year. Our associate editors deserve particular appreciation and gratitude for their willingness to donate extraordinary amounts of time and effort to ensure the success of JHMVincent Chang from Boston Children's Hospital, Scott Flanders from the University of Michigan, Karen Hauer from the University of California, San Francisco, Jean Kutner from the University of Colorado, James Pile from Cleveland MetroHealth, and Kaveh Shojania from the University of Ottawa. Additionally, the energetic assistant editors have supported them and me with frequent reviews, article submissions, and creative ideas for improving the journal. Finally, our auspicious editorial board has proffered sage guidance, and many of its members have also submitted manuscripts and participated in reviewing articles.

Moving forward we expect continued growth, as both the submitted articles and demand for the journal are being recognized. At 7:29 a.m. on November 30, 2006, Vickie Thaw (Vice President and Publisher, John Wiley & Sons, Inc.) called me to report that the National Library of Medicine validated all our efforts. The Journal of Hospital Medicine had been selected for indexing and inclusion in the National Library of Medicine's MEDLINE (Medical Literature Analysis and Retrieval System Online). The primary component of PubMed, MEDLINE is a bibliographic database containing approximately 13 million references to journal articles on medicine, nursing, dentistry, veterinary medicine, health care systems, and preclinical sciences dating to the mid‐1960s. With this approval, hospital medicine has achieved another milestone in its evolution into a new specialty.

We now hope to respond to the robust interest in clinical materials as well as to continue publication of original research. To achieve our aim of increasing the amount of clinically relevant content for practicing hospitalists, authors are encouraged to submit to JHM case reports, clinical updates, and clinical images that convey novel or underappreciated teaching points. Teaching points may be purely clinical and may focus on clinical pearls or unusual presentations of well‐known diseases, although submission of straightforward presentations of rare diseases is discouraged. Alternatively, manuscripts may involve succinct case‐based descriptions of innovations, quality improvementrelated issues, or medical errors. Submitted case reports should be less than 800 words and should contain a maximum of 5 references and no more than 1 table or figure. Case reports should not include an abstract. Submission of the case report and review type should be avoided. Instead, we seek formal clinical updates of no more than 2000 words that present important aspects of a case along with new research findings and citations from the literature that change what has historically been the standard of delivery of care. Finally, we continue to seek cases most appropriate for the Hospital Images Dx section, edited by Paul Aronowitz. They should be submitted with that designation and have fewer than 150 words. These 3 categories are identified on our Manuscript Central website (http://mc.manuscriptcentral.com/jhm).

Again, thanks to all of you for making the launch of the Journal of Hospital Medicine an unqualified success. We look forward to your continued participation as we grow as the premier journal for the specialty of hospital medicine.

P.S. Sadly, one of our superstar associate editors, Kaveh Shojania, is stepping aside, and we sincerely express thanks for his terrific contributions. We welcome suggestions for an alternative to fulfill his responsibilities.

One year of the Journal of Hospital Medicine is done, and we now embark on our second with this first issue of volume 2. Before moving on, I heartily thank all the authors who contributed their manuscripts to the Journal of Hospital Medicine (JHM), bravely investing in this new academic periodical. A remarkable 284 manuscripts have been submitted since we first opened the JHM Web site, 197 of them during 2006. This clearly reflects the robust demand by hospitalists and their colleagues for original research and relevant clinical reviews about our evolving specialty of hospital medicine. I probably should not be surprised that this demand exists among the 15,000‐plus hospitalists in America and the 6000‐plus members of the Society of Hospital Medicine. Regardless, I am ineffably humbled by the enthusiasm and energy of all the contributors.

Understandably, this volume of submissions, exceeding our projections by nearly 50%, required yeoman's work by our associate editors and reviewers. On page 55 we list the 203 reviewers who donated their time and acumen to assure the quality of our publication. Many reviewed more than 4 articles during the year. Our associate editors deserve particular appreciation and gratitude for their willingness to donate extraordinary amounts of time and effort to ensure the success of JHMVincent Chang from Boston Children's Hospital, Scott Flanders from the University of Michigan, Karen Hauer from the University of California, San Francisco, Jean Kutner from the University of Colorado, James Pile from Cleveland MetroHealth, and Kaveh Shojania from the University of Ottawa. Additionally, the energetic assistant editors have supported them and me with frequent reviews, article submissions, and creative ideas for improving the journal. Finally, our auspicious editorial board has proffered sage guidance, and many of its members have also submitted manuscripts and participated in reviewing articles.

Moving forward we expect continued growth, as both the submitted articles and demand for the journal are being recognized. At 7:29 a.m. on November 30, 2006, Vickie Thaw (Vice President and Publisher, John Wiley & Sons, Inc.) called me to report that the National Library of Medicine validated all our efforts. The Journal of Hospital Medicine had been selected for indexing and inclusion in the National Library of Medicine's MEDLINE (Medical Literature Analysis and Retrieval System Online). The primary component of PubMed, MEDLINE is a bibliographic database containing approximately 13 million references to journal articles on medicine, nursing, dentistry, veterinary medicine, health care systems, and preclinical sciences dating to the mid‐1960s. With this approval, hospital medicine has achieved another milestone in its evolution into a new specialty.

We now hope to respond to the robust interest in clinical materials as well as to continue publication of original research. To achieve our aim of increasing the amount of clinically relevant content for practicing hospitalists, authors are encouraged to submit to JHM case reports, clinical updates, and clinical images that convey novel or underappreciated teaching points. Teaching points may be purely clinical and may focus on clinical pearls or unusual presentations of well‐known diseases, although submission of straightforward presentations of rare diseases is discouraged. Alternatively, manuscripts may involve succinct case‐based descriptions of innovations, quality improvementrelated issues, or medical errors. Submitted case reports should be less than 800 words and should contain a maximum of 5 references and no more than 1 table or figure. Case reports should not include an abstract. Submission of the case report and review type should be avoided. Instead, we seek formal clinical updates of no more than 2000 words that present important aspects of a case along with new research findings and citations from the literature that change what has historically been the standard of delivery of care. Finally, we continue to seek cases most appropriate for the Hospital Images Dx section, edited by Paul Aronowitz. They should be submitted with that designation and have fewer than 150 words. These 3 categories are identified on our Manuscript Central website (http://mc.manuscriptcentral.com/jhm).

Again, thanks to all of you for making the launch of the Journal of Hospital Medicine an unqualified success. We look forward to your continued participation as we grow as the premier journal for the specialty of hospital medicine.

P.S. Sadly, one of our superstar associate editors, Kaveh Shojania, is stepping aside, and we sincerely express thanks for his terrific contributions. We welcome suggestions for an alternative to fulfill his responsibilities.

Issue
Journal of Hospital Medicine - 2(1)
Issue
Journal of Hospital Medicine - 2(1)
Page Number
1-2
Page Number
1-2
Article Type
Display Headline
One year done & moving onward
Display Headline
One year done & moving onward
Sections
Article Source
Copyright © 2007 Society of Hospital Medicine
Disallow All Ads
Content Gating
Gated (full article locked unless allowed per User)
Gating Strategy
First Peek Free
Article PDF Media

Mortality Predictors from the CBC

Article Type
Changed
Sun, 05/28/2017 - 22:42
Display Headline
Which observations from the complete blood cell count predict mortality for hospitalized patients?

The complete blood count (CBC) bundles the automated hemogram, an automated differential count of 5 types of cells, and a reflex manual differential count (when required by protocol) and is one of the most frequently ordered laboratory tests on admission to the hospital. In practice, it is a routine ingredient of all hospital admission ordersphysicians order a hemogram either alone or as part of a complete blood count for 98% of our medical/surgical admissions, and the same is true at most institutions.1 We know that the white blood cell count and hematocrit from the automated hemogram predict disease severity and mortality risk.25 For example, elevated WBC counts predict a worse prognosis in patients with cancer or coronary artery disease,6, 7 and anemia predicts increased risk of death of patients with heart failure.8, 9 Further, these two tests provide direct management guidance in common circumstances, for example, bleeding and infection.

The CBC describes the number and morphology of more than 40 cell types, from acanthocytosis to vacuolated white blood cells. Disagreement exists about the clinical significance of many of these observations.1013 And only a few components of the manual differential, for example, nucleated red blood cells (NRBCs) and lymphocytosis, have been quantitatively evaluated to determine their prognostic significance.1417 But these two observations have not been examined to determine their independent contributions to predictions of mortality when taken in conjunction with their accompanying CBC observations. Which of the numerous cell types and cell counts in the commonly ordered CBC, indicate that a patient is at high risk of death? In this article we report an inpatient study that used univariate and multivariate analyses of admission CBCs to predict 30‐day mortality in order to answer that question.

METHODS

Patients and Protocol

The institutional review board of Indiana University, Purdue University, Indianapolis, approved this study. We included in the study all adult patients (those at least 18 years old) admitted to Wishard Hospital between January 1, 1993, and December 31, 2002, except for prisoners (for IRB reasons) and obstetric patients (because their 30‐day mortality is very close to zero0.07% at our institution). Wishard Hospital is a large urban hospital that serves a diverse but predominantly inner‐city population in Indianapolis. If a patient was admitted more than once during the 10 years of observation, we included only the first admission in the analysis in order to assure statistical independence of the observations. We extracted data from the Regenstrief Medical Record System (RMRS), a comprehensive medical records system that has demographic data, vital signs, diagnoses, results of clinical tests, and pharmacy information on all inpatient, emergency department, and outpatient encounter sites.18

We obtained the admission and discharge ICD9 and DRG codes to assess the disease patterns associated with individual CBC abnormalities. We obtained these codes from routine hospital case abstractions performed by Wishard Hospital's medical records department using NCoder+ and Quadramed. Patients assigned DRG codes 370‐384 were identified as obstetric and therefore excluded. Using the ICD9 and CPT codes according to the Charlson algorithm, we calculated a Charlson Comorbidity Index value19 for each patient as a marker of coexisting conditions.

Outcomes

The primary outcome was 30‐day mortality counted from the date of admission. We used information from the hospital record (inpatient deaths) and the Indiana state death tapes to determine the dates of death of all patients. Patients were matched to the Indiana death tapes by an algorithm using name, social security number, date of birth, and sex.20

Hemogram and Differential Count Test Methods

The hemogram, differential counts, and blood smear exam results included in this study all came from Wishard Hospital's laboratory. During this study, the hospital used only 2 cell counters, the Coulter STK‐S and the Gen‐S automated blood analyzer (Beckman Coulter, Brea, California), to produce hemogram and automated blood differential counts. Both instruments provided automated differential counts of 5 cell types: neutrophils, lymphocytes, monocytes, basophils, and eosinophils. The latter machine also produced platelet counts and reticulocyte counts, but during the study period these counts were not routinely reported to physicians unless ordered specifically, so we did not include them in the analyses. The laboratory reflexively performed 100‐cell manual differential counts and blood smear exams when abnormalities as defined by College of American Pathologists (CAP) criteria were observed in the automated measures. Both automated blood analyzers used the same automated CAP criteria to decide when to add a manual differential count and blood smear analysis, and these criteria were constant throughout the study. This protocol predicts manual differential abnormalities with high sensitivity, missing less than 1% of important findings in a manual differential.21 When the CAP criteria did not require a manual differential count and blood smear exam, we assumed that those counts unique to a manual count, for example, blast cell count, were zero and that there were no abnormalities in blood smear morphology.

Laboratories may report white blood cells as absolute counts (eg, number of cells/mm3) and/or as percentages. We converted all counts reported as percentages to absolute numbers (eg, WBC count 1000 cell type percent/100). For absolute counts that have both high and low ranges, such as white blood cell (WBC) count, we constructed two binary variables. WBC‐low was 1 when the WBC was below the lower limit of normal; otherwise it was 0. WBC‐high was 1 if the WBC was above the upper limit of normal; otherwise it was 0. For continuous variables such as NRBCs or blasts where any presence on the manual differential count is abnormal, we constructed binary variables with 0 indicating absence of the cell type and 1 indicating a cell count was at least 1.

Measurements of many cell types in the manual differential count and smear assessment (eg, burr cells) are reported in qualitative terms such as occasional, few, increased, or present, if observed, or none seen, unremarkable, or no mention, if not observed. We dichotomized all such results as present or absent for analysis purposes.

Statistical Analysis

For all the original variables, we plotted cell counts against 30‐day mortality to graphically show this univariate association. To screen the effects of these 45 binary CBC variables univariately, we used each as the sole independent variable in a logistic regression model with 30‐day mortality as the dependent variable.

The simultaneous effects of the 45 CBC measures on mortality were investigated using multiple logistic regression models, always controlling for patient age (in years, as a continuous variable) and sex (as a dichotomous variable). Two approaches were taken to handle the large number of predictors in the model. First, we formed subgroups of predictors based on clinical judgment (eg, the subgroup of bands, Dohle bodies, and toxic granules associated with infections) and ran logistic regressions of each subgroup to choose the significant predictors of these subgroups to fit them into an overall prediction model of 30‐day mortality. The results were verified using a second approach that did not depend on subjective judgment. Both backward and forward stepwise variable selection procedures were used to choose the subset of significant predictors (P < .005) of 30‐day mortality in logistic regression, again controlling for age and sex. To be sure that the predictive power of the models was not decreased by converting continuous variables into categorical variables, we also ran models that included the continuous variables as potential predictors. We used the c statistic as a measure of the goodness‐of‐fit of the models. We included the Charlson Index and the 10 most common admission diagnoses in our model to control for comorbidities and prime reason for admission, respectively.

We performed the analysis using SAS software, version 8.02 (SAS Institute, Inc., Cary, NC).

Chart Review

For each independent predictor of 30‐day mortality that was both statistically significant and had a very high relative risk (>2.5), one author (A.K.) took a random sample of 100200 patients with positive values for this predictor and reviewed the dictated discharge summaries in order to asses the clinical correlates of these findings.

RESULTS

During the 10 years from January 1993 through December 2002, physicians admitted 46,522 unique eligible patients to Wishard Memorial Hospital. Each patient averaged 2 admissions during the study period, for a total of 94,582 admissions. The overall 30‐day mortality of these admissions was 3.4%. Automated hemograms (white blood cell count, hemoglobin, red cell count, and red blood cell indices) were performed on blood samples from 45,709 of these patients (98%) within one day of admission. Seventy‐seven percent (35,692) had a complete blood count that included an automated differential count plus a reflex manual count and smear when required by the CAP protocol, as well as an automated hemogram. The patients with an admission CBC with differential count had a 30‐day mortality rate of 4%, slightly higher than that of patients who had only a hemogram. The patients' mean Charlson score for the CBC with differential count was 0.83, which was lower than the national average, which is closer to 1.22 Table 1 shows the demographics of this study population.

Characteristics of 35,692 Unique Patients with a CBC and Automated Differential Count
CharacteristicValue
Average age (years)46.2 17.7
Average LOS (days)6.5 8.1
Male (%)55.4
Race
White (%)52.9
Black (%)43.4
Other (%)3.7
Charlson Index (mean)0.83 1.5
Most common admission diagnoses (ICD9)Chest pain
 Pneumonia, organism unspecified
 Other symptoms involving abdomen or pelvis
 Unspecified heart failure
 Intermediate coronary syndrome
 Unspecified hemorrhage of GI tract
 Acute but ill‐defined cerebrovascular disease
 Diseases of pancreas
 Cellulitis and abscess of leg except foot
 Convulsions

Predictors of 30‐Day Mortality

We examined the univariate effect of age, sex, and the 45 CBC variables (Table 2) on 30‐day mortality. Most of these variables showed a significant (P < .0001) effect on mortality. Only a few abnormalities, for example, a low WBC (< 5000/L), basophilia (>200/L), and eosinophilia (>450/L), were unrelated to 30‐day mortality. Increasing age and male sex were associated with increased mortality. Of the 45 CBC variables, 29 were strong (P < .0001) univariate predictors of mortality and had odds ratios (ORs) greater than 2.5. Eight variables had univariate ORs greater than 4: toxic granules, Dohle bodies, smudge cells, promyelocytes, myelocytes, metamyelocytes, NRBCs, and burr cells. All but 2 of these are white blood cell observations.

Univariate Risk of 30‐Day Mortality in Patients with an Admission CBC and Automated Differential Count
  Number (%)Odds ratioP value
HemogramAge ( 18 years)35,688 (100)1.039< .0001
Sex (male)19,788 (55.4)1.420<.0001
 WBC > 12,00011,124 (31.2)2.049<.0001
 WBC < 50002176 (6.1)0.938.5765
 Hematocrit (>54)212 (0.6)2.633<.0001
 Hematocrit (<37)8687 (24.3)2.359<.0001
 MCV (>94)6552 (18.4)1.584<.0001
 MCV (<80)2815 (7.9)1.258.0121
 High RDW (>14.5)9478 (26.6)2.647<.0001
 High MCH (>32)5308 (14.9)1.367<.0001
 Low MCH (<26)2064 (5.8)1.392.0011
 High MCHC (>36)28 (0.1)3.964.0109
 Low MCHC (<32)738 (2.1)2.190<.0001
 Automated differential countNeutrophilia (>7700)10,578 (37.8)1.601<.0001
Neutropenia (<1500)469 (1.3)2.831<.0001
 Basophilia (>200)1137 (3.2)1.362.0215
 Eosinophilia (>450)1529 (4.3)1.074.5788
 Monocytosis (>800)10,066 (28.2)1.262<.0001
 Lymphocytosis (>4000)3046 (8.5)2.495<.0001
Manual differential countBlast cells (Y/N)31 (0.1)1.638.5001
Myelocytes (Y/N)215 (0.6)8.231< .0001
 Promyelocytes (Y/N)25 (0.1)13.429< .0001
 Metamyeloctyes (Y/N)905 (2.5)5.798< .0001
 Atypical lymphocytes (Y/N)1303 (3.7)1.881< .0001
 Hypersegmented neutrophils (Y/N)141 (0.4)3.061< .0001
 Microcytes (Y/N)3452 (9.7)2.578< .0001
 Macrocytes (Y/N)3475 (9.7)3.282< .0001
 Hypochromic RBCs (Y/N)2252 (6.3)2.290< .0001
 Basophilic stippling (Y/N)273 (0.8)3.553< .0001
 Target cells (Y/N)1140 (3.2)2.866< .0001
 Polychromasia (Y/N)1675 (4.7)3.622< .0001
 Toxic granules (Y/N)1063 (3.0)4.021< .0001
 Dohle bodies (Y/N)524 (1.5)4.821< .0001
 Ovalocytes (Y/N)1555 (4.4)2.558< .0001
 Spherocytes (Y/N)465 (1.3)3.132< .0001
 Schistocytes (Y/N)1484 (4.2)3.150< .0001
 Sickle Cells (Y/N)62 (0.2)0.389.3490
 Howell‐Jolly bodies (Y/N)71 (0.2)3.025.0033
 Pappenheimer bodies (Y/N)67 (0.2)2.344.0468
 Burr cells (Y/N)253 (0.7)9.297<.0001
 Teardrop cells (Y/N)538 (1.5)2.150< .0001
 Vacuolated cells (Y/N)897 (2.5)3.667< .0001
 Giant platelets (Y/N)781 (2.2)3.102< .0001
 Smudge cells (Y/N)50 (0.1)5.237< .0001
 Cleaved cells (Y/N)8 (0.0)3.393.2533
 Band forms (Y/N)7594 (21.3)2.964< .0001
 NRBCs (Y/N)467 (1.3)8.756< .0001

All the statistical approaches produced essentially the same model for predicting mortality. Table 3 shows that age, sex, and 13 of the CBC variables were retained in the final model of dichotomous variables using backward and forward selection. Lymphocytosis, burr cells, and NRBCs were the greatest independent predictors of mortality, with odds ratios greater than 2.5. Only 1 variable, sickle cells, predicted reduced mortality (with an odds ratio well below 1).

Multivariate Model of Statistically Significant (P < .005) Predictors of 30‐Day Mortality from the CBC and Automated Differential Count Pared Stepwise Backward Selection
ParameterOdds ratioConfidence intervalP value
Age (years)1.0401.0371.043< .0001
Sex (male)1.9651.7462.213< .0001
WBC > 12,0001.7011.5081.919< .0001
Hematocrit (>54)2.3311.4383.780< .0006
Hematocrit (<37)1.7141.5141.941< .0001
MCV (>94)1.3521.1861.543< .0001
High RDW (>14.5)1.4631.2911.658< .0001
Lymphocytosis (>4000)2.8482.4353.332< .0001
Metamyeloctye (Y/N)2.0741.6662.581< .0001
Macrocytes (Y/N)1.3171.1271.539< .0005
Toxic granules (Y/N)1.4941.2001.859.0003
Sickle cells (Y/N)0.0390.0050.292.0016
Burr cells (Y/N)3.2542.3474.513< .0001
Band forms (Y/N)1.5861.3861.814< .0001
NRBCs (Y/N)2.9062.2403.770< .0001

The c statistic (the ratio of the area under the ROC curve to the whole area, which reflects the overall predictive power of the final model), was about 0.80 by any approach, which compared favorably with previous prediction models.3, 4 Using continuous measures of CBC in the model did not increase the predictive power. Inclusion of the Charlson Index and the top 10 admission diagnoses did not significantly change the prediction model, although 2 admission diagnoses, chest pain and acute but ill‐defined cerebrovascular disease, emerged as independent predictors of 30‐day mortality, with odds ratios of 0.314 and 2.033, respectively, at P < .0001.

Chart Review

Of the 200 cases with NRBCs, the leading probable causes for this finding were severe hypoxia (average A‐a gradient = 326 mm Hg), acute anemia (average hgb = 6.1 gm/dL), and sickle‐cell anemia. Other diseases associated with NRBCs were infection/sepsis, HIV, solid tumors (breast/lung/colon/prostate), and leukemia or multiple myeloma. Having even a single NRBC at admission correlated with a 25.5% mortality rate. Of note, 30%40% of patients with sickle‐cell disease had NRBCs and moderate anemia (hgb = 8.7 gm/dL) on admission to the hospital, but there was no excess risk of mortality. Indeed, the 49 patients with sickle‐cell disease who had NRBCs at admission had a 30‐day mortality of 0%.

Most of the patients with NRBCs reviewed exhibited overt signs of severe disease, for example, shock, respiratory failure, or severe trauma, in addition to having NRBCs. However, in 2 patients the NRBCs were the only strong signal of disease severity. Both had NRBCs on the day of discharge and were readmitted within 3 days in extremis and died. One was readmitted in fulminant septic shock, likely from a bacterial peritonitis or urinary tract infection, and the other was readmitted in shock, likely from decompensated heart failure.

In univariate analysis, burr cells at admission correlated with a mortality rate of 27.3%. A review of 100 randomly chosen patients with burr cells revealed a pattern of associated diseases, that is, acute renal failure, liver failure, and congestive heart failure, different from that of patients with NRBCs. There was little overlap in the presence of burr cells and NRBCs, but the 12% who had burr cells and NRBCs had a high mortality rate (57%).

Absolute lymphocytosis was associated with a mortality rate of 8.6%. Although univariate analysis showed that the risk with lymphocytosis was not as high as that for patients with NRBCs or burr cells at admission, lymphocytosis was much more common (8.5%), and within the logistic model its presence explained more of the chi‐square statistic than any other variable except age. Indeed, lymphocytosis was a stronger predictor of 30‐day mortality than was high WBCs or anemia. Chart review of 200 patients with lymphocytosis showed a preponderance of them had large physiologic stressors, for example, traumatic tissue injury (surgery) or cerebrovascular injury. In one subset, half the patients (50.9% of 53 patients) who underwent craniotomy for trauma and had absolute lymphocytosis at admission died, compared with 20.8% of 101 patients admitted for the same diagnosis without absolute lymphocytosis.

DISCUSSION

Some investigators have incorporated selected CBC measures, for example, white blood cell count and hemoglobin/hematocrit, into multivariable models that predict mortality or rehospitalizations.6, 7, 9, 23 However, CBC reports can include a spectrum of more than 40 distinct counts and morphologic findings. Our study was the first to take into account all the different variables in the complete blood count and differential to determine elements that independently predict a high risk of mortality.

In addition to age and sex, our multivariable analysis of the 45 CBC variables found 13 independent predictors of mortality. Five were observations about white blood cells: absolute leukocytosis, high band form cell count, the presence of metamyelocytes, the presence of toxic granules, and absolute lymphocytosis. Eight were observations about red blood cells: high hematocrit, low hematocrit, high MCV and the presence of macrocytes, high red cell distribution width, the presence of NRBCs, the presence of burr cells, and the presence of sickle cells. Because controlling for severity of illness by Charlson comorbidity scores did not significantly change the model, the CBC abnormalities among the predictors of mortality did not simply reflect how sick the patients were. Including the 10 most common admission diagnoses did not significantly attenuate our reported odds ratios, suggesting the CBC predictors did not merely reflect the primary reason for admission. Interestingly, however, admission for chest pain did correlate with a greatly reduced risk of 30‐day mortality, which may reflect the low threshold that physicians have for admitting patients with this complaint. Admission for acute but ill‐defined cerebrovascular disease independently predicted a 2‐fold increased risk of 30‐day mortality.

What is the message to physicians from this analysis? Physicians commonly order CBCs and may rely on quick heuristics to sift through the myriad findings in CBC reports. Our analysis focuses physician attention on high‐impact findings in the CBC. We assume that physicians already consider low hematocrit, high hematocrit (a sign of fluid loss and/or chronic hypoxia), high WBC count, high band cell count, and the presence of metamyeloctes (left shift) as important prognostic indicators. These abnormal findings are routinely mentioned at morning report and in a physician's notes.

Physicians, however, may not appreciate the importance of other CBC findings that our analysis found are predictive of mortality. Macrocytosis and a high RDW count (indicating an abnormally wide distribution of red blood cell size) have not previously been reported as predictors of mortality. And although other studies have suggested that bands are not predictors of mortality,11 our study found they were an important prognostic indicator, with an OR =1.59, approaching those of leukocytosis and anemia.

The most impressive predictors of mortality were burr cells, NRBCs, and absolute lymphocytosis. The multivariate ORs of these 3, ranging from 2.8 to 3.2, were the highest of any CBC finding. In univariate analysis, the first 2 were associated with mortality rates 8 to 10 times higher than that of the average admitted patient. There are anecdotal reports in the literature of burr cells being associated with ominous prognoses2426 and more robust statistical analyses showing NRBCs to be associated with increased mortality.14 Lymphocytosis has also been reported as a mortality risk in patients with trauma and emergency medical conditions.15, 16 Our analysis has shown that, indeed, all 3 of these findings are strong independent predictors of mortality.

The presence of sickle cells was also a strong predictor, but of decreased mortality. Patients with sickle cells in their smear had a risk of death one third that of patients without sickle cells. This does not indicate a protective effect. Rather, patients with sickle‐cell disease typically are young and admitted for pain control and other non‐life‐threatening conditions. The presence of NRBCs in patients with sickle‐cell disease appears to be intrinsic to the disease itself and did not have the same implications for mortality as it did for other patients in our study.

The overall logistic model including age, sex, and admission CBC variables had a respectable c statistic for predicting 30‐day mortality of 0.80. This compares well with findings in other multivariable models. For example, the APACHE II score used to predict the mortality of hospitalized critical care patients has a c statistic that ranges from 0.78 to 0.86.3, 27, 28 The APACHE score uses the worst value from the first 2 days after admission for some of its predictors so it cannot provide as early a warning as the admission CBC, and it requires collection of significantly more data. The inclusion of more CBC findings in the APACHE model might increase its predictive accuracy.

Our multivariate analysis was based on a very large number of patient samples using data collected through routine clinical care. However, our study has a number of limitations. The analysis was done at only a single institution, and the exact logistic regression model may not apply to other institutions that have different case mixes and laboratory procedures. Our institution's reported 30‐day mortality rate of 3.4% was lower than the 4.6%11.9% reported in studies of patients admitted to general ward services,2931 but this may be accounted for by the lower‐than‐average Charlson comorbidity scores in our study population. Our risk adjustment by Charlson comorbidity scores may not be as precise as a risk adjustment tailored for our particular institution.32 Our 30‐day mortality rate was calculated using state death tapes, which means we would have missed patients who died outside the state, although we believe this rarely happens. We developed predictive equations on the basis of 30‐day mortality, so we cannot comment on whether the CBC elements predict mortality beyond 30 days. We analyzed most variables as either high or low or as present or absent. Increasing degrees of abnormality may further increase the predictive power of some variables. Finally, the CBC is only one of many tests and clinical findings; it may be that some of these other variables would displace some CBC variables and/or improve the overall predictive power at the time the admission laboratory tests were performed. In this initial study, we have described the prognostic implication of the CBC across a wide range of diagnoses. Future work will focus on the predictive power of commonly gathered variables in more specific conditions (eg, low white blood cell count in sepsis).

Physicians generally have an intuitive ability to identify patients who are seriously ill and at high risk of dying33 and adjust their diagnostic and therapeutic efforts accordingly. Our analysis highlights the value that certain observations in the CBC, notably burr cells, NRBCs, and absolute lymphocytosis, add to physicians' assessments of mortality risk. Even after adjustment for age, sex, comorbidities, common admission diagnoses, and other variables in the CBC, the presence of these findings predicted a 3‐fold increase in 30‐day mortality. Identifying the red flags within this ubiquitously performed test can make the difference in premature discharge or inappropriate triage of patients. Busy physicians can choose from a wide selection of ever‐improving diagnostic tests, yet the workhorse CBC can serve as a simple and early identifier of patients with a poor prognosis.

References
  1. Shapiro MF,Greenfield SG.The complete blood count and leukocyte differential count.Ann Intern Med.1987;106:6574.
  2. Chang R,Wong GY.Prognostic significance of marked leukocytosis in hospitalized patients.J Gen Intern Med.1991;6:199203.
  3. Knaus WA,Wagner DP,Draper EA, et al.The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest.1991;100:16191636.
  4. Knaus WA,Draper EA,Wagner DP,Zimmerman JE.APACHE II: a severity of disease classification system.Crit Care Med.1985;13:818829.
  5. Fine MJ,Auble TE,Yealy DM, et al.A prediction rule to identify low‐risk patients with community‐acquired pneumonia.N Engl J Med.1997;336:243250.
  6. Grimm R,Neaton J,Ludwig W.Prognostic importance of the white blood cell count for coronary, cancer, and all‐cause mortality.JAMA.1985;254:19321937.
  7. Labry LD,Campion E,Glynn R,Vokonas P.White blood cell count as a predictor of mortality: results over 18 years from the Normative Aging Study.J Clin Epidemiol.1990;43:153157.
  8. Frumin AM,Mendell TH,Mintz SS,Novack P,Faulk AT.Nucleated red blood cells in congestive heart failure.Circulation.1959;20:367370.
  9. Mozaffarian D,Nye R,Levy WC.Anemia predicts mortality in severe heart failure: the prospective randomized amlodipine survival evaluation (PRAISE).J Am Coll Cardiol.2003;41:19331939.
  10. Ardron MJ,Westengard JC,Dutcher TF.Band neutrophil counts are unnecessary for the diagnosis of infection in patients with normal total leukocyte counts.Am J Clin Pathol.1994;102:646649.
  11. Brigden M,Page N.The lack of clinical utility of white blood cell differential counts and blood morphology in elderly individuals with normal hematology profiles.Arch Pathol Lab Med.1990;114:394398.
  12. Wenz B,Gennis P,Canova C,Burns ER.The clinical utility of the leucocyte differential in emergency medicine.Am J Clin Pathol.1986;86:298303.
  13. Wile MJ,Homer LD,Gaehler S,Phillips S,Millan J.Manual differential cell counts help predict bacterial infection.Am J Clin Pathol.2001;115:644649.
  14. Schwartz SO,Stansbury F.Significance of nucleated red blood cells in peripheral blood; analysis of 1,496 cases.JAMA.1954;154:13391340.
  15. Stachon A,Sondermann N,Imohl M,Krieg M.Nucleated red blood cells indicate high risk of in‐hospital mortality.J Lab Clin Med.2002;140:407412.
  16. Teggatz JR,Parkin J,Peterson L.Transient atypical lymphocytosis in patients with emergency medical conditions.Arch Pathol Lab Med.1987;111:712714.
  17. Pinkerton PH,McLellan BA,Quantz MC,Robinson JB.Acute lymphocytosis after trauma—early recognition of the high‐risk patient?J Trauma.1989;29:749751.
  18. McDonald CJ,Overhage JM,Tierney WM, et al.The Regenstrief Medical Record System: a quarter century experience.Int J Med Inf.1999;54:225253.
  19. Charlson M,Szatrowski TP,Peterson J,Gold J.Validation of a combined comorbidity index.J Clin Epidemiol.1994;47:12451251.
  20. Grannis S,Overhage JM,McDonald CJ.Real world performance of approximate string comparators for use in patient matching.Medinfo.2004;11(Pt1):4347.
  21. Picard F,Gicquel C,Marnet L,Guesnu M,Levy JP.Preliminary evaluation of the new hematology analyzer COULTER GEN‐S in a university hospital.Clin Chem Lab Med.1999;37:681686.
  22. Rosenthal GE,Kaboli PJ,Barnett MJ.Differences in length of stay in veterans health administration and other united states hospitals: is the gap closing?Med Care.2003;41:882894.
  23. Kosiborod M,Smith G,Radford M,Foody J,Krumholz H.The Prognostic importance of anemia in patients with heart failure.Am J Med.2003;114:112119.
  24. Schwartz SO,Motto SA.The diagnostic significance of “burr” red blood cells.Am J Med Sci.1949;218:563.
  25. Aherne WA.The “burr” red cell and azotemia.J Clin Pathol.1957;10:252257.
  26. Bell RE.The origin of ‘burr’ erythrocytes.Br J Haematol.1963;9:552555.
  27. de Keizer NF,Bonsel GJ,Goldfad C,Rowan KM.The added value that increasing levels of diagnostic information provide in prognostic models to estimate hospital mortality for adult intensive care patients.Intern Care Med.2000;26:577584.
  28. Harrell F,Califf R,Pryor D,Lee K,Rosati R.Evaluating the yield of medical tests.JAMA.1982;247:25432546.
  29. Meltzer D,Manning WG,Morrison J, et al.Effects of physician experience on costs and outcomes on an academic general medical service: results of a trial of hospitalists.Ann Intern Med.2002;137:866874.
  30. Kearns PJ,Wang CC,Morris WJ, et al.Hospital care by hospital‐based and clinic‐based faculty. a prospective, controlled trial.Arch Intern Med.2001;161:235241.
  31. Auerbach AD,Wachter RM,Katz P,Showstack J,Baron RB,Goldman L.Implementation of a voluntary hospitalist service at a community teaching hospital: improved clinical efficiency and patient outcomes.Ann Intern Med.2002;137:859865.
  32. Rosenthal GE,Harper DL,Quinn LM,Cooper GS.Severity‐adjusted mortality and length of stay in teaching and nonteaching hospitals: results of a regional study.JAMA.1997;278:485490.
  33. McClish DK,Powell SH.How well can physicians estimate mortality in a medical intensive care unit?Med Decis Mak.1989;9:125132.
Article PDF
Issue
Journal of Hospital Medicine - 2(1)
Page Number
5-12
Legacy Keywords
diagnostic decision making, laboratory testing, electronic medical record
Sections
Article PDF
Article PDF

The complete blood count (CBC) bundles the automated hemogram, an automated differential count of 5 types of cells, and a reflex manual differential count (when required by protocol) and is one of the most frequently ordered laboratory tests on admission to the hospital. In practice, it is a routine ingredient of all hospital admission ordersphysicians order a hemogram either alone or as part of a complete blood count for 98% of our medical/surgical admissions, and the same is true at most institutions.1 We know that the white blood cell count and hematocrit from the automated hemogram predict disease severity and mortality risk.25 For example, elevated WBC counts predict a worse prognosis in patients with cancer or coronary artery disease,6, 7 and anemia predicts increased risk of death of patients with heart failure.8, 9 Further, these two tests provide direct management guidance in common circumstances, for example, bleeding and infection.

The CBC describes the number and morphology of more than 40 cell types, from acanthocytosis to vacuolated white blood cells. Disagreement exists about the clinical significance of many of these observations.1013 And only a few components of the manual differential, for example, nucleated red blood cells (NRBCs) and lymphocytosis, have been quantitatively evaluated to determine their prognostic significance.1417 But these two observations have not been examined to determine their independent contributions to predictions of mortality when taken in conjunction with their accompanying CBC observations. Which of the numerous cell types and cell counts in the commonly ordered CBC, indicate that a patient is at high risk of death? In this article we report an inpatient study that used univariate and multivariate analyses of admission CBCs to predict 30‐day mortality in order to answer that question.

METHODS

Patients and Protocol

The institutional review board of Indiana University, Purdue University, Indianapolis, approved this study. We included in the study all adult patients (those at least 18 years old) admitted to Wishard Hospital between January 1, 1993, and December 31, 2002, except for prisoners (for IRB reasons) and obstetric patients (because their 30‐day mortality is very close to zero0.07% at our institution). Wishard Hospital is a large urban hospital that serves a diverse but predominantly inner‐city population in Indianapolis. If a patient was admitted more than once during the 10 years of observation, we included only the first admission in the analysis in order to assure statistical independence of the observations. We extracted data from the Regenstrief Medical Record System (RMRS), a comprehensive medical records system that has demographic data, vital signs, diagnoses, results of clinical tests, and pharmacy information on all inpatient, emergency department, and outpatient encounter sites.18

We obtained the admission and discharge ICD9 and DRG codes to assess the disease patterns associated with individual CBC abnormalities. We obtained these codes from routine hospital case abstractions performed by Wishard Hospital's medical records department using NCoder+ and Quadramed. Patients assigned DRG codes 370‐384 were identified as obstetric and therefore excluded. Using the ICD9 and CPT codes according to the Charlson algorithm, we calculated a Charlson Comorbidity Index value19 for each patient as a marker of coexisting conditions.

Outcomes

The primary outcome was 30‐day mortality counted from the date of admission. We used information from the hospital record (inpatient deaths) and the Indiana state death tapes to determine the dates of death of all patients. Patients were matched to the Indiana death tapes by an algorithm using name, social security number, date of birth, and sex.20

Hemogram and Differential Count Test Methods

The hemogram, differential counts, and blood smear exam results included in this study all came from Wishard Hospital's laboratory. During this study, the hospital used only 2 cell counters, the Coulter STK‐S and the Gen‐S automated blood analyzer (Beckman Coulter, Brea, California), to produce hemogram and automated blood differential counts. Both instruments provided automated differential counts of 5 cell types: neutrophils, lymphocytes, monocytes, basophils, and eosinophils. The latter machine also produced platelet counts and reticulocyte counts, but during the study period these counts were not routinely reported to physicians unless ordered specifically, so we did not include them in the analyses. The laboratory reflexively performed 100‐cell manual differential counts and blood smear exams when abnormalities as defined by College of American Pathologists (CAP) criteria were observed in the automated measures. Both automated blood analyzers used the same automated CAP criteria to decide when to add a manual differential count and blood smear analysis, and these criteria were constant throughout the study. This protocol predicts manual differential abnormalities with high sensitivity, missing less than 1% of important findings in a manual differential.21 When the CAP criteria did not require a manual differential count and blood smear exam, we assumed that those counts unique to a manual count, for example, blast cell count, were zero and that there were no abnormalities in blood smear morphology.

Laboratories may report white blood cells as absolute counts (eg, number of cells/mm3) and/or as percentages. We converted all counts reported as percentages to absolute numbers (eg, WBC count 1000 cell type percent/100). For absolute counts that have both high and low ranges, such as white blood cell (WBC) count, we constructed two binary variables. WBC‐low was 1 when the WBC was below the lower limit of normal; otherwise it was 0. WBC‐high was 1 if the WBC was above the upper limit of normal; otherwise it was 0. For continuous variables such as NRBCs or blasts where any presence on the manual differential count is abnormal, we constructed binary variables with 0 indicating absence of the cell type and 1 indicating a cell count was at least 1.

Measurements of many cell types in the manual differential count and smear assessment (eg, burr cells) are reported in qualitative terms such as occasional, few, increased, or present, if observed, or none seen, unremarkable, or no mention, if not observed. We dichotomized all such results as present or absent for analysis purposes.

Statistical Analysis

For all the original variables, we plotted cell counts against 30‐day mortality to graphically show this univariate association. To screen the effects of these 45 binary CBC variables univariately, we used each as the sole independent variable in a logistic regression model with 30‐day mortality as the dependent variable.

The simultaneous effects of the 45 CBC measures on mortality were investigated using multiple logistic regression models, always controlling for patient age (in years, as a continuous variable) and sex (as a dichotomous variable). Two approaches were taken to handle the large number of predictors in the model. First, we formed subgroups of predictors based on clinical judgment (eg, the subgroup of bands, Dohle bodies, and toxic granules associated with infections) and ran logistic regressions of each subgroup to choose the significant predictors of these subgroups to fit them into an overall prediction model of 30‐day mortality. The results were verified using a second approach that did not depend on subjective judgment. Both backward and forward stepwise variable selection procedures were used to choose the subset of significant predictors (P < .005) of 30‐day mortality in logistic regression, again controlling for age and sex. To be sure that the predictive power of the models was not decreased by converting continuous variables into categorical variables, we also ran models that included the continuous variables as potential predictors. We used the c statistic as a measure of the goodness‐of‐fit of the models. We included the Charlson Index and the 10 most common admission diagnoses in our model to control for comorbidities and prime reason for admission, respectively.

We performed the analysis using SAS software, version 8.02 (SAS Institute, Inc., Cary, NC).

Chart Review

For each independent predictor of 30‐day mortality that was both statistically significant and had a very high relative risk (>2.5), one author (A.K.) took a random sample of 100200 patients with positive values for this predictor and reviewed the dictated discharge summaries in order to asses the clinical correlates of these findings.

RESULTS

During the 10 years from January 1993 through December 2002, physicians admitted 46,522 unique eligible patients to Wishard Memorial Hospital. Each patient averaged 2 admissions during the study period, for a total of 94,582 admissions. The overall 30‐day mortality of these admissions was 3.4%. Automated hemograms (white blood cell count, hemoglobin, red cell count, and red blood cell indices) were performed on blood samples from 45,709 of these patients (98%) within one day of admission. Seventy‐seven percent (35,692) had a complete blood count that included an automated differential count plus a reflex manual count and smear when required by the CAP protocol, as well as an automated hemogram. The patients with an admission CBC with differential count had a 30‐day mortality rate of 4%, slightly higher than that of patients who had only a hemogram. The patients' mean Charlson score for the CBC with differential count was 0.83, which was lower than the national average, which is closer to 1.22 Table 1 shows the demographics of this study population.

Characteristics of 35,692 Unique Patients with a CBC and Automated Differential Count
CharacteristicValue
Average age (years)46.2 17.7
Average LOS (days)6.5 8.1
Male (%)55.4
Race
White (%)52.9
Black (%)43.4
Other (%)3.7
Charlson Index (mean)0.83 1.5
Most common admission diagnoses (ICD9)Chest pain
 Pneumonia, organism unspecified
 Other symptoms involving abdomen or pelvis
 Unspecified heart failure
 Intermediate coronary syndrome
 Unspecified hemorrhage of GI tract
 Acute but ill‐defined cerebrovascular disease
 Diseases of pancreas
 Cellulitis and abscess of leg except foot
 Convulsions

Predictors of 30‐Day Mortality

We examined the univariate effect of age, sex, and the 45 CBC variables (Table 2) on 30‐day mortality. Most of these variables showed a significant (P < .0001) effect on mortality. Only a few abnormalities, for example, a low WBC (< 5000/L), basophilia (>200/L), and eosinophilia (>450/L), were unrelated to 30‐day mortality. Increasing age and male sex were associated with increased mortality. Of the 45 CBC variables, 29 were strong (P < .0001) univariate predictors of mortality and had odds ratios (ORs) greater than 2.5. Eight variables had univariate ORs greater than 4: toxic granules, Dohle bodies, smudge cells, promyelocytes, myelocytes, metamyelocytes, NRBCs, and burr cells. All but 2 of these are white blood cell observations.

Univariate Risk of 30‐Day Mortality in Patients with an Admission CBC and Automated Differential Count
  Number (%)Odds ratioP value
HemogramAge ( 18 years)35,688 (100)1.039< .0001
Sex (male)19,788 (55.4)1.420<.0001
 WBC > 12,00011,124 (31.2)2.049<.0001
 WBC < 50002176 (6.1)0.938.5765
 Hematocrit (>54)212 (0.6)2.633<.0001
 Hematocrit (<37)8687 (24.3)2.359<.0001
 MCV (>94)6552 (18.4)1.584<.0001
 MCV (<80)2815 (7.9)1.258.0121
 High RDW (>14.5)9478 (26.6)2.647<.0001
 High MCH (>32)5308 (14.9)1.367<.0001
 Low MCH (<26)2064 (5.8)1.392.0011
 High MCHC (>36)28 (0.1)3.964.0109
 Low MCHC (<32)738 (2.1)2.190<.0001
 Automated differential countNeutrophilia (>7700)10,578 (37.8)1.601<.0001
Neutropenia (<1500)469 (1.3)2.831<.0001
 Basophilia (>200)1137 (3.2)1.362.0215
 Eosinophilia (>450)1529 (4.3)1.074.5788
 Monocytosis (>800)10,066 (28.2)1.262<.0001
 Lymphocytosis (>4000)3046 (8.5)2.495<.0001
Manual differential countBlast cells (Y/N)31 (0.1)1.638.5001
Myelocytes (Y/N)215 (0.6)8.231< .0001
 Promyelocytes (Y/N)25 (0.1)13.429< .0001
 Metamyeloctyes (Y/N)905 (2.5)5.798< .0001
 Atypical lymphocytes (Y/N)1303 (3.7)1.881< .0001
 Hypersegmented neutrophils (Y/N)141 (0.4)3.061< .0001
 Microcytes (Y/N)3452 (9.7)2.578< .0001
 Macrocytes (Y/N)3475 (9.7)3.282< .0001
 Hypochromic RBCs (Y/N)2252 (6.3)2.290< .0001
 Basophilic stippling (Y/N)273 (0.8)3.553< .0001
 Target cells (Y/N)1140 (3.2)2.866< .0001
 Polychromasia (Y/N)1675 (4.7)3.622< .0001
 Toxic granules (Y/N)1063 (3.0)4.021< .0001
 Dohle bodies (Y/N)524 (1.5)4.821< .0001
 Ovalocytes (Y/N)1555 (4.4)2.558< .0001
 Spherocytes (Y/N)465 (1.3)3.132< .0001
 Schistocytes (Y/N)1484 (4.2)3.150< .0001
 Sickle Cells (Y/N)62 (0.2)0.389.3490
 Howell‐Jolly bodies (Y/N)71 (0.2)3.025.0033
 Pappenheimer bodies (Y/N)67 (0.2)2.344.0468
 Burr cells (Y/N)253 (0.7)9.297<.0001
 Teardrop cells (Y/N)538 (1.5)2.150< .0001
 Vacuolated cells (Y/N)897 (2.5)3.667< .0001
 Giant platelets (Y/N)781 (2.2)3.102< .0001
 Smudge cells (Y/N)50 (0.1)5.237< .0001
 Cleaved cells (Y/N)8 (0.0)3.393.2533
 Band forms (Y/N)7594 (21.3)2.964< .0001
 NRBCs (Y/N)467 (1.3)8.756< .0001

All the statistical approaches produced essentially the same model for predicting mortality. Table 3 shows that age, sex, and 13 of the CBC variables were retained in the final model of dichotomous variables using backward and forward selection. Lymphocytosis, burr cells, and NRBCs were the greatest independent predictors of mortality, with odds ratios greater than 2.5. Only 1 variable, sickle cells, predicted reduced mortality (with an odds ratio well below 1).

Multivariate Model of Statistically Significant (P < .005) Predictors of 30‐Day Mortality from the CBC and Automated Differential Count Pared Stepwise Backward Selection
ParameterOdds ratioConfidence intervalP value
Age (years)1.0401.0371.043< .0001
Sex (male)1.9651.7462.213< .0001
WBC > 12,0001.7011.5081.919< .0001
Hematocrit (>54)2.3311.4383.780< .0006
Hematocrit (<37)1.7141.5141.941< .0001
MCV (>94)1.3521.1861.543< .0001
High RDW (>14.5)1.4631.2911.658< .0001
Lymphocytosis (>4000)2.8482.4353.332< .0001
Metamyeloctye (Y/N)2.0741.6662.581< .0001
Macrocytes (Y/N)1.3171.1271.539< .0005
Toxic granules (Y/N)1.4941.2001.859.0003
Sickle cells (Y/N)0.0390.0050.292.0016
Burr cells (Y/N)3.2542.3474.513< .0001
Band forms (Y/N)1.5861.3861.814< .0001
NRBCs (Y/N)2.9062.2403.770< .0001

The c statistic (the ratio of the area under the ROC curve to the whole area, which reflects the overall predictive power of the final model), was about 0.80 by any approach, which compared favorably with previous prediction models.3, 4 Using continuous measures of CBC in the model did not increase the predictive power. Inclusion of the Charlson Index and the top 10 admission diagnoses did not significantly change the prediction model, although 2 admission diagnoses, chest pain and acute but ill‐defined cerebrovascular disease, emerged as independent predictors of 30‐day mortality, with odds ratios of 0.314 and 2.033, respectively, at P < .0001.

Chart Review

Of the 200 cases with NRBCs, the leading probable causes for this finding were severe hypoxia (average A‐a gradient = 326 mm Hg), acute anemia (average hgb = 6.1 gm/dL), and sickle‐cell anemia. Other diseases associated with NRBCs were infection/sepsis, HIV, solid tumors (breast/lung/colon/prostate), and leukemia or multiple myeloma. Having even a single NRBC at admission correlated with a 25.5% mortality rate. Of note, 30%40% of patients with sickle‐cell disease had NRBCs and moderate anemia (hgb = 8.7 gm/dL) on admission to the hospital, but there was no excess risk of mortality. Indeed, the 49 patients with sickle‐cell disease who had NRBCs at admission had a 30‐day mortality of 0%.

Most of the patients with NRBCs reviewed exhibited overt signs of severe disease, for example, shock, respiratory failure, or severe trauma, in addition to having NRBCs. However, in 2 patients the NRBCs were the only strong signal of disease severity. Both had NRBCs on the day of discharge and were readmitted within 3 days in extremis and died. One was readmitted in fulminant septic shock, likely from a bacterial peritonitis or urinary tract infection, and the other was readmitted in shock, likely from decompensated heart failure.

In univariate analysis, burr cells at admission correlated with a mortality rate of 27.3%. A review of 100 randomly chosen patients with burr cells revealed a pattern of associated diseases, that is, acute renal failure, liver failure, and congestive heart failure, different from that of patients with NRBCs. There was little overlap in the presence of burr cells and NRBCs, but the 12% who had burr cells and NRBCs had a high mortality rate (57%).

Absolute lymphocytosis was associated with a mortality rate of 8.6%. Although univariate analysis showed that the risk with lymphocytosis was not as high as that for patients with NRBCs or burr cells at admission, lymphocytosis was much more common (8.5%), and within the logistic model its presence explained more of the chi‐square statistic than any other variable except age. Indeed, lymphocytosis was a stronger predictor of 30‐day mortality than was high WBCs or anemia. Chart review of 200 patients with lymphocytosis showed a preponderance of them had large physiologic stressors, for example, traumatic tissue injury (surgery) or cerebrovascular injury. In one subset, half the patients (50.9% of 53 patients) who underwent craniotomy for trauma and had absolute lymphocytosis at admission died, compared with 20.8% of 101 patients admitted for the same diagnosis without absolute lymphocytosis.

DISCUSSION

Some investigators have incorporated selected CBC measures, for example, white blood cell count and hemoglobin/hematocrit, into multivariable models that predict mortality or rehospitalizations.6, 7, 9, 23 However, CBC reports can include a spectrum of more than 40 distinct counts and morphologic findings. Our study was the first to take into account all the different variables in the complete blood count and differential to determine elements that independently predict a high risk of mortality.

In addition to age and sex, our multivariable analysis of the 45 CBC variables found 13 independent predictors of mortality. Five were observations about white blood cells: absolute leukocytosis, high band form cell count, the presence of metamyelocytes, the presence of toxic granules, and absolute lymphocytosis. Eight were observations about red blood cells: high hematocrit, low hematocrit, high MCV and the presence of macrocytes, high red cell distribution width, the presence of NRBCs, the presence of burr cells, and the presence of sickle cells. Because controlling for severity of illness by Charlson comorbidity scores did not significantly change the model, the CBC abnormalities among the predictors of mortality did not simply reflect how sick the patients were. Including the 10 most common admission diagnoses did not significantly attenuate our reported odds ratios, suggesting the CBC predictors did not merely reflect the primary reason for admission. Interestingly, however, admission for chest pain did correlate with a greatly reduced risk of 30‐day mortality, which may reflect the low threshold that physicians have for admitting patients with this complaint. Admission for acute but ill‐defined cerebrovascular disease independently predicted a 2‐fold increased risk of 30‐day mortality.

What is the message to physicians from this analysis? Physicians commonly order CBCs and may rely on quick heuristics to sift through the myriad findings in CBC reports. Our analysis focuses physician attention on high‐impact findings in the CBC. We assume that physicians already consider low hematocrit, high hematocrit (a sign of fluid loss and/or chronic hypoxia), high WBC count, high band cell count, and the presence of metamyeloctes (left shift) as important prognostic indicators. These abnormal findings are routinely mentioned at morning report and in a physician's notes.

Physicians, however, may not appreciate the importance of other CBC findings that our analysis found are predictive of mortality. Macrocytosis and a high RDW count (indicating an abnormally wide distribution of red blood cell size) have not previously been reported as predictors of mortality. And although other studies have suggested that bands are not predictors of mortality,11 our study found they were an important prognostic indicator, with an OR =1.59, approaching those of leukocytosis and anemia.

The most impressive predictors of mortality were burr cells, NRBCs, and absolute lymphocytosis. The multivariate ORs of these 3, ranging from 2.8 to 3.2, were the highest of any CBC finding. In univariate analysis, the first 2 were associated with mortality rates 8 to 10 times higher than that of the average admitted patient. There are anecdotal reports in the literature of burr cells being associated with ominous prognoses2426 and more robust statistical analyses showing NRBCs to be associated with increased mortality.14 Lymphocytosis has also been reported as a mortality risk in patients with trauma and emergency medical conditions.15, 16 Our analysis has shown that, indeed, all 3 of these findings are strong independent predictors of mortality.

The presence of sickle cells was also a strong predictor, but of decreased mortality. Patients with sickle cells in their smear had a risk of death one third that of patients without sickle cells. This does not indicate a protective effect. Rather, patients with sickle‐cell disease typically are young and admitted for pain control and other non‐life‐threatening conditions. The presence of NRBCs in patients with sickle‐cell disease appears to be intrinsic to the disease itself and did not have the same implications for mortality as it did for other patients in our study.

The overall logistic model including age, sex, and admission CBC variables had a respectable c statistic for predicting 30‐day mortality of 0.80. This compares well with findings in other multivariable models. For example, the APACHE II score used to predict the mortality of hospitalized critical care patients has a c statistic that ranges from 0.78 to 0.86.3, 27, 28 The APACHE score uses the worst value from the first 2 days after admission for some of its predictors so it cannot provide as early a warning as the admission CBC, and it requires collection of significantly more data. The inclusion of more CBC findings in the APACHE model might increase its predictive accuracy.

Our multivariate analysis was based on a very large number of patient samples using data collected through routine clinical care. However, our study has a number of limitations. The analysis was done at only a single institution, and the exact logistic regression model may not apply to other institutions that have different case mixes and laboratory procedures. Our institution's reported 30‐day mortality rate of 3.4% was lower than the 4.6%11.9% reported in studies of patients admitted to general ward services,2931 but this may be accounted for by the lower‐than‐average Charlson comorbidity scores in our study population. Our risk adjustment by Charlson comorbidity scores may not be as precise as a risk adjustment tailored for our particular institution.32 Our 30‐day mortality rate was calculated using state death tapes, which means we would have missed patients who died outside the state, although we believe this rarely happens. We developed predictive equations on the basis of 30‐day mortality, so we cannot comment on whether the CBC elements predict mortality beyond 30 days. We analyzed most variables as either high or low or as present or absent. Increasing degrees of abnormality may further increase the predictive power of some variables. Finally, the CBC is only one of many tests and clinical findings; it may be that some of these other variables would displace some CBC variables and/or improve the overall predictive power at the time the admission laboratory tests were performed. In this initial study, we have described the prognostic implication of the CBC across a wide range of diagnoses. Future work will focus on the predictive power of commonly gathered variables in more specific conditions (eg, low white blood cell count in sepsis).

Physicians generally have an intuitive ability to identify patients who are seriously ill and at high risk of dying33 and adjust their diagnostic and therapeutic efforts accordingly. Our analysis highlights the value that certain observations in the CBC, notably burr cells, NRBCs, and absolute lymphocytosis, add to physicians' assessments of mortality risk. Even after adjustment for age, sex, comorbidities, common admission diagnoses, and other variables in the CBC, the presence of these findings predicted a 3‐fold increase in 30‐day mortality. Identifying the red flags within this ubiquitously performed test can make the difference in premature discharge or inappropriate triage of patients. Busy physicians can choose from a wide selection of ever‐improving diagnostic tests, yet the workhorse CBC can serve as a simple and early identifier of patients with a poor prognosis.

The complete blood count (CBC) bundles the automated hemogram, an automated differential count of 5 types of cells, and a reflex manual differential count (when required by protocol) and is one of the most frequently ordered laboratory tests on admission to the hospital. In practice, it is a routine ingredient of all hospital admission ordersphysicians order a hemogram either alone or as part of a complete blood count for 98% of our medical/surgical admissions, and the same is true at most institutions.1 We know that the white blood cell count and hematocrit from the automated hemogram predict disease severity and mortality risk.25 For example, elevated WBC counts predict a worse prognosis in patients with cancer or coronary artery disease,6, 7 and anemia predicts increased risk of death of patients with heart failure.8, 9 Further, these two tests provide direct management guidance in common circumstances, for example, bleeding and infection.

The CBC describes the number and morphology of more than 40 cell types, from acanthocytosis to vacuolated white blood cells. Disagreement exists about the clinical significance of many of these observations.1013 And only a few components of the manual differential, for example, nucleated red blood cells (NRBCs) and lymphocytosis, have been quantitatively evaluated to determine their prognostic significance.1417 But these two observations have not been examined to determine their independent contributions to predictions of mortality when taken in conjunction with their accompanying CBC observations. Which of the numerous cell types and cell counts in the commonly ordered CBC, indicate that a patient is at high risk of death? In this article we report an inpatient study that used univariate and multivariate analyses of admission CBCs to predict 30‐day mortality in order to answer that question.

METHODS

Patients and Protocol

The institutional review board of Indiana University, Purdue University, Indianapolis, approved this study. We included in the study all adult patients (those at least 18 years old) admitted to Wishard Hospital between January 1, 1993, and December 31, 2002, except for prisoners (for IRB reasons) and obstetric patients (because their 30‐day mortality is very close to zero0.07% at our institution). Wishard Hospital is a large urban hospital that serves a diverse but predominantly inner‐city population in Indianapolis. If a patient was admitted more than once during the 10 years of observation, we included only the first admission in the analysis in order to assure statistical independence of the observations. We extracted data from the Regenstrief Medical Record System (RMRS), a comprehensive medical records system that has demographic data, vital signs, diagnoses, results of clinical tests, and pharmacy information on all inpatient, emergency department, and outpatient encounter sites.18

We obtained the admission and discharge ICD9 and DRG codes to assess the disease patterns associated with individual CBC abnormalities. We obtained these codes from routine hospital case abstractions performed by Wishard Hospital's medical records department using NCoder+ and Quadramed. Patients assigned DRG codes 370‐384 were identified as obstetric and therefore excluded. Using the ICD9 and CPT codes according to the Charlson algorithm, we calculated a Charlson Comorbidity Index value19 for each patient as a marker of coexisting conditions.

Outcomes

The primary outcome was 30‐day mortality counted from the date of admission. We used information from the hospital record (inpatient deaths) and the Indiana state death tapes to determine the dates of death of all patients. Patients were matched to the Indiana death tapes by an algorithm using name, social security number, date of birth, and sex.20

Hemogram and Differential Count Test Methods

The hemogram, differential counts, and blood smear exam results included in this study all came from Wishard Hospital's laboratory. During this study, the hospital used only 2 cell counters, the Coulter STK‐S and the Gen‐S automated blood analyzer (Beckman Coulter, Brea, California), to produce hemogram and automated blood differential counts. Both instruments provided automated differential counts of 5 cell types: neutrophils, lymphocytes, monocytes, basophils, and eosinophils. The latter machine also produced platelet counts and reticulocyte counts, but during the study period these counts were not routinely reported to physicians unless ordered specifically, so we did not include them in the analyses. The laboratory reflexively performed 100‐cell manual differential counts and blood smear exams when abnormalities as defined by College of American Pathologists (CAP) criteria were observed in the automated measures. Both automated blood analyzers used the same automated CAP criteria to decide when to add a manual differential count and blood smear analysis, and these criteria were constant throughout the study. This protocol predicts manual differential abnormalities with high sensitivity, missing less than 1% of important findings in a manual differential.21 When the CAP criteria did not require a manual differential count and blood smear exam, we assumed that those counts unique to a manual count, for example, blast cell count, were zero and that there were no abnormalities in blood smear morphology.

Laboratories may report white blood cells as absolute counts (eg, number of cells/mm3) and/or as percentages. We converted all counts reported as percentages to absolute numbers (eg, WBC count 1000 cell type percent/100). For absolute counts that have both high and low ranges, such as white blood cell (WBC) count, we constructed two binary variables. WBC‐low was 1 when the WBC was below the lower limit of normal; otherwise it was 0. WBC‐high was 1 if the WBC was above the upper limit of normal; otherwise it was 0. For continuous variables such as NRBCs or blasts where any presence on the manual differential count is abnormal, we constructed binary variables with 0 indicating absence of the cell type and 1 indicating a cell count was at least 1.

Measurements of many cell types in the manual differential count and smear assessment (eg, burr cells) are reported in qualitative terms such as occasional, few, increased, or present, if observed, or none seen, unremarkable, or no mention, if not observed. We dichotomized all such results as present or absent for analysis purposes.

Statistical Analysis

For all the original variables, we plotted cell counts against 30‐day mortality to graphically show this univariate association. To screen the effects of these 45 binary CBC variables univariately, we used each as the sole independent variable in a logistic regression model with 30‐day mortality as the dependent variable.

The simultaneous effects of the 45 CBC measures on mortality were investigated using multiple logistic regression models, always controlling for patient age (in years, as a continuous variable) and sex (as a dichotomous variable). Two approaches were taken to handle the large number of predictors in the model. First, we formed subgroups of predictors based on clinical judgment (eg, the subgroup of bands, Dohle bodies, and toxic granules associated with infections) and ran logistic regressions of each subgroup to choose the significant predictors of these subgroups to fit them into an overall prediction model of 30‐day mortality. The results were verified using a second approach that did not depend on subjective judgment. Both backward and forward stepwise variable selection procedures were used to choose the subset of significant predictors (P < .005) of 30‐day mortality in logistic regression, again controlling for age and sex. To be sure that the predictive power of the models was not decreased by converting continuous variables into categorical variables, we also ran models that included the continuous variables as potential predictors. We used the c statistic as a measure of the goodness‐of‐fit of the models. We included the Charlson Index and the 10 most common admission diagnoses in our model to control for comorbidities and prime reason for admission, respectively.

We performed the analysis using SAS software, version 8.02 (SAS Institute, Inc., Cary, NC).

Chart Review

For each independent predictor of 30‐day mortality that was both statistically significant and had a very high relative risk (>2.5), one author (A.K.) took a random sample of 100200 patients with positive values for this predictor and reviewed the dictated discharge summaries in order to asses the clinical correlates of these findings.

RESULTS

During the 10 years from January 1993 through December 2002, physicians admitted 46,522 unique eligible patients to Wishard Memorial Hospital. Each patient averaged 2 admissions during the study period, for a total of 94,582 admissions. The overall 30‐day mortality of these admissions was 3.4%. Automated hemograms (white blood cell count, hemoglobin, red cell count, and red blood cell indices) were performed on blood samples from 45,709 of these patients (98%) within one day of admission. Seventy‐seven percent (35,692) had a complete blood count that included an automated differential count plus a reflex manual count and smear when required by the CAP protocol, as well as an automated hemogram. The patients with an admission CBC with differential count had a 30‐day mortality rate of 4%, slightly higher than that of patients who had only a hemogram. The patients' mean Charlson score for the CBC with differential count was 0.83, which was lower than the national average, which is closer to 1.22 Table 1 shows the demographics of this study population.

Characteristics of 35,692 Unique Patients with a CBC and Automated Differential Count
CharacteristicValue
Average age (years)46.2 17.7
Average LOS (days)6.5 8.1
Male (%)55.4
Race
White (%)52.9
Black (%)43.4
Other (%)3.7
Charlson Index (mean)0.83 1.5
Most common admission diagnoses (ICD9)Chest pain
 Pneumonia, organism unspecified
 Other symptoms involving abdomen or pelvis
 Unspecified heart failure
 Intermediate coronary syndrome
 Unspecified hemorrhage of GI tract
 Acute but ill‐defined cerebrovascular disease
 Diseases of pancreas
 Cellulitis and abscess of leg except foot
 Convulsions

Predictors of 30‐Day Mortality

We examined the univariate effect of age, sex, and the 45 CBC variables (Table 2) on 30‐day mortality. Most of these variables showed a significant (P < .0001) effect on mortality. Only a few abnormalities, for example, a low WBC (< 5000/L), basophilia (>200/L), and eosinophilia (>450/L), were unrelated to 30‐day mortality. Increasing age and male sex were associated with increased mortality. Of the 45 CBC variables, 29 were strong (P < .0001) univariate predictors of mortality and had odds ratios (ORs) greater than 2.5. Eight variables had univariate ORs greater than 4: toxic granules, Dohle bodies, smudge cells, promyelocytes, myelocytes, metamyelocytes, NRBCs, and burr cells. All but 2 of these are white blood cell observations.

Univariate Risk of 30‐Day Mortality in Patients with an Admission CBC and Automated Differential Count
  Number (%)Odds ratioP value
HemogramAge ( 18 years)35,688 (100)1.039< .0001
Sex (male)19,788 (55.4)1.420<.0001
 WBC > 12,00011,124 (31.2)2.049<.0001
 WBC < 50002176 (6.1)0.938.5765
 Hematocrit (>54)212 (0.6)2.633<.0001
 Hematocrit (<37)8687 (24.3)2.359<.0001
 MCV (>94)6552 (18.4)1.584<.0001
 MCV (<80)2815 (7.9)1.258.0121
 High RDW (>14.5)9478 (26.6)2.647<.0001
 High MCH (>32)5308 (14.9)1.367<.0001
 Low MCH (<26)2064 (5.8)1.392.0011
 High MCHC (>36)28 (0.1)3.964.0109
 Low MCHC (<32)738 (2.1)2.190<.0001
 Automated differential countNeutrophilia (>7700)10,578 (37.8)1.601<.0001
Neutropenia (<1500)469 (1.3)2.831<.0001
 Basophilia (>200)1137 (3.2)1.362.0215
 Eosinophilia (>450)1529 (4.3)1.074.5788
 Monocytosis (>800)10,066 (28.2)1.262<.0001
 Lymphocytosis (>4000)3046 (8.5)2.495<.0001
Manual differential countBlast cells (Y/N)31 (0.1)1.638.5001
Myelocytes (Y/N)215 (0.6)8.231< .0001
 Promyelocytes (Y/N)25 (0.1)13.429< .0001
 Metamyeloctyes (Y/N)905 (2.5)5.798< .0001
 Atypical lymphocytes (Y/N)1303 (3.7)1.881< .0001
 Hypersegmented neutrophils (Y/N)141 (0.4)3.061< .0001
 Microcytes (Y/N)3452 (9.7)2.578< .0001
 Macrocytes (Y/N)3475 (9.7)3.282< .0001
 Hypochromic RBCs (Y/N)2252 (6.3)2.290< .0001
 Basophilic stippling (Y/N)273 (0.8)3.553< .0001
 Target cells (Y/N)1140 (3.2)2.866< .0001
 Polychromasia (Y/N)1675 (4.7)3.622< .0001
 Toxic granules (Y/N)1063 (3.0)4.021< .0001
 Dohle bodies (Y/N)524 (1.5)4.821< .0001
 Ovalocytes (Y/N)1555 (4.4)2.558< .0001
 Spherocytes (Y/N)465 (1.3)3.132< .0001
 Schistocytes (Y/N)1484 (4.2)3.150< .0001
 Sickle Cells (Y/N)62 (0.2)0.389.3490
 Howell‐Jolly bodies (Y/N)71 (0.2)3.025.0033
 Pappenheimer bodies (Y/N)67 (0.2)2.344.0468
 Burr cells (Y/N)253 (0.7)9.297<.0001
 Teardrop cells (Y/N)538 (1.5)2.150< .0001
 Vacuolated cells (Y/N)897 (2.5)3.667< .0001
 Giant platelets (Y/N)781 (2.2)3.102< .0001
 Smudge cells (Y/N)50 (0.1)5.237< .0001
 Cleaved cells (Y/N)8 (0.0)3.393.2533
 Band forms (Y/N)7594 (21.3)2.964< .0001
 NRBCs (Y/N)467 (1.3)8.756< .0001

All the statistical approaches produced essentially the same model for predicting mortality. Table 3 shows that age, sex, and 13 of the CBC variables were retained in the final model of dichotomous variables using backward and forward selection. Lymphocytosis, burr cells, and NRBCs were the greatest independent predictors of mortality, with odds ratios greater than 2.5. Only 1 variable, sickle cells, predicted reduced mortality (with an odds ratio well below 1).

Multivariate Model of Statistically Significant (P < .005) Predictors of 30‐Day Mortality from the CBC and Automated Differential Count Pared Stepwise Backward Selection
ParameterOdds ratioConfidence intervalP value
Age (years)1.0401.0371.043< .0001
Sex (male)1.9651.7462.213< .0001
WBC > 12,0001.7011.5081.919< .0001
Hematocrit (>54)2.3311.4383.780< .0006
Hematocrit (<37)1.7141.5141.941< .0001
MCV (>94)1.3521.1861.543< .0001
High RDW (>14.5)1.4631.2911.658< .0001
Lymphocytosis (>4000)2.8482.4353.332< .0001
Metamyeloctye (Y/N)2.0741.6662.581< .0001
Macrocytes (Y/N)1.3171.1271.539< .0005
Toxic granules (Y/N)1.4941.2001.859.0003
Sickle cells (Y/N)0.0390.0050.292.0016
Burr cells (Y/N)3.2542.3474.513< .0001
Band forms (Y/N)1.5861.3861.814< .0001
NRBCs (Y/N)2.9062.2403.770< .0001

The c statistic (the ratio of the area under the ROC curve to the whole area, which reflects the overall predictive power of the final model), was about 0.80 by any approach, which compared favorably with previous prediction models.3, 4 Using continuous measures of CBC in the model did not increase the predictive power. Inclusion of the Charlson Index and the top 10 admission diagnoses did not significantly change the prediction model, although 2 admission diagnoses, chest pain and acute but ill‐defined cerebrovascular disease, emerged as independent predictors of 30‐day mortality, with odds ratios of 0.314 and 2.033, respectively, at P < .0001.

Chart Review

Of the 200 cases with NRBCs, the leading probable causes for this finding were severe hypoxia (average A‐a gradient = 326 mm Hg), acute anemia (average hgb = 6.1 gm/dL), and sickle‐cell anemia. Other diseases associated with NRBCs were infection/sepsis, HIV, solid tumors (breast/lung/colon/prostate), and leukemia or multiple myeloma. Having even a single NRBC at admission correlated with a 25.5% mortality rate. Of note, 30%40% of patients with sickle‐cell disease had NRBCs and moderate anemia (hgb = 8.7 gm/dL) on admission to the hospital, but there was no excess risk of mortality. Indeed, the 49 patients with sickle‐cell disease who had NRBCs at admission had a 30‐day mortality of 0%.

Most of the patients with NRBCs reviewed exhibited overt signs of severe disease, for example, shock, respiratory failure, or severe trauma, in addition to having NRBCs. However, in 2 patients the NRBCs were the only strong signal of disease severity. Both had NRBCs on the day of discharge and were readmitted within 3 days in extremis and died. One was readmitted in fulminant septic shock, likely from a bacterial peritonitis or urinary tract infection, and the other was readmitted in shock, likely from decompensated heart failure.

In univariate analysis, burr cells at admission correlated with a mortality rate of 27.3%. A review of 100 randomly chosen patients with burr cells revealed a pattern of associated diseases, that is, acute renal failure, liver failure, and congestive heart failure, different from that of patients with NRBCs. There was little overlap in the presence of burr cells and NRBCs, but the 12% who had burr cells and NRBCs had a high mortality rate (57%).

Absolute lymphocytosis was associated with a mortality rate of 8.6%. Although univariate analysis showed that the risk with lymphocytosis was not as high as that for patients with NRBCs or burr cells at admission, lymphocytosis was much more common (8.5%), and within the logistic model its presence explained more of the chi‐square statistic than any other variable except age. Indeed, lymphocytosis was a stronger predictor of 30‐day mortality than was high WBCs or anemia. Chart review of 200 patients with lymphocytosis showed a preponderance of them had large physiologic stressors, for example, traumatic tissue injury (surgery) or cerebrovascular injury. In one subset, half the patients (50.9% of 53 patients) who underwent craniotomy for trauma and had absolute lymphocytosis at admission died, compared with 20.8% of 101 patients admitted for the same diagnosis without absolute lymphocytosis.

DISCUSSION

Some investigators have incorporated selected CBC measures, for example, white blood cell count and hemoglobin/hematocrit, into multivariable models that predict mortality or rehospitalizations.6, 7, 9, 23 However, CBC reports can include a spectrum of more than 40 distinct counts and morphologic findings. Our study was the first to take into account all the different variables in the complete blood count and differential to determine elements that independently predict a high risk of mortality.

In addition to age and sex, our multivariable analysis of the 45 CBC variables found 13 independent predictors of mortality. Five were observations about white blood cells: absolute leukocytosis, high band form cell count, the presence of metamyelocytes, the presence of toxic granules, and absolute lymphocytosis. Eight were observations about red blood cells: high hematocrit, low hematocrit, high MCV and the presence of macrocytes, high red cell distribution width, the presence of NRBCs, the presence of burr cells, and the presence of sickle cells. Because controlling for severity of illness by Charlson comorbidity scores did not significantly change the model, the CBC abnormalities among the predictors of mortality did not simply reflect how sick the patients were. Including the 10 most common admission diagnoses did not significantly attenuate our reported odds ratios, suggesting the CBC predictors did not merely reflect the primary reason for admission. Interestingly, however, admission for chest pain did correlate with a greatly reduced risk of 30‐day mortality, which may reflect the low threshold that physicians have for admitting patients with this complaint. Admission for acute but ill‐defined cerebrovascular disease independently predicted a 2‐fold increased risk of 30‐day mortality.

What is the message to physicians from this analysis? Physicians commonly order CBCs and may rely on quick heuristics to sift through the myriad findings in CBC reports. Our analysis focuses physician attention on high‐impact findings in the CBC. We assume that physicians already consider low hematocrit, high hematocrit (a sign of fluid loss and/or chronic hypoxia), high WBC count, high band cell count, and the presence of metamyeloctes (left shift) as important prognostic indicators. These abnormal findings are routinely mentioned at morning report and in a physician's notes.

Physicians, however, may not appreciate the importance of other CBC findings that our analysis found are predictive of mortality. Macrocytosis and a high RDW count (indicating an abnormally wide distribution of red blood cell size) have not previously been reported as predictors of mortality. And although other studies have suggested that bands are not predictors of mortality,11 our study found they were an important prognostic indicator, with an OR =1.59, approaching those of leukocytosis and anemia.

The most impressive predictors of mortality were burr cells, NRBCs, and absolute lymphocytosis. The multivariate ORs of these 3, ranging from 2.8 to 3.2, were the highest of any CBC finding. In univariate analysis, the first 2 were associated with mortality rates 8 to 10 times higher than that of the average admitted patient. There are anecdotal reports in the literature of burr cells being associated with ominous prognoses2426 and more robust statistical analyses showing NRBCs to be associated with increased mortality.14 Lymphocytosis has also been reported as a mortality risk in patients with trauma and emergency medical conditions.15, 16 Our analysis has shown that, indeed, all 3 of these findings are strong independent predictors of mortality.

The presence of sickle cells was also a strong predictor, but of decreased mortality. Patients with sickle cells in their smear had a risk of death one third that of patients without sickle cells. This does not indicate a protective effect. Rather, patients with sickle‐cell disease typically are young and admitted for pain control and other non‐life‐threatening conditions. The presence of NRBCs in patients with sickle‐cell disease appears to be intrinsic to the disease itself and did not have the same implications for mortality as it did for other patients in our study.

The overall logistic model including age, sex, and admission CBC variables had a respectable c statistic for predicting 30‐day mortality of 0.80. This compares well with findings in other multivariable models. For example, the APACHE II score used to predict the mortality of hospitalized critical care patients has a c statistic that ranges from 0.78 to 0.86.3, 27, 28 The APACHE score uses the worst value from the first 2 days after admission for some of its predictors so it cannot provide as early a warning as the admission CBC, and it requires collection of significantly more data. The inclusion of more CBC findings in the APACHE model might increase its predictive accuracy.

Our multivariate analysis was based on a very large number of patient samples using data collected through routine clinical care. However, our study has a number of limitations. The analysis was done at only a single institution, and the exact logistic regression model may not apply to other institutions that have different case mixes and laboratory procedures. Our institution's reported 30‐day mortality rate of 3.4% was lower than the 4.6%11.9% reported in studies of patients admitted to general ward services,2931 but this may be accounted for by the lower‐than‐average Charlson comorbidity scores in our study population. Our risk adjustment by Charlson comorbidity scores may not be as precise as a risk adjustment tailored for our particular institution.32 Our 30‐day mortality rate was calculated using state death tapes, which means we would have missed patients who died outside the state, although we believe this rarely happens. We developed predictive equations on the basis of 30‐day mortality, so we cannot comment on whether the CBC elements predict mortality beyond 30 days. We analyzed most variables as either high or low or as present or absent. Increasing degrees of abnormality may further increase the predictive power of some variables. Finally, the CBC is only one of many tests and clinical findings; it may be that some of these other variables would displace some CBC variables and/or improve the overall predictive power at the time the admission laboratory tests were performed. In this initial study, we have described the prognostic implication of the CBC across a wide range of diagnoses. Future work will focus on the predictive power of commonly gathered variables in more specific conditions (eg, low white blood cell count in sepsis).

Physicians generally have an intuitive ability to identify patients who are seriously ill and at high risk of dying33 and adjust their diagnostic and therapeutic efforts accordingly. Our analysis highlights the value that certain observations in the CBC, notably burr cells, NRBCs, and absolute lymphocytosis, add to physicians' assessments of mortality risk. Even after adjustment for age, sex, comorbidities, common admission diagnoses, and other variables in the CBC, the presence of these findings predicted a 3‐fold increase in 30‐day mortality. Identifying the red flags within this ubiquitously performed test can make the difference in premature discharge or inappropriate triage of patients. Busy physicians can choose from a wide selection of ever‐improving diagnostic tests, yet the workhorse CBC can serve as a simple and early identifier of patients with a poor prognosis.

References
  1. Shapiro MF,Greenfield SG.The complete blood count and leukocyte differential count.Ann Intern Med.1987;106:6574.
  2. Chang R,Wong GY.Prognostic significance of marked leukocytosis in hospitalized patients.J Gen Intern Med.1991;6:199203.
  3. Knaus WA,Wagner DP,Draper EA, et al.The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest.1991;100:16191636.
  4. Knaus WA,Draper EA,Wagner DP,Zimmerman JE.APACHE II: a severity of disease classification system.Crit Care Med.1985;13:818829.
  5. Fine MJ,Auble TE,Yealy DM, et al.A prediction rule to identify low‐risk patients with community‐acquired pneumonia.N Engl J Med.1997;336:243250.
  6. Grimm R,Neaton J,Ludwig W.Prognostic importance of the white blood cell count for coronary, cancer, and all‐cause mortality.JAMA.1985;254:19321937.
  7. Labry LD,Campion E,Glynn R,Vokonas P.White blood cell count as a predictor of mortality: results over 18 years from the Normative Aging Study.J Clin Epidemiol.1990;43:153157.
  8. Frumin AM,Mendell TH,Mintz SS,Novack P,Faulk AT.Nucleated red blood cells in congestive heart failure.Circulation.1959;20:367370.
  9. Mozaffarian D,Nye R,Levy WC.Anemia predicts mortality in severe heart failure: the prospective randomized amlodipine survival evaluation (PRAISE).J Am Coll Cardiol.2003;41:19331939.
  10. Ardron MJ,Westengard JC,Dutcher TF.Band neutrophil counts are unnecessary for the diagnosis of infection in patients with normal total leukocyte counts.Am J Clin Pathol.1994;102:646649.
  11. Brigden M,Page N.The lack of clinical utility of white blood cell differential counts and blood morphology in elderly individuals with normal hematology profiles.Arch Pathol Lab Med.1990;114:394398.
  12. Wenz B,Gennis P,Canova C,Burns ER.The clinical utility of the leucocyte differential in emergency medicine.Am J Clin Pathol.1986;86:298303.
  13. Wile MJ,Homer LD,Gaehler S,Phillips S,Millan J.Manual differential cell counts help predict bacterial infection.Am J Clin Pathol.2001;115:644649.
  14. Schwartz SO,Stansbury F.Significance of nucleated red blood cells in peripheral blood; analysis of 1,496 cases.JAMA.1954;154:13391340.
  15. Stachon A,Sondermann N,Imohl M,Krieg M.Nucleated red blood cells indicate high risk of in‐hospital mortality.J Lab Clin Med.2002;140:407412.
  16. Teggatz JR,Parkin J,Peterson L.Transient atypical lymphocytosis in patients with emergency medical conditions.Arch Pathol Lab Med.1987;111:712714.
  17. Pinkerton PH,McLellan BA,Quantz MC,Robinson JB.Acute lymphocytosis after trauma—early recognition of the high‐risk patient?J Trauma.1989;29:749751.
  18. McDonald CJ,Overhage JM,Tierney WM, et al.The Regenstrief Medical Record System: a quarter century experience.Int J Med Inf.1999;54:225253.
  19. Charlson M,Szatrowski TP,Peterson J,Gold J.Validation of a combined comorbidity index.J Clin Epidemiol.1994;47:12451251.
  20. Grannis S,Overhage JM,McDonald CJ.Real world performance of approximate string comparators for use in patient matching.Medinfo.2004;11(Pt1):4347.
  21. Picard F,Gicquel C,Marnet L,Guesnu M,Levy JP.Preliminary evaluation of the new hematology analyzer COULTER GEN‐S in a university hospital.Clin Chem Lab Med.1999;37:681686.
  22. Rosenthal GE,Kaboli PJ,Barnett MJ.Differences in length of stay in veterans health administration and other united states hospitals: is the gap closing?Med Care.2003;41:882894.
  23. Kosiborod M,Smith G,Radford M,Foody J,Krumholz H.The Prognostic importance of anemia in patients with heart failure.Am J Med.2003;114:112119.
  24. Schwartz SO,Motto SA.The diagnostic significance of “burr” red blood cells.Am J Med Sci.1949;218:563.
  25. Aherne WA.The “burr” red cell and azotemia.J Clin Pathol.1957;10:252257.
  26. Bell RE.The origin of ‘burr’ erythrocytes.Br J Haematol.1963;9:552555.
  27. de Keizer NF,Bonsel GJ,Goldfad C,Rowan KM.The added value that increasing levels of diagnostic information provide in prognostic models to estimate hospital mortality for adult intensive care patients.Intern Care Med.2000;26:577584.
  28. Harrell F,Califf R,Pryor D,Lee K,Rosati R.Evaluating the yield of medical tests.JAMA.1982;247:25432546.
  29. Meltzer D,Manning WG,Morrison J, et al.Effects of physician experience on costs and outcomes on an academic general medical service: results of a trial of hospitalists.Ann Intern Med.2002;137:866874.
  30. Kearns PJ,Wang CC,Morris WJ, et al.Hospital care by hospital‐based and clinic‐based faculty. a prospective, controlled trial.Arch Intern Med.2001;161:235241.
  31. Auerbach AD,Wachter RM,Katz P,Showstack J,Baron RB,Goldman L.Implementation of a voluntary hospitalist service at a community teaching hospital: improved clinical efficiency and patient outcomes.Ann Intern Med.2002;137:859865.
  32. Rosenthal GE,Harper DL,Quinn LM,Cooper GS.Severity‐adjusted mortality and length of stay in teaching and nonteaching hospitals: results of a regional study.JAMA.1997;278:485490.
  33. McClish DK,Powell SH.How well can physicians estimate mortality in a medical intensive care unit?Med Decis Mak.1989;9:125132.
References
  1. Shapiro MF,Greenfield SG.The complete blood count and leukocyte differential count.Ann Intern Med.1987;106:6574.
  2. Chang R,Wong GY.Prognostic significance of marked leukocytosis in hospitalized patients.J Gen Intern Med.1991;6:199203.
  3. Knaus WA,Wagner DP,Draper EA, et al.The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest.1991;100:16191636.
  4. Knaus WA,Draper EA,Wagner DP,Zimmerman JE.APACHE II: a severity of disease classification system.Crit Care Med.1985;13:818829.
  5. Fine MJ,Auble TE,Yealy DM, et al.A prediction rule to identify low‐risk patients with community‐acquired pneumonia.N Engl J Med.1997;336:243250.
  6. Grimm R,Neaton J,Ludwig W.Prognostic importance of the white blood cell count for coronary, cancer, and all‐cause mortality.JAMA.1985;254:19321937.
  7. Labry LD,Campion E,Glynn R,Vokonas P.White blood cell count as a predictor of mortality: results over 18 years from the Normative Aging Study.J Clin Epidemiol.1990;43:153157.
  8. Frumin AM,Mendell TH,Mintz SS,Novack P,Faulk AT.Nucleated red blood cells in congestive heart failure.Circulation.1959;20:367370.
  9. Mozaffarian D,Nye R,Levy WC.Anemia predicts mortality in severe heart failure: the prospective randomized amlodipine survival evaluation (PRAISE).J Am Coll Cardiol.2003;41:19331939.
  10. Ardron MJ,Westengard JC,Dutcher TF.Band neutrophil counts are unnecessary for the diagnosis of infection in patients with normal total leukocyte counts.Am J Clin Pathol.1994;102:646649.
  11. Brigden M,Page N.The lack of clinical utility of white blood cell differential counts and blood morphology in elderly individuals with normal hematology profiles.Arch Pathol Lab Med.1990;114:394398.
  12. Wenz B,Gennis P,Canova C,Burns ER.The clinical utility of the leucocyte differential in emergency medicine.Am J Clin Pathol.1986;86:298303.
  13. Wile MJ,Homer LD,Gaehler S,Phillips S,Millan J.Manual differential cell counts help predict bacterial infection.Am J Clin Pathol.2001;115:644649.
  14. Schwartz SO,Stansbury F.Significance of nucleated red blood cells in peripheral blood; analysis of 1,496 cases.JAMA.1954;154:13391340.
  15. Stachon A,Sondermann N,Imohl M,Krieg M.Nucleated red blood cells indicate high risk of in‐hospital mortality.J Lab Clin Med.2002;140:407412.
  16. Teggatz JR,Parkin J,Peterson L.Transient atypical lymphocytosis in patients with emergency medical conditions.Arch Pathol Lab Med.1987;111:712714.
  17. Pinkerton PH,McLellan BA,Quantz MC,Robinson JB.Acute lymphocytosis after trauma—early recognition of the high‐risk patient?J Trauma.1989;29:749751.
  18. McDonald CJ,Overhage JM,Tierney WM, et al.The Regenstrief Medical Record System: a quarter century experience.Int J Med Inf.1999;54:225253.
  19. Charlson M,Szatrowski TP,Peterson J,Gold J.Validation of a combined comorbidity index.J Clin Epidemiol.1994;47:12451251.
  20. Grannis S,Overhage JM,McDonald CJ.Real world performance of approximate string comparators for use in patient matching.Medinfo.2004;11(Pt1):4347.
  21. Picard F,Gicquel C,Marnet L,Guesnu M,Levy JP.Preliminary evaluation of the new hematology analyzer COULTER GEN‐S in a university hospital.Clin Chem Lab Med.1999;37:681686.
  22. Rosenthal GE,Kaboli PJ,Barnett MJ.Differences in length of stay in veterans health administration and other united states hospitals: is the gap closing?Med Care.2003;41:882894.
  23. Kosiborod M,Smith G,Radford M,Foody J,Krumholz H.The Prognostic importance of anemia in patients with heart failure.Am J Med.2003;114:112119.
  24. Schwartz SO,Motto SA.The diagnostic significance of “burr” red blood cells.Am J Med Sci.1949;218:563.
  25. Aherne WA.The “burr” red cell and azotemia.J Clin Pathol.1957;10:252257.
  26. Bell RE.The origin of ‘burr’ erythrocytes.Br J Haematol.1963;9:552555.
  27. de Keizer NF,Bonsel GJ,Goldfad C,Rowan KM.The added value that increasing levels of diagnostic information provide in prognostic models to estimate hospital mortality for adult intensive care patients.Intern Care Med.2000;26:577584.
  28. Harrell F,Califf R,Pryor D,Lee K,Rosati R.Evaluating the yield of medical tests.JAMA.1982;247:25432546.
  29. Meltzer D,Manning WG,Morrison J, et al.Effects of physician experience on costs and outcomes on an academic general medical service: results of a trial of hospitalists.Ann Intern Med.2002;137:866874.
  30. Kearns PJ,Wang CC,Morris WJ, et al.Hospital care by hospital‐based and clinic‐based faculty. a prospective, controlled trial.Arch Intern Med.2001;161:235241.
  31. Auerbach AD,Wachter RM,Katz P,Showstack J,Baron RB,Goldman L.Implementation of a voluntary hospitalist service at a community teaching hospital: improved clinical efficiency and patient outcomes.Ann Intern Med.2002;137:859865.
  32. Rosenthal GE,Harper DL,Quinn LM,Cooper GS.Severity‐adjusted mortality and length of stay in teaching and nonteaching hospitals: results of a regional study.JAMA.1997;278:485490.
  33. McClish DK,Powell SH.How well can physicians estimate mortality in a medical intensive care unit?Med Decis Mak.1989;9:125132.
Issue
Journal of Hospital Medicine - 2(1)
Issue
Journal of Hospital Medicine - 2(1)
Page Number
5-12
Page Number
5-12
Article Type
Display Headline
Which observations from the complete blood cell count predict mortality for hospitalized patients?
Display Headline
Which observations from the complete blood cell count predict mortality for hospitalized patients?
Legacy Keywords
diagnostic decision making, laboratory testing, electronic medical record
Legacy Keywords
diagnostic decision making, laboratory testing, electronic medical record
Sections
Article Source

Copyright © 2007 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
Northwestern University, General Internal Medicine, 676 N. St. Clair, Suite 200, Chicago, IL 60611; Fax: (312) 695‐4307
Content Gating
No Gating (article Unlocked/Free)
Alternative CME
Article PDF Media

The Effect of Fexofenadine Hydrochloride on Productivity and Quality of Life in Patients With Chronic Idiopathic Urticaria

Article Type
Changed
Thu, 01/10/2019 - 12:10
Display Headline
The Effect of Fexofenadine Hydrochloride on Productivity and Quality of Life in Patients With Chronic Idiopathic Urticaria

Article PDF
Author and Disclosure Information

Spector SL, Shikiar R, Harding G, Meeves S, Leahy MJ

Issue
Cutis - 79(2)
Publications
Topics
Page Number
157-162
Sections
Author and Disclosure Information

Spector SL, Shikiar R, Harding G, Meeves S, Leahy MJ

Author and Disclosure Information

Spector SL, Shikiar R, Harding G, Meeves S, Leahy MJ

Article PDF
Article PDF

Issue
Cutis - 79(2)
Issue
Cutis - 79(2)
Page Number
157-162
Page Number
157-162
Publications
Publications
Topics
Article Type
Display Headline
The Effect of Fexofenadine Hydrochloride on Productivity and Quality of Life in Patients With Chronic Idiopathic Urticaria
Display Headline
The Effect of Fexofenadine Hydrochloride on Productivity and Quality of Life in Patients With Chronic Idiopathic Urticaria
Sections
Article Source

PURLs Copyright

Inside the Article

Article PDF Media

Lentigo Maligna (Melanoma In Situ) Treated With Imiquimod Cream 5%: 12 Case Reports

Article Type
Changed
Thu, 01/10/2019 - 12:10
Display Headline
Lentigo Maligna (Melanoma In Situ) Treated With Imiquimod Cream 5%: 12 Case Reports

Article PDF
Author and Disclosure Information

Spenny ML, Walford J, Werchniak AE, Beltrani V, Brennick JB, Storm CA, Perry AE, Chapman MS

Issue
Cutis - 79(2)
Publications
Topics
Page Number
149-152
Sections
Author and Disclosure Information

Spenny ML, Walford J, Werchniak AE, Beltrani V, Brennick JB, Storm CA, Perry AE, Chapman MS

Author and Disclosure Information

Spenny ML, Walford J, Werchniak AE, Beltrani V, Brennick JB, Storm CA, Perry AE, Chapman MS

Article PDF
Article PDF

Issue
Cutis - 79(2)
Issue
Cutis - 79(2)
Page Number
149-152
Page Number
149-152
Publications
Publications
Topics
Article Type
Display Headline
Lentigo Maligna (Melanoma In Situ) Treated With Imiquimod Cream 5%: 12 Case Reports
Display Headline
Lentigo Maligna (Melanoma In Situ) Treated With Imiquimod Cream 5%: 12 Case Reports
Sections
Article Source

PURLs Copyright

Inside the Article

Article PDF Media

Classic and Atypical Spitz Nevi: Review of the Literature

Article Type
Changed
Thu, 01/10/2019 - 12:10
Display Headline
Classic and Atypical Spitz Nevi: Review of the Literature

Spitz nevi were first described in 1948.1 Spitz1 originally called these lesions benign juvenile melanoma. She was able to identify and describe a separate class of benign melanocytic neoplasms in children that were previously diagnosed and treated as melanoma.2 Prior to this discovery, the standard of care was to remove all suspicious pigmented lesions in children prior to adulthood to prevent possible malignant transformation.2,3 Today, Spitz nevus is the more commonly used term for benign juvenile melanoma because it is encountered occasionally in adults and the term melanoma carries a negative connotation.4 Other synonyms include juvenile melanoma, Spitz tumor, nevus of large spindle and/or epithelioid cells, and spindle cell and epithelioid nevus.3,5 

Classic Spitz Nevus

Spitz nevi are uncommon. The approximate incidence is 7 per 100,000 people. Spitz nevi are more frequently found in children and adolescents but can occur in adults.6,7 Spitz nevi occur predominantly in the white population and slightly more often in females.4,8

A Spitz nevus can arise de novo or in association with an existing melanocytic nevus. The lesions can be asymptomatic or have a history of rapid but limited growth. Clinical features of Spitz nevi are well-circumscribed, symmetrical, small- to medium-sized firm papules with smooth discrete borders and a uniform color (typically pink or flesh colored).9 Spitz nevi can occur in various shapes. In a study of 211 cases of Spitz nevi, 19% were described as flat or uneven, 24% as polypoid, and 57% as plateau or elevated.7 Spitz nevi usually are found on the face, neck, or lower extremities but can occur anywhere on the body.7,9 Size is typically less than 6 mm (Figures 1 and 2).

PLEASE REFER TO THE PDF TO VIEW THE FIGURES

The classic Spitz nevus histologically consists of large spindle and/or epithelioid melanocytes arrayed as epidermal nests grouped in a vertical orientation (called "bunches of bananas" or "raining down pattern"), with clefting artifact at the perimeter (Figure 3).4,9,10 The nests are fairly uniform, nonconfluent, and evenly spaced. There is little or no pagetoid spread pattern. Epidermal changes include acanthosis, hypergranulosis, and hyperkeratosis. The intradermal pattern displays maturation, with single-file or single-unit arrays descending to the base. Eosinophilic Kamino bodies frequently are found along the dermoepidermal interface. Kamino bodies are globular clusters that represent apoptotic degenerative melanocytes (Figure 4). They stain positive with both periodic acid-Schiff and trichrome stains. At the dermal base, there is no mitosis, no pushing deep margins, and lack of significant pleomorphism. Little or no melanin is present.4,9,10 The classic Spitz nevus behaves in a benign manner.1 The differential diagnosis of the Spitz nevus includes pyogenic granuloma, mastocytoma, juvenile xanthogranuloma, and malignant melanoma.

PLEASE REFER TO THE PDF TO VIEW THE FIGURES

Atypical Spitz Nevus

The atypical Spitz nevus is difficult to formally define. Instead, it is loosely defined. An atypical Spitz nevus shares histologic features with the classic Spitz nevus, but it may have one or more atypical features, which can be characteristic of malignancy.10-12 Gross atypical features may include irregular shape, nonuniform color, large size, or ulcerations. Histologically, there can be one or more of the following features: pleomorphism; increased cellularity; loss of cellular cohesion; epidermal pagetoid spread; minimal epidermal changes; absence of Kamino bodies; lack of maturation in the intradermal pattern; high-grade nuclear atypia; high basal mitotic rate; pushing deep margins into the dermal base or subcutis; and nests variable in size, shape, and orientation.9,10,13

The behavior of any atypical Spitz nevus is unpredictable. There are case reports of metastasizing and malignant lesions with Spitz-like characteristics causing fatal outcomes.11,13 However, there also are studies that show Spitz nevi acting in a benign manner, even with a history of metastases.11,13-15 Some researchers try to explain this phenomenon by theorizing that Spitz nevi and melanoma exist along a continuum with the classic benign Spitz nevus at one end of the spectrum and the aggressive malignant melanoma at the opposite end, with a diverse range of atypical Spitz-like lesions with features of both in between.4,10-12,14 Other researchers refute this claim and view the unequivocal Spitz nevus as benign and unrelated to melanoma. They point out that many of these case reports of melanomas with Spitz-like features do not fit the diagnosis of the Spitz nevus.16

In general, the more features an atypical Spitz nevus shares with melanoma, the greater the risk for malignant behavior. In 1999, Spatz et al12 proposed formal and specific criteria for determining the risk for malignant behavior in atypical Spitz nevi in children. In the retrospective study, atypical features were used to define atypical Spitz nevi and grade their risk for metastasis. The 5 major factors were age, size, presence of ulceration, involvement of subcutaneous fat, and mitotic activity. Positive risk factors that increased the grade included age greater than 10 years, diameter greater than 10.0 mm, lesions with fat involvement, presence of ulceration, and dermal component mitotic activity greater than 5 mitoses/mm2. The higher the grade, the higher the risk for malignancy and metastasis.12 Since its publication, this grading system for categorizing atypical Spitz nevi has been put to use in a few case reports and studies.17,18 Additional prospective studies using these criteria will be helpful in determining the true clinical nature of atypical Spitz nevi in children, the usefulness of this grading system, and the possible application of this grading system in adults. 

 

 

Problems Differentiating Classic and Atypical Spitz Nevi From Melanoma

Melanoma is a major part of the differential diagnosis of Spitz nevi. The classic Spitz nevus typically has a benign nature, while the atypical Spitz nevus displays unpredictable behavior that appears to be dependent on the degree of atypia.1,3,16 In contrast, melanoma is potentially fatal. Fortunately, Spitz nevi typically occur in children and the risk for having childhood melanoma is rare.6,8,19 Though risk is minimal, rare cases of melanoma have been reported in children.8,11,14,15,19-21 Therefore, making a correct diagnosis and ruling out melanoma is important.

Unfortunately, even with clinical and histologic guidelines, sometimes it is difficult to distinguish classic and atypical Spitz nevi from melanoma. The major problem is histologic overlap with Spitz nevi and melanoma. Many researchers have emphasized that there is no single discriminating factor for Spitz nevi and melanoma because virtually every trait of Spitz nevi has been described in melanoma.2,10,13,20,22,23 Results of multiple studies show variability among researchers on the analysis of melanocytic nevi and melanoma lesions, and the final diagnosis was subjective.5,22 In one retrospective study where clinical outcome was already known, 30 melanocytic lesions were evaluated independently by a panel of 10 dermatopathologists and categorized as either a typical Spitz nevus, atypical Spitz nevus, melanoma, tumor with unknown biologic potential, or other melanocytic lesion.5 The dermatopathologists were blinded to the clinical data. Evaluation of 17 Spitzoid lesions yielded no clear diagnostic consensus and a few lethal lesions were identified by most dermatopathologists as either typical or atypical Spitz nevi. The authors maintain that these results show that current objective criteria are deficient and inadequate to permit the discrimination of Spitz nevi with atypical features from melanoma.5

Given these histologic analysis limitations, many investigators are researching other tools and techniques that may help enhance diagnostic accuracy. Promising genetic analysis techniques include comparative genomic hybridization and fluorescent in situ hybridization.24 In one study,24 researchers compared Spitz nevi with primary cutaneous melanomas using comparative genomic hybridization and fluorescent in situ hybridization and discovered differences. In the study, Spitz nevi were found to have no chromosomal aberrations or gains in chromosome 11p or 7q21qter. In comparison, primary cutaneous melanomas had frequent chromosome deletions of chromosomes 9p, 10q, 6q, and 8p, and gains of chromosomes 7, 8, 6p, and 1q.24,25 Immunohistochemistry is another potential tool for improving diagnostic accuracy. Examples of promising immunohistochemical markers include antibody MIB-1,26-28 BCL-2,29 and anti-S100A6.30 Studies have shown that most melanomas are immunoreactive to MIB-1 and BCL-2, whereas Spitz nevi are not.26-29 Recently, anti-S100A6 protein also was shown to be a potential immunohistochemical marker to differentiate a Spitz nevus from melanoma.30 Anti-S100A6 is different from anti-S100 because it is more specific to a subclass of normal cell types and certain cancer cell lines. Investigators found strong, uniform, and diffuse S100A6 protein expression in the junctional and dermal components of all 42 Spitz nevi they studied versus weak and patchy S100A6 protein expression found mainly in the dermal component of 35 of 105 melanoma specimens they studied.30 Although these techniques show exceptional potential, further research will be required to prove their reliability. 

Management of Classic and Atypical Spitz Nevi

There is controversy regarding the treatment of a classic Spitz nevus. Some investigators recommend conservative treatment because a Spitz nevus is benign. They find that the Spitz nevus may be removed or left alone.3 Others agree but would add that complete excision with clinical follow-up is appropriate if there are atypical features found on the Spitz nevus.16,23,31 Other investigators are more aggressive and recommend complete excision with clear margins of all Spitz nevi, unequivocal or not, because Spitz nevi have histologic overlap with melanoma, and recurrent lesions may present with pseudomelanomatous changes, which makes differentiation more difficult later.4,32 They conclude that the benefits of complete excision outweigh the risks of partial treatment.4 Regardless of how a Spitz nevus case is managed, regular follow-up with a dermatologist is recommended to look for any changes or recurrences suggestive of malignancy.

Currently, there are no available evidence-based recommendations with predictive value for the specific management of atypical Spitz nevi because their clinical course is mostly unknown and unpredictable. Most articles that do address the management of atypical Spitz nevi state that they should be completely excised and followed periodically.11,33 Murphy et al34 suggest that an atypical Spitz nevus should be completely excised to avoid the rare possibility of a melanoma masquerading as an atypical Spitz nevus. Furthermore, if the physician is suspicious of malignancy, it is recommended that the lesion be managed like a melanoma and be removed in accordance with current melanoma margin guidelines or with comprehensive margin control via Mohs micrographic surgery.34,35 Gurbuz et al17 stated that surgical margin excision, sentinel lymph node dissection, and clinical follow-up is recommended for atypical Spitz tumors. However, currently there are no prospective studies that have tested these various recommendations on atypical Spitz nevi management.

 

 

Within the last few years, sentinel lymph node biopsy (SLNB) has been proposed as a useful tool in the management of melanocytic neoplasms of uncertain behavior, such as the atypical Spitz nevus.36 Researchers recommend SLNB in atypical Spitz nevi greater than 1.0-mm thick.18,36,37 Supporters maintain that it increases the sensitivity of the diagnosis of melanoma (vs atypical Spitz nevus) and identifies patients who may potentially benefit from early lymph node dissection and/or adjuvant therapy. They state that a positive SLNB supports the diagnosis of malignancy and recommend that the lesion be treated aggressively. If the SLNB is negative, melanoma cannot be completely ruled out, but there is more reassurance that the lesion may be confined to the skin and can be completely removed by excision.18,36,37 Other advantages of SLNB include minimal invasiveness and morbidity. Some researchers believe melanocytic neoplasms in which melanoma cannot be ruled out should undergo complete surgical excision with wide margins in accordance with current melanoma guidelines,34,35 which can be as much as 3 cm.36,38 A negative SLNB offers the advantage of planning a complete excision of an atypical Spitz nevus that preserves surrounding margins and is cosmetically more acceptable,36 and avoiding the morbidity (ie, lymphedema, paresthesia) associated with regional or elective lymph node dissection.18

However, some researchers argue that a positive SLNB in an atypical Spitz nevus is not metastatic melanoma and point out articles that have shown classic and atypical Spitz nevi spreading to lymphatic vessels and lymph nodes but behaving in a benign manner.11,13,15,21,37 Therefore, more studies are needed to assess the prognostic significance of positive SLNB in atypical Spitz nevi.18

 

References

 

 

  1. Spitz S. Melanomas of childhood. Am J Pathol. 1948;24:591-609.
  2. Spatz A, Barnhill RL. The Spitz tumor 50 years later: revisiting a landmark contribution and unresolved controversy. J Am Acad Dermatol. 1999;40:223-228.
  3. Paniago-Pereira C, Maize JC, Ackerman AB. Nevus of large spindle and/or epithelioid cells (Spitz's nevus). Arch Dermatol. 1978;114:1811-1823.
  4. Casso EM, Grin-Jorgensen CM, Grant-Kels JM. Spitz nevi. J Am Acad Dermatol. 1992;27:901-913.
  5. Barnhill RL, Argenyi ZB, From L, et al. Atypical Spitz nevi/tumors: lack of consensus for diagnosis, discrimination from melanoma, and prediction of outcome. Hum Pathol. 1999;30:513-520.
  6. Herreid PA, Shapiro PE. Age distribution of Spitz nevus vs malignant melanoma. Arch Dermatol. 1996;132:352-353.
  7. Weedon D, Little JH. Spindle and epithelioid cell nevi in children and adults. a review of 211 cases of the Spitz nevus. Cancer. 1977;40:217-225.
  8. Bader JL, Li FP, Olmstead PM, et al. Childhood malignant melanoma. incidence and etiology. Am J Pediatr Hematol Oncol. 1985;7:341-345.
  9. Elder DE, Murphy GF. Melanocytic tumors of the skin. In: Elder DE, Murphy GF, eds. Atlas of Tumor Pathology. Washington, DC: Armed Forces Institute of Pathology; 1990:40-57.
  10. Piepkorn M. On the nature of histologic observations: the case of the Spitz nevus. J Am Acad Dermatol. 1995;32:248-254.
  11. Barnhill RL, Flotte TJ, Fleischli M, et al. Cutaneous melanoma and atypical Spitz tumors in childhood. Cancer. 1995;76:1833-1845.
  12. Spatz A, Calonje E, Handfield-Jones S, et al. Spitz tumors in children: a grading system for risk stratification. Arch Dermatol. 1999;135:282-285.
  13. Smith KJ, Barrett TL, Skelton HG 3rd, et al. Spindle cell and epithelioid cell nevi with atypia and metastasis (malignant Spitz nevus). Am J Surg Pathol. 1989;13:931-939.
  14. Barnhill RL. Childhood melanoma. Semin Diagn Pathol. 1998;15:189-194.
  15. Melnik MK, Urdaneta LF, Al-Jurf AS, et al. Malignant melanoma in childhood and adolescence. Am Surg. 1986;52:142-147.
  16. Shapiro PE. Spitz nevi. J Am Acad Dermatol. 1993;29:667-668.
  17. Gurbuz Y, Apaydin R, Muezzinoglu B, et al. A current dilemma in histopathology: atypical spitz tumor or Spitzoid melanoma? Pediatr Dermatol. 2002;19:99-102.
  18. Lohmann CM, Coit DG, Brady MS, et al. Sentinel lymph node biopsy in patients with diagnostically controversial spitzoid melanocytic tumors. Am J Surg Pathol. 2002;26:47-55.
  19. Handfield-Jones SE, Smith NP. Malignant melanoma in childhood. Br J Dermatol. 1996;134:607-616.
  20. Crotty KA, McCarthy SW, Palmer AA, et al. Malignant melanoma in childhood: a clinicopathologic study of 13 cases and comparison with Spitz nevi. World J Surg. 1992;16:179-185.
  21. Lerman RI, Murray D, O'Hara JM, et al. Malignant melanoma of childhood. a clinicopathologic study and a report of 12 cases. Cancer. 1970;25:436-449.
  22. Farmer ER, Gonin R, Hanna MP. Discordance in the histopathologic diagnosis of melanoma and melano-cytic nevi between expert pathologists. Hum Pathol.1996;27:528-531.
  23. Shimek CM, Golitz LE. The golden anniversary of the Spitz nevus. Arch Dermatol. 1999;135:333-335.
  24. Bastian BC, Wesselmann U, Pinkel D, et al. Molecular cytogenetic analysis of Spitz nevi shows clear differences to melanoma. J Invest Dermatol.1999; 113:1065-1069.
  25. Bastian BC, LeBoit PE, Hamm H, et al. Chromo-somal gains and losses in primary cutaneous melanomas detected by comparative genomic hybridization. Cancer Res.1998;58:2170-2175.
  26. Bergman R, Malkin L, Sabo E, et al. MIB-1 mono-clonal antibody to determine proliferative activity of Ki-67 antigen as an adjunct to the histopathologic dif-ferential diagnosis of Spitz nevi. J Am Acad Dermatol. 2001; 44:500-504.
  27. Li LX, Crotty KA, McCarthy SW, et al. A zonal com-parison of MIB1-Ki67 immunoreactivity in benign and malignant melanocytic lesions. Am J Dermatopathol. 2000;22:489-495.
  28. McNutt NS, Urmacher C, Hakimian J, et al. Nevoid malignant melanoma: morphologicpatterns and immu-nohistochemical reactivity. J Cutan Pathol.1995;22:502-517.
  29. Kanter-Lewensohn L, Hedblad MA, Wejde J, et al. Immu-nohistochemical markers for distinguishing Spitz nevi from malignant melanomas. Mod Pathol.1997;10:917-920.
  30. Ribé A, McNutt NS. S100A6 protein expression is different in spitz nevi and melanomas.  Mod Pathol.2003;16:505-511.
  31. Kaye VN, Dehner LP. Spindle and epithelioid cell nevus (Spitz nevus). natural history following biopsy. Arch Dermatol.1990;126:1581-1583.
  32. Omura EF, Kheir SM. Recurrent Spitz’s nevus. Am J. Dermatopathol.1984;6(suppl): 207212.
  33. Zaenglein AL, Heintz P, Kamino H, et al. Congenital Spitz nevus clinically mimicking melanoma. J Am Acad Dermatol.2002;47:441-444.
  34. Murphy ME, Boyer JD, Stashower ME, et al. The surgical management of Spitz nevi. Dermatol Surg. 2002;28:1065-1069.
  35. Zitelli JA, Brown C, Hanusa BH. Mohs micrographic surgery for the treatment of primary cutaneous melanoma. J Am Acad Dermatol. 1997;37:236-245.
  36. Kelley SW, Cockerell CJ. Sentinel lymph node biopsy as an adjunct to management of histologically difficult to diagnose melanocytic lesions: a proposal. J Am Acad Dermatol. 2000;42:527-530.
  37. Su LD, Fullen DR, Sondak VK, et al. Sentinel lymph node biopsy for patients with problematic spitzoid melanocytic lesions: a report on 18 patients. Cancer. 2003;97:499-507.
  38. Martinez JC, Otley CC. The management of melanoma and nonmelanoma skin cancer: a review for the primary care physician. Mayo Clin Proc. 2001;76:1253-1265.
Article PDF
Author and Disclosure Information

Dr. Sulit is a dermatology resident from the Department of Dermatology, Naval Medical Center, San Diego, California. Dr. Guardiano is Assistant Professor of Dermatology, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr. Krivda is Department Head, Dermatology Department, National Naval Medical Center, Bethesda, and Chief, Dermatology Service, Walter Reed Army Medical Center, Washington, DC.

Drs. Sulit, Guardiano, and Krivda report no conflict of interest. The authors report no discussion of off-label use.

Issue
Cutis - 79(2)
Publications
Topics
Page Number
141-146
Author and Disclosure Information

Dr. Sulit is a dermatology resident from the Department of Dermatology, Naval Medical Center, San Diego, California. Dr. Guardiano is Assistant Professor of Dermatology, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr. Krivda is Department Head, Dermatology Department, National Naval Medical Center, Bethesda, and Chief, Dermatology Service, Walter Reed Army Medical Center, Washington, DC.

Drs. Sulit, Guardiano, and Krivda report no conflict of interest. The authors report no discussion of off-label use.

Author and Disclosure Information

Dr. Sulit is a dermatology resident from the Department of Dermatology, Naval Medical Center, San Diego, California. Dr. Guardiano is Assistant Professor of Dermatology, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr. Krivda is Department Head, Dermatology Department, National Naval Medical Center, Bethesda, and Chief, Dermatology Service, Walter Reed Army Medical Center, Washington, DC.

Drs. Sulit, Guardiano, and Krivda report no conflict of interest. The authors report no discussion of off-label use.

Article PDF
Article PDF

Spitz nevi were first described in 1948.1 Spitz1 originally called these lesions benign juvenile melanoma. She was able to identify and describe a separate class of benign melanocytic neoplasms in children that were previously diagnosed and treated as melanoma.2 Prior to this discovery, the standard of care was to remove all suspicious pigmented lesions in children prior to adulthood to prevent possible malignant transformation.2,3 Today, Spitz nevus is the more commonly used term for benign juvenile melanoma because it is encountered occasionally in adults and the term melanoma carries a negative connotation.4 Other synonyms include juvenile melanoma, Spitz tumor, nevus of large spindle and/or epithelioid cells, and spindle cell and epithelioid nevus.3,5 

Classic Spitz Nevus

Spitz nevi are uncommon. The approximate incidence is 7 per 100,000 people. Spitz nevi are more frequently found in children and adolescents but can occur in adults.6,7 Spitz nevi occur predominantly in the white population and slightly more often in females.4,8

A Spitz nevus can arise de novo or in association with an existing melanocytic nevus. The lesions can be asymptomatic or have a history of rapid but limited growth. Clinical features of Spitz nevi are well-circumscribed, symmetrical, small- to medium-sized firm papules with smooth discrete borders and a uniform color (typically pink or flesh colored).9 Spitz nevi can occur in various shapes. In a study of 211 cases of Spitz nevi, 19% were described as flat or uneven, 24% as polypoid, and 57% as plateau or elevated.7 Spitz nevi usually are found on the face, neck, or lower extremities but can occur anywhere on the body.7,9 Size is typically less than 6 mm (Figures 1 and 2).

PLEASE REFER TO THE PDF TO VIEW THE FIGURES

The classic Spitz nevus histologically consists of large spindle and/or epithelioid melanocytes arrayed as epidermal nests grouped in a vertical orientation (called "bunches of bananas" or "raining down pattern"), with clefting artifact at the perimeter (Figure 3).4,9,10 The nests are fairly uniform, nonconfluent, and evenly spaced. There is little or no pagetoid spread pattern. Epidermal changes include acanthosis, hypergranulosis, and hyperkeratosis. The intradermal pattern displays maturation, with single-file or single-unit arrays descending to the base. Eosinophilic Kamino bodies frequently are found along the dermoepidermal interface. Kamino bodies are globular clusters that represent apoptotic degenerative melanocytes (Figure 4). They stain positive with both periodic acid-Schiff and trichrome stains. At the dermal base, there is no mitosis, no pushing deep margins, and lack of significant pleomorphism. Little or no melanin is present.4,9,10 The classic Spitz nevus behaves in a benign manner.1 The differential diagnosis of the Spitz nevus includes pyogenic granuloma, mastocytoma, juvenile xanthogranuloma, and malignant melanoma.

PLEASE REFER TO THE PDF TO VIEW THE FIGURES

Atypical Spitz Nevus

The atypical Spitz nevus is difficult to formally define. Instead, it is loosely defined. An atypical Spitz nevus shares histologic features with the classic Spitz nevus, but it may have one or more atypical features, which can be characteristic of malignancy.10-12 Gross atypical features may include irregular shape, nonuniform color, large size, or ulcerations. Histologically, there can be one or more of the following features: pleomorphism; increased cellularity; loss of cellular cohesion; epidermal pagetoid spread; minimal epidermal changes; absence of Kamino bodies; lack of maturation in the intradermal pattern; high-grade nuclear atypia; high basal mitotic rate; pushing deep margins into the dermal base or subcutis; and nests variable in size, shape, and orientation.9,10,13

The behavior of any atypical Spitz nevus is unpredictable. There are case reports of metastasizing and malignant lesions with Spitz-like characteristics causing fatal outcomes.11,13 However, there also are studies that show Spitz nevi acting in a benign manner, even with a history of metastases.11,13-15 Some researchers try to explain this phenomenon by theorizing that Spitz nevi and melanoma exist along a continuum with the classic benign Spitz nevus at one end of the spectrum and the aggressive malignant melanoma at the opposite end, with a diverse range of atypical Spitz-like lesions with features of both in between.4,10-12,14 Other researchers refute this claim and view the unequivocal Spitz nevus as benign and unrelated to melanoma. They point out that many of these case reports of melanomas with Spitz-like features do not fit the diagnosis of the Spitz nevus.16

In general, the more features an atypical Spitz nevus shares with melanoma, the greater the risk for malignant behavior. In 1999, Spatz et al12 proposed formal and specific criteria for determining the risk for malignant behavior in atypical Spitz nevi in children. In the retrospective study, atypical features were used to define atypical Spitz nevi and grade their risk for metastasis. The 5 major factors were age, size, presence of ulceration, involvement of subcutaneous fat, and mitotic activity. Positive risk factors that increased the grade included age greater than 10 years, diameter greater than 10.0 mm, lesions with fat involvement, presence of ulceration, and dermal component mitotic activity greater than 5 mitoses/mm2. The higher the grade, the higher the risk for malignancy and metastasis.12 Since its publication, this grading system for categorizing atypical Spitz nevi has been put to use in a few case reports and studies.17,18 Additional prospective studies using these criteria will be helpful in determining the true clinical nature of atypical Spitz nevi in children, the usefulness of this grading system, and the possible application of this grading system in adults. 

 

 

Problems Differentiating Classic and Atypical Spitz Nevi From Melanoma

Melanoma is a major part of the differential diagnosis of Spitz nevi. The classic Spitz nevus typically has a benign nature, while the atypical Spitz nevus displays unpredictable behavior that appears to be dependent on the degree of atypia.1,3,16 In contrast, melanoma is potentially fatal. Fortunately, Spitz nevi typically occur in children and the risk for having childhood melanoma is rare.6,8,19 Though risk is minimal, rare cases of melanoma have been reported in children.8,11,14,15,19-21 Therefore, making a correct diagnosis and ruling out melanoma is important.

Unfortunately, even with clinical and histologic guidelines, sometimes it is difficult to distinguish classic and atypical Spitz nevi from melanoma. The major problem is histologic overlap with Spitz nevi and melanoma. Many researchers have emphasized that there is no single discriminating factor for Spitz nevi and melanoma because virtually every trait of Spitz nevi has been described in melanoma.2,10,13,20,22,23 Results of multiple studies show variability among researchers on the analysis of melanocytic nevi and melanoma lesions, and the final diagnosis was subjective.5,22 In one retrospective study where clinical outcome was already known, 30 melanocytic lesions were evaluated independently by a panel of 10 dermatopathologists and categorized as either a typical Spitz nevus, atypical Spitz nevus, melanoma, tumor with unknown biologic potential, or other melanocytic lesion.5 The dermatopathologists were blinded to the clinical data. Evaluation of 17 Spitzoid lesions yielded no clear diagnostic consensus and a few lethal lesions were identified by most dermatopathologists as either typical or atypical Spitz nevi. The authors maintain that these results show that current objective criteria are deficient and inadequate to permit the discrimination of Spitz nevi with atypical features from melanoma.5

Given these histologic analysis limitations, many investigators are researching other tools and techniques that may help enhance diagnostic accuracy. Promising genetic analysis techniques include comparative genomic hybridization and fluorescent in situ hybridization.24 In one study,24 researchers compared Spitz nevi with primary cutaneous melanomas using comparative genomic hybridization and fluorescent in situ hybridization and discovered differences. In the study, Spitz nevi were found to have no chromosomal aberrations or gains in chromosome 11p or 7q21qter. In comparison, primary cutaneous melanomas had frequent chromosome deletions of chromosomes 9p, 10q, 6q, and 8p, and gains of chromosomes 7, 8, 6p, and 1q.24,25 Immunohistochemistry is another potential tool for improving diagnostic accuracy. Examples of promising immunohistochemical markers include antibody MIB-1,26-28 BCL-2,29 and anti-S100A6.30 Studies have shown that most melanomas are immunoreactive to MIB-1 and BCL-2, whereas Spitz nevi are not.26-29 Recently, anti-S100A6 protein also was shown to be a potential immunohistochemical marker to differentiate a Spitz nevus from melanoma.30 Anti-S100A6 is different from anti-S100 because it is more specific to a subclass of normal cell types and certain cancer cell lines. Investigators found strong, uniform, and diffuse S100A6 protein expression in the junctional and dermal components of all 42 Spitz nevi they studied versus weak and patchy S100A6 protein expression found mainly in the dermal component of 35 of 105 melanoma specimens they studied.30 Although these techniques show exceptional potential, further research will be required to prove their reliability. 

Management of Classic and Atypical Spitz Nevi

There is controversy regarding the treatment of a classic Spitz nevus. Some investigators recommend conservative treatment because a Spitz nevus is benign. They find that the Spitz nevus may be removed or left alone.3 Others agree but would add that complete excision with clinical follow-up is appropriate if there are atypical features found on the Spitz nevus.16,23,31 Other investigators are more aggressive and recommend complete excision with clear margins of all Spitz nevi, unequivocal or not, because Spitz nevi have histologic overlap with melanoma, and recurrent lesions may present with pseudomelanomatous changes, which makes differentiation more difficult later.4,32 They conclude that the benefits of complete excision outweigh the risks of partial treatment.4 Regardless of how a Spitz nevus case is managed, regular follow-up with a dermatologist is recommended to look for any changes or recurrences suggestive of malignancy.

Currently, there are no available evidence-based recommendations with predictive value for the specific management of atypical Spitz nevi because their clinical course is mostly unknown and unpredictable. Most articles that do address the management of atypical Spitz nevi state that they should be completely excised and followed periodically.11,33 Murphy et al34 suggest that an atypical Spitz nevus should be completely excised to avoid the rare possibility of a melanoma masquerading as an atypical Spitz nevus. Furthermore, if the physician is suspicious of malignancy, it is recommended that the lesion be managed like a melanoma and be removed in accordance with current melanoma margin guidelines or with comprehensive margin control via Mohs micrographic surgery.34,35 Gurbuz et al17 stated that surgical margin excision, sentinel lymph node dissection, and clinical follow-up is recommended for atypical Spitz tumors. However, currently there are no prospective studies that have tested these various recommendations on atypical Spitz nevi management.

 

 

Within the last few years, sentinel lymph node biopsy (SLNB) has been proposed as a useful tool in the management of melanocytic neoplasms of uncertain behavior, such as the atypical Spitz nevus.36 Researchers recommend SLNB in atypical Spitz nevi greater than 1.0-mm thick.18,36,37 Supporters maintain that it increases the sensitivity of the diagnosis of melanoma (vs atypical Spitz nevus) and identifies patients who may potentially benefit from early lymph node dissection and/or adjuvant therapy. They state that a positive SLNB supports the diagnosis of malignancy and recommend that the lesion be treated aggressively. If the SLNB is negative, melanoma cannot be completely ruled out, but there is more reassurance that the lesion may be confined to the skin and can be completely removed by excision.18,36,37 Other advantages of SLNB include minimal invasiveness and morbidity. Some researchers believe melanocytic neoplasms in which melanoma cannot be ruled out should undergo complete surgical excision with wide margins in accordance with current melanoma guidelines,34,35 which can be as much as 3 cm.36,38 A negative SLNB offers the advantage of planning a complete excision of an atypical Spitz nevus that preserves surrounding margins and is cosmetically more acceptable,36 and avoiding the morbidity (ie, lymphedema, paresthesia) associated with regional or elective lymph node dissection.18

However, some researchers argue that a positive SLNB in an atypical Spitz nevus is not metastatic melanoma and point out articles that have shown classic and atypical Spitz nevi spreading to lymphatic vessels and lymph nodes but behaving in a benign manner.11,13,15,21,37 Therefore, more studies are needed to assess the prognostic significance of positive SLNB in atypical Spitz nevi.18

 

Spitz nevi were first described in 1948.1 Spitz1 originally called these lesions benign juvenile melanoma. She was able to identify and describe a separate class of benign melanocytic neoplasms in children that were previously diagnosed and treated as melanoma.2 Prior to this discovery, the standard of care was to remove all suspicious pigmented lesions in children prior to adulthood to prevent possible malignant transformation.2,3 Today, Spitz nevus is the more commonly used term for benign juvenile melanoma because it is encountered occasionally in adults and the term melanoma carries a negative connotation.4 Other synonyms include juvenile melanoma, Spitz tumor, nevus of large spindle and/or epithelioid cells, and spindle cell and epithelioid nevus.3,5 

Classic Spitz Nevus

Spitz nevi are uncommon. The approximate incidence is 7 per 100,000 people. Spitz nevi are more frequently found in children and adolescents but can occur in adults.6,7 Spitz nevi occur predominantly in the white population and slightly more often in females.4,8

A Spitz nevus can arise de novo or in association with an existing melanocytic nevus. The lesions can be asymptomatic or have a history of rapid but limited growth. Clinical features of Spitz nevi are well-circumscribed, symmetrical, small- to medium-sized firm papules with smooth discrete borders and a uniform color (typically pink or flesh colored).9 Spitz nevi can occur in various shapes. In a study of 211 cases of Spitz nevi, 19% were described as flat or uneven, 24% as polypoid, and 57% as plateau or elevated.7 Spitz nevi usually are found on the face, neck, or lower extremities but can occur anywhere on the body.7,9 Size is typically less than 6 mm (Figures 1 and 2).

PLEASE REFER TO THE PDF TO VIEW THE FIGURES

The classic Spitz nevus histologically consists of large spindle and/or epithelioid melanocytes arrayed as epidermal nests grouped in a vertical orientation (called "bunches of bananas" or "raining down pattern"), with clefting artifact at the perimeter (Figure 3).4,9,10 The nests are fairly uniform, nonconfluent, and evenly spaced. There is little or no pagetoid spread pattern. Epidermal changes include acanthosis, hypergranulosis, and hyperkeratosis. The intradermal pattern displays maturation, with single-file or single-unit arrays descending to the base. Eosinophilic Kamino bodies frequently are found along the dermoepidermal interface. Kamino bodies are globular clusters that represent apoptotic degenerative melanocytes (Figure 4). They stain positive with both periodic acid-Schiff and trichrome stains. At the dermal base, there is no mitosis, no pushing deep margins, and lack of significant pleomorphism. Little or no melanin is present.4,9,10 The classic Spitz nevus behaves in a benign manner.1 The differential diagnosis of the Spitz nevus includes pyogenic granuloma, mastocytoma, juvenile xanthogranuloma, and malignant melanoma.

PLEASE REFER TO THE PDF TO VIEW THE FIGURES

Atypical Spitz Nevus

The atypical Spitz nevus is difficult to formally define. Instead, it is loosely defined. An atypical Spitz nevus shares histologic features with the classic Spitz nevus, but it may have one or more atypical features, which can be characteristic of malignancy.10-12 Gross atypical features may include irregular shape, nonuniform color, large size, or ulcerations. Histologically, there can be one or more of the following features: pleomorphism; increased cellularity; loss of cellular cohesion; epidermal pagetoid spread; minimal epidermal changes; absence of Kamino bodies; lack of maturation in the intradermal pattern; high-grade nuclear atypia; high basal mitotic rate; pushing deep margins into the dermal base or subcutis; and nests variable in size, shape, and orientation.9,10,13

The behavior of any atypical Spitz nevus is unpredictable. There are case reports of metastasizing and malignant lesions with Spitz-like characteristics causing fatal outcomes.11,13 However, there also are studies that show Spitz nevi acting in a benign manner, even with a history of metastases.11,13-15 Some researchers try to explain this phenomenon by theorizing that Spitz nevi and melanoma exist along a continuum with the classic benign Spitz nevus at one end of the spectrum and the aggressive malignant melanoma at the opposite end, with a diverse range of atypical Spitz-like lesions with features of both in between.4,10-12,14 Other researchers refute this claim and view the unequivocal Spitz nevus as benign and unrelated to melanoma. They point out that many of these case reports of melanomas with Spitz-like features do not fit the diagnosis of the Spitz nevus.16

In general, the more features an atypical Spitz nevus shares with melanoma, the greater the risk for malignant behavior. In 1999, Spatz et al12 proposed formal and specific criteria for determining the risk for malignant behavior in atypical Spitz nevi in children. In the retrospective study, atypical features were used to define atypical Spitz nevi and grade their risk for metastasis. The 5 major factors were age, size, presence of ulceration, involvement of subcutaneous fat, and mitotic activity. Positive risk factors that increased the grade included age greater than 10 years, diameter greater than 10.0 mm, lesions with fat involvement, presence of ulceration, and dermal component mitotic activity greater than 5 mitoses/mm2. The higher the grade, the higher the risk for malignancy and metastasis.12 Since its publication, this grading system for categorizing atypical Spitz nevi has been put to use in a few case reports and studies.17,18 Additional prospective studies using these criteria will be helpful in determining the true clinical nature of atypical Spitz nevi in children, the usefulness of this grading system, and the possible application of this grading system in adults. 

 

 

Problems Differentiating Classic and Atypical Spitz Nevi From Melanoma

Melanoma is a major part of the differential diagnosis of Spitz nevi. The classic Spitz nevus typically has a benign nature, while the atypical Spitz nevus displays unpredictable behavior that appears to be dependent on the degree of atypia.1,3,16 In contrast, melanoma is potentially fatal. Fortunately, Spitz nevi typically occur in children and the risk for having childhood melanoma is rare.6,8,19 Though risk is minimal, rare cases of melanoma have been reported in children.8,11,14,15,19-21 Therefore, making a correct diagnosis and ruling out melanoma is important.

Unfortunately, even with clinical and histologic guidelines, sometimes it is difficult to distinguish classic and atypical Spitz nevi from melanoma. The major problem is histologic overlap with Spitz nevi and melanoma. Many researchers have emphasized that there is no single discriminating factor for Spitz nevi and melanoma because virtually every trait of Spitz nevi has been described in melanoma.2,10,13,20,22,23 Results of multiple studies show variability among researchers on the analysis of melanocytic nevi and melanoma lesions, and the final diagnosis was subjective.5,22 In one retrospective study where clinical outcome was already known, 30 melanocytic lesions were evaluated independently by a panel of 10 dermatopathologists and categorized as either a typical Spitz nevus, atypical Spitz nevus, melanoma, tumor with unknown biologic potential, or other melanocytic lesion.5 The dermatopathologists were blinded to the clinical data. Evaluation of 17 Spitzoid lesions yielded no clear diagnostic consensus and a few lethal lesions were identified by most dermatopathologists as either typical or atypical Spitz nevi. The authors maintain that these results show that current objective criteria are deficient and inadequate to permit the discrimination of Spitz nevi with atypical features from melanoma.5

Given these histologic analysis limitations, many investigators are researching other tools and techniques that may help enhance diagnostic accuracy. Promising genetic analysis techniques include comparative genomic hybridization and fluorescent in situ hybridization.24 In one study,24 researchers compared Spitz nevi with primary cutaneous melanomas using comparative genomic hybridization and fluorescent in situ hybridization and discovered differences. In the study, Spitz nevi were found to have no chromosomal aberrations or gains in chromosome 11p or 7q21qter. In comparison, primary cutaneous melanomas had frequent chromosome deletions of chromosomes 9p, 10q, 6q, and 8p, and gains of chromosomes 7, 8, 6p, and 1q.24,25 Immunohistochemistry is another potential tool for improving diagnostic accuracy. Examples of promising immunohistochemical markers include antibody MIB-1,26-28 BCL-2,29 and anti-S100A6.30 Studies have shown that most melanomas are immunoreactive to MIB-1 and BCL-2, whereas Spitz nevi are not.26-29 Recently, anti-S100A6 protein also was shown to be a potential immunohistochemical marker to differentiate a Spitz nevus from melanoma.30 Anti-S100A6 is different from anti-S100 because it is more specific to a subclass of normal cell types and certain cancer cell lines. Investigators found strong, uniform, and diffuse S100A6 protein expression in the junctional and dermal components of all 42 Spitz nevi they studied versus weak and patchy S100A6 protein expression found mainly in the dermal component of 35 of 105 melanoma specimens they studied.30 Although these techniques show exceptional potential, further research will be required to prove their reliability. 

Management of Classic and Atypical Spitz Nevi

There is controversy regarding the treatment of a classic Spitz nevus. Some investigators recommend conservative treatment because a Spitz nevus is benign. They find that the Spitz nevus may be removed or left alone.3 Others agree but would add that complete excision with clinical follow-up is appropriate if there are atypical features found on the Spitz nevus.16,23,31 Other investigators are more aggressive and recommend complete excision with clear margins of all Spitz nevi, unequivocal or not, because Spitz nevi have histologic overlap with melanoma, and recurrent lesions may present with pseudomelanomatous changes, which makes differentiation more difficult later.4,32 They conclude that the benefits of complete excision outweigh the risks of partial treatment.4 Regardless of how a Spitz nevus case is managed, regular follow-up with a dermatologist is recommended to look for any changes or recurrences suggestive of malignancy.

Currently, there are no available evidence-based recommendations with predictive value for the specific management of atypical Spitz nevi because their clinical course is mostly unknown and unpredictable. Most articles that do address the management of atypical Spitz nevi state that they should be completely excised and followed periodically.11,33 Murphy et al34 suggest that an atypical Spitz nevus should be completely excised to avoid the rare possibility of a melanoma masquerading as an atypical Spitz nevus. Furthermore, if the physician is suspicious of malignancy, it is recommended that the lesion be managed like a melanoma and be removed in accordance with current melanoma margin guidelines or with comprehensive margin control via Mohs micrographic surgery.34,35 Gurbuz et al17 stated that surgical margin excision, sentinel lymph node dissection, and clinical follow-up is recommended for atypical Spitz tumors. However, currently there are no prospective studies that have tested these various recommendations on atypical Spitz nevi management.

 

 

Within the last few years, sentinel lymph node biopsy (SLNB) has been proposed as a useful tool in the management of melanocytic neoplasms of uncertain behavior, such as the atypical Spitz nevus.36 Researchers recommend SLNB in atypical Spitz nevi greater than 1.0-mm thick.18,36,37 Supporters maintain that it increases the sensitivity of the diagnosis of melanoma (vs atypical Spitz nevus) and identifies patients who may potentially benefit from early lymph node dissection and/or adjuvant therapy. They state that a positive SLNB supports the diagnosis of malignancy and recommend that the lesion be treated aggressively. If the SLNB is negative, melanoma cannot be completely ruled out, but there is more reassurance that the lesion may be confined to the skin and can be completely removed by excision.18,36,37 Other advantages of SLNB include minimal invasiveness and morbidity. Some researchers believe melanocytic neoplasms in which melanoma cannot be ruled out should undergo complete surgical excision with wide margins in accordance with current melanoma guidelines,34,35 which can be as much as 3 cm.36,38 A negative SLNB offers the advantage of planning a complete excision of an atypical Spitz nevus that preserves surrounding margins and is cosmetically more acceptable,36 and avoiding the morbidity (ie, lymphedema, paresthesia) associated with regional or elective lymph node dissection.18

However, some researchers argue that a positive SLNB in an atypical Spitz nevus is not metastatic melanoma and point out articles that have shown classic and atypical Spitz nevi spreading to lymphatic vessels and lymph nodes but behaving in a benign manner.11,13,15,21,37 Therefore, more studies are needed to assess the prognostic significance of positive SLNB in atypical Spitz nevi.18

 

References

 

 

  1. Spitz S. Melanomas of childhood. Am J Pathol. 1948;24:591-609.
  2. Spatz A, Barnhill RL. The Spitz tumor 50 years later: revisiting a landmark contribution and unresolved controversy. J Am Acad Dermatol. 1999;40:223-228.
  3. Paniago-Pereira C, Maize JC, Ackerman AB. Nevus of large spindle and/or epithelioid cells (Spitz's nevus). Arch Dermatol. 1978;114:1811-1823.
  4. Casso EM, Grin-Jorgensen CM, Grant-Kels JM. Spitz nevi. J Am Acad Dermatol. 1992;27:901-913.
  5. Barnhill RL, Argenyi ZB, From L, et al. Atypical Spitz nevi/tumors: lack of consensus for diagnosis, discrimination from melanoma, and prediction of outcome. Hum Pathol. 1999;30:513-520.
  6. Herreid PA, Shapiro PE. Age distribution of Spitz nevus vs malignant melanoma. Arch Dermatol. 1996;132:352-353.
  7. Weedon D, Little JH. Spindle and epithelioid cell nevi in children and adults. a review of 211 cases of the Spitz nevus. Cancer. 1977;40:217-225.
  8. Bader JL, Li FP, Olmstead PM, et al. Childhood malignant melanoma. incidence and etiology. Am J Pediatr Hematol Oncol. 1985;7:341-345.
  9. Elder DE, Murphy GF. Melanocytic tumors of the skin. In: Elder DE, Murphy GF, eds. Atlas of Tumor Pathology. Washington, DC: Armed Forces Institute of Pathology; 1990:40-57.
  10. Piepkorn M. On the nature of histologic observations: the case of the Spitz nevus. J Am Acad Dermatol. 1995;32:248-254.
  11. Barnhill RL, Flotte TJ, Fleischli M, et al. Cutaneous melanoma and atypical Spitz tumors in childhood. Cancer. 1995;76:1833-1845.
  12. Spatz A, Calonje E, Handfield-Jones S, et al. Spitz tumors in children: a grading system for risk stratification. Arch Dermatol. 1999;135:282-285.
  13. Smith KJ, Barrett TL, Skelton HG 3rd, et al. Spindle cell and epithelioid cell nevi with atypia and metastasis (malignant Spitz nevus). Am J Surg Pathol. 1989;13:931-939.
  14. Barnhill RL. Childhood melanoma. Semin Diagn Pathol. 1998;15:189-194.
  15. Melnik MK, Urdaneta LF, Al-Jurf AS, et al. Malignant melanoma in childhood and adolescence. Am Surg. 1986;52:142-147.
  16. Shapiro PE. Spitz nevi. J Am Acad Dermatol. 1993;29:667-668.
  17. Gurbuz Y, Apaydin R, Muezzinoglu B, et al. A current dilemma in histopathology: atypical spitz tumor or Spitzoid melanoma? Pediatr Dermatol. 2002;19:99-102.
  18. Lohmann CM, Coit DG, Brady MS, et al. Sentinel lymph node biopsy in patients with diagnostically controversial spitzoid melanocytic tumors. Am J Surg Pathol. 2002;26:47-55.
  19. Handfield-Jones SE, Smith NP. Malignant melanoma in childhood. Br J Dermatol. 1996;134:607-616.
  20. Crotty KA, McCarthy SW, Palmer AA, et al. Malignant melanoma in childhood: a clinicopathologic study of 13 cases and comparison with Spitz nevi. World J Surg. 1992;16:179-185.
  21. Lerman RI, Murray D, O'Hara JM, et al. Malignant melanoma of childhood. a clinicopathologic study and a report of 12 cases. Cancer. 1970;25:436-449.
  22. Farmer ER, Gonin R, Hanna MP. Discordance in the histopathologic diagnosis of melanoma and melano-cytic nevi between expert pathologists. Hum Pathol.1996;27:528-531.
  23. Shimek CM, Golitz LE. The golden anniversary of the Spitz nevus. Arch Dermatol. 1999;135:333-335.
  24. Bastian BC, Wesselmann U, Pinkel D, et al. Molecular cytogenetic analysis of Spitz nevi shows clear differences to melanoma. J Invest Dermatol.1999; 113:1065-1069.
  25. Bastian BC, LeBoit PE, Hamm H, et al. Chromo-somal gains and losses in primary cutaneous melanomas detected by comparative genomic hybridization. Cancer Res.1998;58:2170-2175.
  26. Bergman R, Malkin L, Sabo E, et al. MIB-1 mono-clonal antibody to determine proliferative activity of Ki-67 antigen as an adjunct to the histopathologic dif-ferential diagnosis of Spitz nevi. J Am Acad Dermatol. 2001; 44:500-504.
  27. Li LX, Crotty KA, McCarthy SW, et al. A zonal com-parison of MIB1-Ki67 immunoreactivity in benign and malignant melanocytic lesions. Am J Dermatopathol. 2000;22:489-495.
  28. McNutt NS, Urmacher C, Hakimian J, et al. Nevoid malignant melanoma: morphologicpatterns and immu-nohistochemical reactivity. J Cutan Pathol.1995;22:502-517.
  29. Kanter-Lewensohn L, Hedblad MA, Wejde J, et al. Immu-nohistochemical markers for distinguishing Spitz nevi from malignant melanomas. Mod Pathol.1997;10:917-920.
  30. Ribé A, McNutt NS. S100A6 protein expression is different in spitz nevi and melanomas.  Mod Pathol.2003;16:505-511.
  31. Kaye VN, Dehner LP. Spindle and epithelioid cell nevus (Spitz nevus). natural history following biopsy. Arch Dermatol.1990;126:1581-1583.
  32. Omura EF, Kheir SM. Recurrent Spitz’s nevus. Am J. Dermatopathol.1984;6(suppl): 207212.
  33. Zaenglein AL, Heintz P, Kamino H, et al. Congenital Spitz nevus clinically mimicking melanoma. J Am Acad Dermatol.2002;47:441-444.
  34. Murphy ME, Boyer JD, Stashower ME, et al. The surgical management of Spitz nevi. Dermatol Surg. 2002;28:1065-1069.
  35. Zitelli JA, Brown C, Hanusa BH. Mohs micrographic surgery for the treatment of primary cutaneous melanoma. J Am Acad Dermatol. 1997;37:236-245.
  36. Kelley SW, Cockerell CJ. Sentinel lymph node biopsy as an adjunct to management of histologically difficult to diagnose melanocytic lesions: a proposal. J Am Acad Dermatol. 2000;42:527-530.
  37. Su LD, Fullen DR, Sondak VK, et al. Sentinel lymph node biopsy for patients with problematic spitzoid melanocytic lesions: a report on 18 patients. Cancer. 2003;97:499-507.
  38. Martinez JC, Otley CC. The management of melanoma and nonmelanoma skin cancer: a review for the primary care physician. Mayo Clin Proc. 2001;76:1253-1265.
References

 

 

  1. Spitz S. Melanomas of childhood. Am J Pathol. 1948;24:591-609.
  2. Spatz A, Barnhill RL. The Spitz tumor 50 years later: revisiting a landmark contribution and unresolved controversy. J Am Acad Dermatol. 1999;40:223-228.
  3. Paniago-Pereira C, Maize JC, Ackerman AB. Nevus of large spindle and/or epithelioid cells (Spitz's nevus). Arch Dermatol. 1978;114:1811-1823.
  4. Casso EM, Grin-Jorgensen CM, Grant-Kels JM. Spitz nevi. J Am Acad Dermatol. 1992;27:901-913.
  5. Barnhill RL, Argenyi ZB, From L, et al. Atypical Spitz nevi/tumors: lack of consensus for diagnosis, discrimination from melanoma, and prediction of outcome. Hum Pathol. 1999;30:513-520.
  6. Herreid PA, Shapiro PE. Age distribution of Spitz nevus vs malignant melanoma. Arch Dermatol. 1996;132:352-353.
  7. Weedon D, Little JH. Spindle and epithelioid cell nevi in children and adults. a review of 211 cases of the Spitz nevus. Cancer. 1977;40:217-225.
  8. Bader JL, Li FP, Olmstead PM, et al. Childhood malignant melanoma. incidence and etiology. Am J Pediatr Hematol Oncol. 1985;7:341-345.
  9. Elder DE, Murphy GF. Melanocytic tumors of the skin. In: Elder DE, Murphy GF, eds. Atlas of Tumor Pathology. Washington, DC: Armed Forces Institute of Pathology; 1990:40-57.
  10. Piepkorn M. On the nature of histologic observations: the case of the Spitz nevus. J Am Acad Dermatol. 1995;32:248-254.
  11. Barnhill RL, Flotte TJ, Fleischli M, et al. Cutaneous melanoma and atypical Spitz tumors in childhood. Cancer. 1995;76:1833-1845.
  12. Spatz A, Calonje E, Handfield-Jones S, et al. Spitz tumors in children: a grading system for risk stratification. Arch Dermatol. 1999;135:282-285.
  13. Smith KJ, Barrett TL, Skelton HG 3rd, et al. Spindle cell and epithelioid cell nevi with atypia and metastasis (malignant Spitz nevus). Am J Surg Pathol. 1989;13:931-939.
  14. Barnhill RL. Childhood melanoma. Semin Diagn Pathol. 1998;15:189-194.
  15. Melnik MK, Urdaneta LF, Al-Jurf AS, et al. Malignant melanoma in childhood and adolescence. Am Surg. 1986;52:142-147.
  16. Shapiro PE. Spitz nevi. J Am Acad Dermatol. 1993;29:667-668.
  17. Gurbuz Y, Apaydin R, Muezzinoglu B, et al. A current dilemma in histopathology: atypical spitz tumor or Spitzoid melanoma? Pediatr Dermatol. 2002;19:99-102.
  18. Lohmann CM, Coit DG, Brady MS, et al. Sentinel lymph node biopsy in patients with diagnostically controversial spitzoid melanocytic tumors. Am J Surg Pathol. 2002;26:47-55.
  19. Handfield-Jones SE, Smith NP. Malignant melanoma in childhood. Br J Dermatol. 1996;134:607-616.
  20. Crotty KA, McCarthy SW, Palmer AA, et al. Malignant melanoma in childhood: a clinicopathologic study of 13 cases and comparison with Spitz nevi. World J Surg. 1992;16:179-185.
  21. Lerman RI, Murray D, O'Hara JM, et al. Malignant melanoma of childhood. a clinicopathologic study and a report of 12 cases. Cancer. 1970;25:436-449.
  22. Farmer ER, Gonin R, Hanna MP. Discordance in the histopathologic diagnosis of melanoma and melano-cytic nevi between expert pathologists. Hum Pathol.1996;27:528-531.
  23. Shimek CM, Golitz LE. The golden anniversary of the Spitz nevus. Arch Dermatol. 1999;135:333-335.
  24. Bastian BC, Wesselmann U, Pinkel D, et al. Molecular cytogenetic analysis of Spitz nevi shows clear differences to melanoma. J Invest Dermatol.1999; 113:1065-1069.
  25. Bastian BC, LeBoit PE, Hamm H, et al. Chromo-somal gains and losses in primary cutaneous melanomas detected by comparative genomic hybridization. Cancer Res.1998;58:2170-2175.
  26. Bergman R, Malkin L, Sabo E, et al. MIB-1 mono-clonal antibody to determine proliferative activity of Ki-67 antigen as an adjunct to the histopathologic dif-ferential diagnosis of Spitz nevi. J Am Acad Dermatol. 2001; 44:500-504.
  27. Li LX, Crotty KA, McCarthy SW, et al. A zonal com-parison of MIB1-Ki67 immunoreactivity in benign and malignant melanocytic lesions. Am J Dermatopathol. 2000;22:489-495.
  28. McNutt NS, Urmacher C, Hakimian J, et al. Nevoid malignant melanoma: morphologicpatterns and immu-nohistochemical reactivity. J Cutan Pathol.1995;22:502-517.
  29. Kanter-Lewensohn L, Hedblad MA, Wejde J, et al. Immu-nohistochemical markers for distinguishing Spitz nevi from malignant melanomas. Mod Pathol.1997;10:917-920.
  30. Ribé A, McNutt NS. S100A6 protein expression is different in spitz nevi and melanomas.  Mod Pathol.2003;16:505-511.
  31. Kaye VN, Dehner LP. Spindle and epithelioid cell nevus (Spitz nevus). natural history following biopsy. Arch Dermatol.1990;126:1581-1583.
  32. Omura EF, Kheir SM. Recurrent Spitz’s nevus. Am J. Dermatopathol.1984;6(suppl): 207212.
  33. Zaenglein AL, Heintz P, Kamino H, et al. Congenital Spitz nevus clinically mimicking melanoma. J Am Acad Dermatol.2002;47:441-444.
  34. Murphy ME, Boyer JD, Stashower ME, et al. The surgical management of Spitz nevi. Dermatol Surg. 2002;28:1065-1069.
  35. Zitelli JA, Brown C, Hanusa BH. Mohs micrographic surgery for the treatment of primary cutaneous melanoma. J Am Acad Dermatol. 1997;37:236-245.
  36. Kelley SW, Cockerell CJ. Sentinel lymph node biopsy as an adjunct to management of histologically difficult to diagnose melanocytic lesions: a proposal. J Am Acad Dermatol. 2000;42:527-530.
  37. Su LD, Fullen DR, Sondak VK, et al. Sentinel lymph node biopsy for patients with problematic spitzoid melanocytic lesions: a report on 18 patients. Cancer. 2003;97:499-507.
  38. Martinez JC, Otley CC. The management of melanoma and nonmelanoma skin cancer: a review for the primary care physician. Mayo Clin Proc. 2001;76:1253-1265.
Issue
Cutis - 79(2)
Issue
Cutis - 79(2)
Page Number
141-146
Page Number
141-146
Publications
Publications
Topics
Article Type
Display Headline
Classic and Atypical Spitz Nevi: Review of the Literature
Display Headline
Classic and Atypical Spitz Nevi: Review of the Literature
Disallow All Ads
Alternative CME
Article PDF Media

What is the preferred treatment for a child with mild persistent asthma?

Article Type
Changed
Mon, 01/14/2019 - 11:18
Display Headline
What is the preferred treatment for a child with mild persistent asthma?
EVIDENCE-BASED ANSWER

Low-dose inhaled corticosteroids are the preferred treatment for children with mild persistent asthma because they demonstrate superior reduction in severity and frequency of asthma exacerbations compared with alternatives (strength of recommendation [SOR]: A, based on multiple randomized controlled trials). As add-on therapy, nedocromil, theophylline, and cromolyn have all demonstrated a modest benefit in symptom control; leukotriene receptor antagonists are also recommended based on data from older children (SOR: B, cohort study). Unlike treatment of moderate or severe asthma, long-acting beta-agonists are not recommended (SOR: A, randomized trials).

CLINICAL COMMENTARY

Clear medication choices for mild asthma are supported by good evidence
John Heintzman, MD
Oregon Health and Science University, Portland

Physicians who routinely treat children with asthma are fortunate to have the body of evidence outlined in this review. Clear medication choices are supported in most instances by relatively clear comparisons with alternatives. In my practice, where many children can be classified in the “mild persistent” category, I am always surprised at how many patients’ families lack a clear understanding of the factors that trigger a child’s asthma and how to avoid them.

Another common clinical scenario among children and adolescents is exercise-induced asthma. Depending on the sport, the asthma can be classified as “mild persistent” or “mild intermittent.” for true intermittent symptoms, my clinical experience (and often parental preference) argues for pre-activity treatment with short acting beta-agonists as the most practical therapy.

 

Evidence summary

Mild persistent asthma is defined as forced expiratory volume over 1 second (FEV1) ≥80% predicted, with daytime symptoms more than twice per week but less than once daily, and nighttime symptoms more often than twice monthly.1

Low-dose inhaled corticosteroids

Two large randomized trials support using low-dose inhaled corticosteroids in these children. The Childhood Asthma Management Program (CAMP) study, which included 1041 children, evaluated treatment with either budesonide or nedocromil vs placebo. Patients taking budesonide had a lower rate of urgent care visits (absolute risk reduction [ARR]=10%; number needed to treat [NNT]=10; P=.02) compared with children taking nedocromil (ARR=6%; NNT=17; P=.02). The urgent care visits were reported as number of visits per 100 person-years.

In practical terms, this means that in order to decrease 1 urgent care visit, 1 patient would need to take budesonide for 10 years. However, because rates are not necessarily homogenous over time, the number of visits decreased during the first year may be different than the number of events decreased throughout the tenth year.

Children taking budesonide experienced 21.5% more episode-free days than those taking placebo (P=.01). No change was observed in the nedocromil group.2 In the inhaled Steroid Treatment As Regular Therapy (START) in early asthma study, budesonide demonstrated a 44% relative reduction in time to first severe asthma related event, compared with placebo (95% confidence interval [CI], 0.45–0.71; NNT=44; P=.0001).3

 

Theophylline

Theophylline is considered an alternative to inhaled corticosteroids. One study compared beclomethasone with theophylline in 195 children. This study found near-equivalent efficacy in doctor visits, hospitalizations, monthly peak expiratory flow rates, and FEV1; however, beclomethasone was superior to theophylline in maintaining symptom control and decreasing the use of inhaled bronchodilators and systemic steroids.

 

 

 

When compared with beclomethasone, theophylline was linked to 14% more central nervous system adverse effects (P<.001) and 17% more gastrointestinal disturbances (P<.001). Although beclomethasone induced more oral candidiasis compared with theophylline (8.9% vs 2.4%; P<.001), the incidence of this infection can be reduced by using a spacer.

Long-term systemic effects

The potential long-term adverse systemic effects of inhaled corticosteroids on growth, bone metabolism, and pituitary-adrenal function call for longer-term studies.4 A systematic review of 15 trials reported that the protective effect of leukotriene receptor antagonists is inferior to inhaled corticosteroids for adults (relative risk [RR]=1.71; 95% CI, 1.40–2.09); however, evidence is insufficient to extrapolate this to children.5

Beta-agonists

Evidence does not support use of long-acting beta-agonists as monotherapy or in combination with other medications for children with mild persistent asthma. Although 1 study showed an improvement in lung function for children taking budesonide plus formoterol compared with budesonide alone, the rate of severe exacerbations was lower for those taking budesonide alone (62% decrease vs 55.8% decrease; P=.001). Both groups had a 32% decrease in the number of rescue inhalations per day when compared with placebo (P=.0008).6

Recommendations from others

Recommendations are listed in the TABLE.1,7,8 Unlike the NAEPP and GINA asthma guidelines, the BTS/SIGN asthma guidelines define no objective measurement or staging classification to diagnose asthma among children. Diagnosis is determined by a child’s response to medication.8 Independent of any daily controller medication use, all children should have a short acting bronchodilator on hand in case of an acute attack.1,8

TABLE
Recommendations for treating mild persistent asthma

GUIDELINEDAILY CONTROLLER MEDICATIONALTERNATIVE TREATMENT
National Asthma Education and Prevention Program (NAEPP)1Low-dose inhaled corticosteroidsChildren <5: cromolyn, LTRAs Children >5: cromolyn, LTRAs, nedocromil, sustained release theophylline
Global initiative for asthma (GINA)7low-dose inhaled corticosteroidsAll children: sustained released theophylline, Cromone, LTRAs
British Thoracic Society/Scottish intercollegiate Guidelines network (BTS/SIGN)8Inhaled steroidsAll children: LTRAs, theophylline Children >5: cromones, nedocromil
LRTA leukotriene receptor antagonists.
Sources: NAEPP J Allergy Clin Immunol 20021; GINA Guidelines and Resources 20057 and BTS/SIGN, Thorax 2003.8
References

1. National Asthma Education and Prevention Program. Expert Panel Report: Guidelines for the Diagnosis and Management of Asthma Update on Selected Topics—2002. National Asthma Education and Prevention Program. J Allergy Clin Immunol 2002;110:S141-S219.

2. Long-term effects of budesonide or nedocromil in children with asthma. The Childhood Asthma Management Program Research Group. N Engl J Med 2000;343:1054-1063.

3. Pauwels RA, Pedersen S, Busse WW, et al. START Investigators Group. Early intervention with budesonide in mild persistent asthma: a randomised, double-blind trial. Lancet 2003;361:1071-1076.

4. Reed CE, Offord KP, Nelson HS, Li JT, Tinkelman DG. Aerosol beclomethasone dipropionate spray compared with theophylline as primary treatment for chronic mild-to-moderate asthma. The American Academy of Allergy, Asthma and Immunology Beclomethasone Dipropionate-Theophylline Study Group. J Allergy Clin Immunol 1998;101:14-23.

5. Ducharme FM, Salvio F, Ducharme F. Anti-leukotriene agents compared to inhaled corticosteroids in the management of recurrent and/or chronic asthma in adults and children (Cochrane review). In: The Cochrane Library. 2006 Issue 2. Chichester, UK: John Wiley and Sons, Ltd.

6. O’byrne PM, Barnes PJ, Rodriguez-Roisin R, et al. Low dose inhaled budesonide and formoterol in mild persistent asthma: the OPTIMA randomized trial. Am J Respir Crit Care Med 2001;164:1392-1397.

7. The Global Initiative for Asthma. Guidelines and Resources: 2005 Update. Available at: www.ginasthma.com/Guidelineitem.asp??I1=2&I2=1&intId=60. Accessed January 9, 2007.

8. British Thoracic Society Scottish Intercollegiate Guidelines Network. British guideline on the management of asthma. A national clinical guideline. Thorax 2003;58:i1-i94.

Article PDF
Author and Disclosure Information

Brice A. Labruzzo, PharmD
Louisiana State University Health Sciences Center, Shreveport

Lisa Edgerton, PharmD
New Hanover Regional Medical Center, Wilmington, NC

Stacy Rideout, MLIS, MA
Wake Area Health Education Center Medical Library, Raleigh, NC

Issue
The Journal of Family Practice - 56(2)
Publications
Topics
Page Number
137-139
Sections
Author and Disclosure Information

Brice A. Labruzzo, PharmD
Louisiana State University Health Sciences Center, Shreveport

Lisa Edgerton, PharmD
New Hanover Regional Medical Center, Wilmington, NC

Stacy Rideout, MLIS, MA
Wake Area Health Education Center Medical Library, Raleigh, NC

Author and Disclosure Information

Brice A. Labruzzo, PharmD
Louisiana State University Health Sciences Center, Shreveport

Lisa Edgerton, PharmD
New Hanover Regional Medical Center, Wilmington, NC

Stacy Rideout, MLIS, MA
Wake Area Health Education Center Medical Library, Raleigh, NC

Article PDF
Article PDF
EVIDENCE-BASED ANSWER

Low-dose inhaled corticosteroids are the preferred treatment for children with mild persistent asthma because they demonstrate superior reduction in severity and frequency of asthma exacerbations compared with alternatives (strength of recommendation [SOR]: A, based on multiple randomized controlled trials). As add-on therapy, nedocromil, theophylline, and cromolyn have all demonstrated a modest benefit in symptom control; leukotriene receptor antagonists are also recommended based on data from older children (SOR: B, cohort study). Unlike treatment of moderate or severe asthma, long-acting beta-agonists are not recommended (SOR: A, randomized trials).

CLINICAL COMMENTARY

Clear medication choices for mild asthma are supported by good evidence
John Heintzman, MD
Oregon Health and Science University, Portland

Physicians who routinely treat children with asthma are fortunate to have the body of evidence outlined in this review. Clear medication choices are supported in most instances by relatively clear comparisons with alternatives. In my practice, where many children can be classified in the “mild persistent” category, I am always surprised at how many patients’ families lack a clear understanding of the factors that trigger a child’s asthma and how to avoid them.

Another common clinical scenario among children and adolescents is exercise-induced asthma. Depending on the sport, the asthma can be classified as “mild persistent” or “mild intermittent.” for true intermittent symptoms, my clinical experience (and often parental preference) argues for pre-activity treatment with short acting beta-agonists as the most practical therapy.

 

Evidence summary

Mild persistent asthma is defined as forced expiratory volume over 1 second (FEV1) ≥80% predicted, with daytime symptoms more than twice per week but less than once daily, and nighttime symptoms more often than twice monthly.1

Low-dose inhaled corticosteroids

Two large randomized trials support using low-dose inhaled corticosteroids in these children. The Childhood Asthma Management Program (CAMP) study, which included 1041 children, evaluated treatment with either budesonide or nedocromil vs placebo. Patients taking budesonide had a lower rate of urgent care visits (absolute risk reduction [ARR]=10%; number needed to treat [NNT]=10; P=.02) compared with children taking nedocromil (ARR=6%; NNT=17; P=.02). The urgent care visits were reported as number of visits per 100 person-years.

In practical terms, this means that in order to decrease 1 urgent care visit, 1 patient would need to take budesonide for 10 years. However, because rates are not necessarily homogenous over time, the number of visits decreased during the first year may be different than the number of events decreased throughout the tenth year.

Children taking budesonide experienced 21.5% more episode-free days than those taking placebo (P=.01). No change was observed in the nedocromil group.2 In the inhaled Steroid Treatment As Regular Therapy (START) in early asthma study, budesonide demonstrated a 44% relative reduction in time to first severe asthma related event, compared with placebo (95% confidence interval [CI], 0.45–0.71; NNT=44; P=.0001).3

 

Theophylline

Theophylline is considered an alternative to inhaled corticosteroids. One study compared beclomethasone with theophylline in 195 children. This study found near-equivalent efficacy in doctor visits, hospitalizations, monthly peak expiratory flow rates, and FEV1; however, beclomethasone was superior to theophylline in maintaining symptom control and decreasing the use of inhaled bronchodilators and systemic steroids.

 

 

 

When compared with beclomethasone, theophylline was linked to 14% more central nervous system adverse effects (P<.001) and 17% more gastrointestinal disturbances (P<.001). Although beclomethasone induced more oral candidiasis compared with theophylline (8.9% vs 2.4%; P<.001), the incidence of this infection can be reduced by using a spacer.

Long-term systemic effects

The potential long-term adverse systemic effects of inhaled corticosteroids on growth, bone metabolism, and pituitary-adrenal function call for longer-term studies.4 A systematic review of 15 trials reported that the protective effect of leukotriene receptor antagonists is inferior to inhaled corticosteroids for adults (relative risk [RR]=1.71; 95% CI, 1.40–2.09); however, evidence is insufficient to extrapolate this to children.5

Beta-agonists

Evidence does not support use of long-acting beta-agonists as monotherapy or in combination with other medications for children with mild persistent asthma. Although 1 study showed an improvement in lung function for children taking budesonide plus formoterol compared with budesonide alone, the rate of severe exacerbations was lower for those taking budesonide alone (62% decrease vs 55.8% decrease; P=.001). Both groups had a 32% decrease in the number of rescue inhalations per day when compared with placebo (P=.0008).6

Recommendations from others

Recommendations are listed in the TABLE.1,7,8 Unlike the NAEPP and GINA asthma guidelines, the BTS/SIGN asthma guidelines define no objective measurement or staging classification to diagnose asthma among children. Diagnosis is determined by a child’s response to medication.8 Independent of any daily controller medication use, all children should have a short acting bronchodilator on hand in case of an acute attack.1,8

TABLE
Recommendations for treating mild persistent asthma

GUIDELINEDAILY CONTROLLER MEDICATIONALTERNATIVE TREATMENT
National Asthma Education and Prevention Program (NAEPP)1Low-dose inhaled corticosteroidsChildren <5: cromolyn, LTRAs Children >5: cromolyn, LTRAs, nedocromil, sustained release theophylline
Global initiative for asthma (GINA)7low-dose inhaled corticosteroidsAll children: sustained released theophylline, Cromone, LTRAs
British Thoracic Society/Scottish intercollegiate Guidelines network (BTS/SIGN)8Inhaled steroidsAll children: LTRAs, theophylline Children >5: cromones, nedocromil
LRTA leukotriene receptor antagonists.
Sources: NAEPP J Allergy Clin Immunol 20021; GINA Guidelines and Resources 20057 and BTS/SIGN, Thorax 2003.8
EVIDENCE-BASED ANSWER

Low-dose inhaled corticosteroids are the preferred treatment for children with mild persistent asthma because they demonstrate superior reduction in severity and frequency of asthma exacerbations compared with alternatives (strength of recommendation [SOR]: A, based on multiple randomized controlled trials). As add-on therapy, nedocromil, theophylline, and cromolyn have all demonstrated a modest benefit in symptom control; leukotriene receptor antagonists are also recommended based on data from older children (SOR: B, cohort study). Unlike treatment of moderate or severe asthma, long-acting beta-agonists are not recommended (SOR: A, randomized trials).

CLINICAL COMMENTARY

Clear medication choices for mild asthma are supported by good evidence
John Heintzman, MD
Oregon Health and Science University, Portland

Physicians who routinely treat children with asthma are fortunate to have the body of evidence outlined in this review. Clear medication choices are supported in most instances by relatively clear comparisons with alternatives. In my practice, where many children can be classified in the “mild persistent” category, I am always surprised at how many patients’ families lack a clear understanding of the factors that trigger a child’s asthma and how to avoid them.

Another common clinical scenario among children and adolescents is exercise-induced asthma. Depending on the sport, the asthma can be classified as “mild persistent” or “mild intermittent.” for true intermittent symptoms, my clinical experience (and often parental preference) argues for pre-activity treatment with short acting beta-agonists as the most practical therapy.

 

Evidence summary

Mild persistent asthma is defined as forced expiratory volume over 1 second (FEV1) ≥80% predicted, with daytime symptoms more than twice per week but less than once daily, and nighttime symptoms more often than twice monthly.1

Low-dose inhaled corticosteroids

Two large randomized trials support using low-dose inhaled corticosteroids in these children. The Childhood Asthma Management Program (CAMP) study, which included 1041 children, evaluated treatment with either budesonide or nedocromil vs placebo. Patients taking budesonide had a lower rate of urgent care visits (absolute risk reduction [ARR]=10%; number needed to treat [NNT]=10; P=.02) compared with children taking nedocromil (ARR=6%; NNT=17; P=.02). The urgent care visits were reported as number of visits per 100 person-years.

In practical terms, this means that in order to decrease 1 urgent care visit, 1 patient would need to take budesonide for 10 years. However, because rates are not necessarily homogenous over time, the number of visits decreased during the first year may be different than the number of events decreased throughout the tenth year.

Children taking budesonide experienced 21.5% more episode-free days than those taking placebo (P=.01). No change was observed in the nedocromil group.2 In the inhaled Steroid Treatment As Regular Therapy (START) in early asthma study, budesonide demonstrated a 44% relative reduction in time to first severe asthma related event, compared with placebo (95% confidence interval [CI], 0.45–0.71; NNT=44; P=.0001).3

 

Theophylline

Theophylline is considered an alternative to inhaled corticosteroids. One study compared beclomethasone with theophylline in 195 children. This study found near-equivalent efficacy in doctor visits, hospitalizations, monthly peak expiratory flow rates, and FEV1; however, beclomethasone was superior to theophylline in maintaining symptom control and decreasing the use of inhaled bronchodilators and systemic steroids.

 

 

 

When compared with beclomethasone, theophylline was linked to 14% more central nervous system adverse effects (P<.001) and 17% more gastrointestinal disturbances (P<.001). Although beclomethasone induced more oral candidiasis compared with theophylline (8.9% vs 2.4%; P<.001), the incidence of this infection can be reduced by using a spacer.

Long-term systemic effects

The potential long-term adverse systemic effects of inhaled corticosteroids on growth, bone metabolism, and pituitary-adrenal function call for longer-term studies.4 A systematic review of 15 trials reported that the protective effect of leukotriene receptor antagonists is inferior to inhaled corticosteroids for adults (relative risk [RR]=1.71; 95% CI, 1.40–2.09); however, evidence is insufficient to extrapolate this to children.5

Beta-agonists

Evidence does not support use of long-acting beta-agonists as monotherapy or in combination with other medications for children with mild persistent asthma. Although 1 study showed an improvement in lung function for children taking budesonide plus formoterol compared with budesonide alone, the rate of severe exacerbations was lower for those taking budesonide alone (62% decrease vs 55.8% decrease; P=.001). Both groups had a 32% decrease in the number of rescue inhalations per day when compared with placebo (P=.0008).6

Recommendations from others

Recommendations are listed in the TABLE.1,7,8 Unlike the NAEPP and GINA asthma guidelines, the BTS/SIGN asthma guidelines define no objective measurement or staging classification to diagnose asthma among children. Diagnosis is determined by a child’s response to medication.8 Independent of any daily controller medication use, all children should have a short acting bronchodilator on hand in case of an acute attack.1,8

TABLE
Recommendations for treating mild persistent asthma

GUIDELINEDAILY CONTROLLER MEDICATIONALTERNATIVE TREATMENT
National Asthma Education and Prevention Program (NAEPP)1Low-dose inhaled corticosteroidsChildren <5: cromolyn, LTRAs Children >5: cromolyn, LTRAs, nedocromil, sustained release theophylline
Global initiative for asthma (GINA)7low-dose inhaled corticosteroidsAll children: sustained released theophylline, Cromone, LTRAs
British Thoracic Society/Scottish intercollegiate Guidelines network (BTS/SIGN)8Inhaled steroidsAll children: LTRAs, theophylline Children >5: cromones, nedocromil
LRTA leukotriene receptor antagonists.
Sources: NAEPP J Allergy Clin Immunol 20021; GINA Guidelines and Resources 20057 and BTS/SIGN, Thorax 2003.8
References

1. National Asthma Education and Prevention Program. Expert Panel Report: Guidelines for the Diagnosis and Management of Asthma Update on Selected Topics—2002. National Asthma Education and Prevention Program. J Allergy Clin Immunol 2002;110:S141-S219.

2. Long-term effects of budesonide or nedocromil in children with asthma. The Childhood Asthma Management Program Research Group. N Engl J Med 2000;343:1054-1063.

3. Pauwels RA, Pedersen S, Busse WW, et al. START Investigators Group. Early intervention with budesonide in mild persistent asthma: a randomised, double-blind trial. Lancet 2003;361:1071-1076.

4. Reed CE, Offord KP, Nelson HS, Li JT, Tinkelman DG. Aerosol beclomethasone dipropionate spray compared with theophylline as primary treatment for chronic mild-to-moderate asthma. The American Academy of Allergy, Asthma and Immunology Beclomethasone Dipropionate-Theophylline Study Group. J Allergy Clin Immunol 1998;101:14-23.

5. Ducharme FM, Salvio F, Ducharme F. Anti-leukotriene agents compared to inhaled corticosteroids in the management of recurrent and/or chronic asthma in adults and children (Cochrane review). In: The Cochrane Library. 2006 Issue 2. Chichester, UK: John Wiley and Sons, Ltd.

6. O’byrne PM, Barnes PJ, Rodriguez-Roisin R, et al. Low dose inhaled budesonide and formoterol in mild persistent asthma: the OPTIMA randomized trial. Am J Respir Crit Care Med 2001;164:1392-1397.

7. The Global Initiative for Asthma. Guidelines and Resources: 2005 Update. Available at: www.ginasthma.com/Guidelineitem.asp??I1=2&I2=1&intId=60. Accessed January 9, 2007.

8. British Thoracic Society Scottish Intercollegiate Guidelines Network. British guideline on the management of asthma. A national clinical guideline. Thorax 2003;58:i1-i94.

References

1. National Asthma Education and Prevention Program. Expert Panel Report: Guidelines for the Diagnosis and Management of Asthma Update on Selected Topics—2002. National Asthma Education and Prevention Program. J Allergy Clin Immunol 2002;110:S141-S219.

2. Long-term effects of budesonide or nedocromil in children with asthma. The Childhood Asthma Management Program Research Group. N Engl J Med 2000;343:1054-1063.

3. Pauwels RA, Pedersen S, Busse WW, et al. START Investigators Group. Early intervention with budesonide in mild persistent asthma: a randomised, double-blind trial. Lancet 2003;361:1071-1076.

4. Reed CE, Offord KP, Nelson HS, Li JT, Tinkelman DG. Aerosol beclomethasone dipropionate spray compared with theophylline as primary treatment for chronic mild-to-moderate asthma. The American Academy of Allergy, Asthma and Immunology Beclomethasone Dipropionate-Theophylline Study Group. J Allergy Clin Immunol 1998;101:14-23.

5. Ducharme FM, Salvio F, Ducharme F. Anti-leukotriene agents compared to inhaled corticosteroids in the management of recurrent and/or chronic asthma in adults and children (Cochrane review). In: The Cochrane Library. 2006 Issue 2. Chichester, UK: John Wiley and Sons, Ltd.

6. O’byrne PM, Barnes PJ, Rodriguez-Roisin R, et al. Low dose inhaled budesonide and formoterol in mild persistent asthma: the OPTIMA randomized trial. Am J Respir Crit Care Med 2001;164:1392-1397.

7. The Global Initiative for Asthma. Guidelines and Resources: 2005 Update. Available at: www.ginasthma.com/Guidelineitem.asp??I1=2&I2=1&intId=60. Accessed January 9, 2007.

8. British Thoracic Society Scottish Intercollegiate Guidelines Network. British guideline on the management of asthma. A national clinical guideline. Thorax 2003;58:i1-i94.

Issue
The Journal of Family Practice - 56(2)
Issue
The Journal of Family Practice - 56(2)
Page Number
137-139
Page Number
137-139
Publications
Publications
Topics
Article Type
Display Headline
What is the preferred treatment for a child with mild persistent asthma?
Display Headline
What is the preferred treatment for a child with mild persistent asthma?
Sections
PURLs Copyright

Evidence-based answers from the Family Physicians Inquiries Network

Disallow All Ads
Alternative CME
Article PDF Media

Avoid confusion over terms when billing McCall culdoplasty ... Complete and transvaginal US scan must be specified

Article Type
Changed
Tue, 08/28/2018 - 10:53
Display Headline
Avoid confusion over terms when billing McCall culdoplasty ... Complete and transvaginal US scan must be specified

Avoid confusion over terms when billing McCall culdoplasty

Q I performed a McCall culdoplasty following vaginal hysterectomy, but the insurance company denied payment for the culdoplasty, stating that this procedure is included in the hysterectomy. How do I appeal?

ADenial could take place only if the incorrect code combination was billed. For example, if your billing staff itemized the procedures by reporting 58260 for the vaginal hysterectomy and 57268 [Repair of enterocele, vaginal approach (separate procedure)], then the enterocele repair (McCall) would be denied as inclusive, as these two codes are bundled. But they are bundled because there are 4 codes that combine enterocele repair with vaginal hysterectomy, depending on the documented weight of the uterus and whether you took, or left, the tubes and ovaries.

Your code choices are:

58263 Vaginal hysterectomy, for uterus 250 g or less; with removal of tube(s), and/or ovary(s), with repair of enterocele

58270 Vaginal hysterectomy, for uterus 250 g or less; with repair of enterocele

58292 Vaginal hysterectomy, for uterus greater than 250 g; with removal of tube(s) and/or ovary(s), with repair of enterocele

58294 Vaginal hysterectomy, for uterus greater than 250 g; with repair of enterocele

Don’t blame your billing staff if this is what occurred. The term “McCall culdoplasty” appears nowhere in the CPT book, so your billers would need to know that you actually performed an enterocele repair.

Correctly communicating what you did is an important step in getting the claim paid in a timely manner. Refile with the correct code!

Read a description of the technique of McCall culdoplasty.

Complete and transvaginal US scan must be specified

Q Regarding ultrasonography (US) codes 76856 and 76857, are these codes for an abdominal or a vaginal approach? Recently, we scanned a patient transvaginally for a complete US study (uterine, ovary, stripe, etc) but could not determine which code to use. My understanding has been that code 76830 is for a limited transvaginal scan.

ACodes 76856 [Ultrasound, pelvic (nonobstetric), B-scan and/or real time with image documentation; complete] and 76857 [Ultrasound…; limited or follow-up (eg, for follicles)] describe a transabdominal approach. If you performed a complete transvaginal scan, the code would be 76830, which is not a limited scan. In fact, the physician work relative value units assigned to these codes are identical, at .69. The only code for a limited gynecologic US would be 76857. If you performed a limited US by a vaginal approach, however, you can bill 76830 with a modifier -52 (reduced services) added to indicate that you did not perform a complete scan.

Article PDF
Author and Disclosure Information

Melanie Witt, RN, CPC-OGS, MA
Independent coding and documentation consultant; former program manager, Department of Coding and Nomenclature, American College of Obstetricians and Gynecologists

Issue
OBG Management - 19(02)
Publications
Topics
Page Number
73-73
Sections
Author and Disclosure Information

Melanie Witt, RN, CPC-OGS, MA
Independent coding and documentation consultant; former program manager, Department of Coding and Nomenclature, American College of Obstetricians and Gynecologists

Author and Disclosure Information

Melanie Witt, RN, CPC-OGS, MA
Independent coding and documentation consultant; former program manager, Department of Coding and Nomenclature, American College of Obstetricians and Gynecologists

Article PDF
Article PDF

Avoid confusion over terms when billing McCall culdoplasty

Q I performed a McCall culdoplasty following vaginal hysterectomy, but the insurance company denied payment for the culdoplasty, stating that this procedure is included in the hysterectomy. How do I appeal?

ADenial could take place only if the incorrect code combination was billed. For example, if your billing staff itemized the procedures by reporting 58260 for the vaginal hysterectomy and 57268 [Repair of enterocele, vaginal approach (separate procedure)], then the enterocele repair (McCall) would be denied as inclusive, as these two codes are bundled. But they are bundled because there are 4 codes that combine enterocele repair with vaginal hysterectomy, depending on the documented weight of the uterus and whether you took, or left, the tubes and ovaries.

Your code choices are:

58263 Vaginal hysterectomy, for uterus 250 g or less; with removal of tube(s), and/or ovary(s), with repair of enterocele

58270 Vaginal hysterectomy, for uterus 250 g or less; with repair of enterocele

58292 Vaginal hysterectomy, for uterus greater than 250 g; with removal of tube(s) and/or ovary(s), with repair of enterocele

58294 Vaginal hysterectomy, for uterus greater than 250 g; with repair of enterocele

Don’t blame your billing staff if this is what occurred. The term “McCall culdoplasty” appears nowhere in the CPT book, so your billers would need to know that you actually performed an enterocele repair.

Correctly communicating what you did is an important step in getting the claim paid in a timely manner. Refile with the correct code!

Read a description of the technique of McCall culdoplasty.

Complete and transvaginal US scan must be specified

Q Regarding ultrasonography (US) codes 76856 and 76857, are these codes for an abdominal or a vaginal approach? Recently, we scanned a patient transvaginally for a complete US study (uterine, ovary, stripe, etc) but could not determine which code to use. My understanding has been that code 76830 is for a limited transvaginal scan.

ACodes 76856 [Ultrasound, pelvic (nonobstetric), B-scan and/or real time with image documentation; complete] and 76857 [Ultrasound…; limited or follow-up (eg, for follicles)] describe a transabdominal approach. If you performed a complete transvaginal scan, the code would be 76830, which is not a limited scan. In fact, the physician work relative value units assigned to these codes are identical, at .69. The only code for a limited gynecologic US would be 76857. If you performed a limited US by a vaginal approach, however, you can bill 76830 with a modifier -52 (reduced services) added to indicate that you did not perform a complete scan.

Avoid confusion over terms when billing McCall culdoplasty

Q I performed a McCall culdoplasty following vaginal hysterectomy, but the insurance company denied payment for the culdoplasty, stating that this procedure is included in the hysterectomy. How do I appeal?

ADenial could take place only if the incorrect code combination was billed. For example, if your billing staff itemized the procedures by reporting 58260 for the vaginal hysterectomy and 57268 [Repair of enterocele, vaginal approach (separate procedure)], then the enterocele repair (McCall) would be denied as inclusive, as these two codes are bundled. But they are bundled because there are 4 codes that combine enterocele repair with vaginal hysterectomy, depending on the documented weight of the uterus and whether you took, or left, the tubes and ovaries.

Your code choices are:

58263 Vaginal hysterectomy, for uterus 250 g or less; with removal of tube(s), and/or ovary(s), with repair of enterocele

58270 Vaginal hysterectomy, for uterus 250 g or less; with repair of enterocele

58292 Vaginal hysterectomy, for uterus greater than 250 g; with removal of tube(s) and/or ovary(s), with repair of enterocele

58294 Vaginal hysterectomy, for uterus greater than 250 g; with repair of enterocele

Don’t blame your billing staff if this is what occurred. The term “McCall culdoplasty” appears nowhere in the CPT book, so your billers would need to know that you actually performed an enterocele repair.

Correctly communicating what you did is an important step in getting the claim paid in a timely manner. Refile with the correct code!

Read a description of the technique of McCall culdoplasty.

Complete and transvaginal US scan must be specified

Q Regarding ultrasonography (US) codes 76856 and 76857, are these codes for an abdominal or a vaginal approach? Recently, we scanned a patient transvaginally for a complete US study (uterine, ovary, stripe, etc) but could not determine which code to use. My understanding has been that code 76830 is for a limited transvaginal scan.

ACodes 76856 [Ultrasound, pelvic (nonobstetric), B-scan and/or real time with image documentation; complete] and 76857 [Ultrasound…; limited or follow-up (eg, for follicles)] describe a transabdominal approach. If you performed a complete transvaginal scan, the code would be 76830, which is not a limited scan. In fact, the physician work relative value units assigned to these codes are identical, at .69. The only code for a limited gynecologic US would be 76857. If you performed a limited US by a vaginal approach, however, you can bill 76830 with a modifier -52 (reduced services) added to indicate that you did not perform a complete scan.

Issue
OBG Management - 19(02)
Issue
OBG Management - 19(02)
Page Number
73-73
Page Number
73-73
Publications
Publications
Topics
Article Type
Display Headline
Avoid confusion over terms when billing McCall culdoplasty ... Complete and transvaginal US scan must be specified
Display Headline
Avoid confusion over terms when billing McCall culdoplasty ... Complete and transvaginal US scan must be specified
Sections
Article Source

PURLs Copyright

Inside the Article

Article PDF Media

Limits of care: What events can you prevent?

Article Type
Changed
Mon, 04/16/2018 - 14:20
Display Headline
Limits of care: What events can you prevent?

Psychotic patient declines hospital admission, drives into an office building

Cook County (IL) Circuit Court

The patient, age 43, had been treated for mental illness for many years. He was voluntarily admitted to a hospital under the care of his psychiatrist, and was discharged at his own request a few days later. He had improved and was not considered a candidate for involuntary admission because he was not a danger to himself or others.

The patient then informed the psychiatrist that he did not want to continue treatment and said he had an appointment with a new psychiatrist within 2 weeks.

Five days later, the patient went to another hospital for voluntary admission. He was seen by an emergency room physician, who determined the patient was a candidate for voluntary admission. The patient, however, decided to leave the hospital while a bed was being arranged.

Two days later, the patient began having auditory and visual hallucinations. He then drove his car through the glass doors of an office building. No one was injured, but the patient was arrested and convicted of felony damage to property.

In his suit, the patient alleged his longtime psychiatrist was negligent and failed to properly treat him to avoid development of hallucinations. The psychiatrist argued that involuntary admission was not indicated and that the care given was appropriate.

  • A defense verdict was returned

Patient commits suicide after discharge

Cook County (IL) Circuit Court

A patient, age 45, committed suicide by taking lethal doses of medication prescribed by her psychiatrist. The patient had suffered from severe depression, personality disorder, and substance abuse. The day before her death, she went to a hospital emergency room, where she was assessed for suicide and released without the psychiatrist having been notified.

The patient’s family claimed that the psychiatrist was negligent because he did not adequately assess or monitor the patient’s clinical condition at sufficient intervals over the 3 months preceding her suicide. The family also alleged that the psychiatrist prescribed oxycodone inappropriately.

The psychiatrist argued that proper care was given and that the patient failed to provide a complete, accurate medical history at the emergency room visit and did not to consent to admission.

  • A defense verdict was returned

Could admission have prevented patient’s suicide?

Douglas County (NE) District Court

A patient in his mid-60s with a history of depression committed suicide with a gunshot wound to the head. Before his suicide, the patient was seeing a psychiatrist and psychologist for depression and emotional problems.

The patient’s family alleged the psychiatrist failed to diagnose the severity of the patient’s problems and admit him to a hospital for treatment and observation. The psychiatrist and psychologist denied negligence.

  • A defense verdict was returned

Medical malpractice law is constantly evolving to determine what constitutes “negligent care.” The legal standard requires a patient who brings a negligence claim against a psychiatrist to prove:

  • a relationship between patient and psychiatrist such that a duty of care exists
  • the duty was breached—meaning the standard of care was not met
  • the breach of duty caused the injury.

Relationship rules

The first case highlights issues surrounding the patient-psychiatrist relationship. In general, once you have agreed to treat a patient, a doctor-patient relationship and duty of care exists.

In the first case, the patient informed his longtime psychiatrist that he no longer wanted to continue care after discharge. A psychiatrist who terminates a doctor-patient relationship should provide written notice, an explanation of termination, and referrals and continue to care for the patient for a reasonable period.1 No such duty exists, however, when the patient ends treatment. Courts have found that the patient has not been abandoned when he or she voluntarily and unilaterally terminates the relationship.2,3

The relationship ends the moment the patient terminates care, unless the patient is not competent to make that unilateral decision. In that situation, your duty of care to the patient continues.2 When a competent patient terminates care, document the date and time of termination and the patient’s competence.

When relationships begin

The patient in the first case had an appointment with a new psychiatrist within 2 weeks. Is the new psychiatrist liable for what happens in the intervening period or does the relationship begin when the patient has been examined or treated? The legal question of when a physician-patient relationship is created remains problematic. Standards vary from state to state, but general principles offer some guidance.

The physician-patient relationship is a contract. The court would examine parties’ actions to ascertain their intent to determine if the patient reasonably believed that the physician—by actions or words—agreed to provide necessary medical care. Additionally, whether a relationship exists depends on the specific facts and circumstances of each situation.

 

 

There is some authority, across many jurisdictions, that a physician-patient relationship is established only when a physician conducts the initial history and physical examination. In some cases, however, the relationship has been found to exist at an earlier point, such as when a physician gave a referred patient an appointment for a consultation. When in doubt, assume the relationship exists.4

Duty of care

These cases raise areas where possible duty of care was breached:

  • negligent prescription of medication
  • failure to assess suicidal thinking.
Ethical prescribing. In the second case, the patient’s family claimed that oxycodone was prescribed inappropriately. It is unclear from the case why the psychiatrist prescribed oxycodone. Because psychiatrists generally do not prescribe narcotics, the physician may have been prescribing outside of his or her area of professional competence. A psychiatrist who regularly does this is considered to have acted unethically.5

Assessing suicide risk. Negligence in the second and third cases is based upon failure to assess suicidal thoughts. The legal system recognizes that psychiatrists cannot predict suicide,6 and mistakes in clinical judgment are not the same as negligence. Psychiatrists, however, are required to assess suicide risk and intervene appropriately.

When defending a negligence claim, the profession’s custom—reflected by the standard of care common to others with the practitioner’s training—is the benchmark against which the courts measure negligence. Therefore, take steps determined appropriate by the profession and document this risk assessment.7 For example, ask the patient about:

  • suicidal thoughts and intent
  • stressors
  • history of suicidal behavior/attempts
  • substance use
  • signs and symptoms of depression
  • bipolar disorder
  • psychosis.8
Patient dishonesty. Patients who do not disclose their suicidal thoughts might be seen as contributing to negligence. This means that despite the psychiatrist’s mistakes, the harm would not have occurred without the patient’s actions—which could include not being honest about his or her emotional condition. Contributory negligence might relieve the psychiatrist of liability or have an effect on resulting damages.9

Prescriptions. No clear line defines negligence when potentially dangerous medications are prescribed to a suicidal patient. Some psychiatrists dispense limited quantities of medications and see the patient weekly to monitor mood and medication. But even then a psychiatrist cannot prevent suicide—for example, the patient may have multiple prescribers or hoard medications. The concept of “sufficient intervals” to see a patient is determined case-by-case.

Documentation. Make suicide assessments an ongoing process. Document all aspects of the patient’s care, stability, and suicide risk, and reasons for the visit intervals. Indicate in the records your risk-benefit assessment in making treatment decisions.

Cases are selected byfrom Medical Malpractice Verdicts, Settlements & Experts, with permission of its editor, Lewis Laska of Nashville, TN (www.verdictslaska.com). Information may be incomplete in some instances, but these cases represent clinical situations that typically result in litigation.

Drug brand name

  • Oxycodone • Percocet
References

1. American Medical Association Code of Medical Ethics, Opinion 8.115.

2. Knapp v. Eppright, 783 SW2d 293 (Tex 1989).

3. Saunders v. Tisher (Maine Sup. Jud. Ct. 2006).

4. Physicians Risk Management Update. The physician-patient relationship: when does it begin? Available at: http://www.phyins.com/pi/risk/updates/mayjun04.html. Accessed December 28, 2006.

5. American Psychiatric Association. Principles of medical ethics with annotations especially applicable to psychiatry. Washington, DC; 2006. Available at: http://www.psych.org/psych_pract/ethics/ppaethics.cfm. Accessed December 28, 2006.

6. Pokorny A. Prediction of suicide in psychiatric patients. Report of a prospective study. Arch Gen Psychiatry 1983;40(3):249-57.

7. Packman WL, Pennuto TO, Bongar B, Orthwein J. Legal issues of professional negligence in suicide cases. Behav Sci Law 2004;22:697-713.

8. Simon RI. The suicidal patient. In: Lifson LE, Simon RI, eds. The mental health practitioner and the law: a comprehensive handbook. Cambridge, MA: Harvard University Press; 1998:166-86.

9. Maunz v. Perales, 276 Kan. 313, 76 P.3d 1027 (Kan 2003).

Article PDF
Author and Disclosure Information

Jon E. Grant, JD, MD, MPH
Associate professor of psychiatry, University of Minnesota Medical Center, Minneapolis

Issue
Current Psychiatry - 06(02)
Publications
Page Number
48-57
Legacy Keywords
malpractice; malpractice verdicts; liability; medicolegal issues; malpractice lawsuits; medical malpractice; negligence; documentation; suicidality; suicide risk; patient death; patient injury; psychiatric verdicts; psychiatry verdicts; assessing suicidal thinking; assessing suicidality; prescription negligence; prescription liability; doctor-patient relationship; breach of duty; duty of care; ethical prescribing; oxycodone; limits of care; Jon E. Grant; Jon Grant; Grant JE; Grant J
Sections
Author and Disclosure Information

Jon E. Grant, JD, MD, MPH
Associate professor of psychiatry, University of Minnesota Medical Center, Minneapolis

Author and Disclosure Information

Jon E. Grant, JD, MD, MPH
Associate professor of psychiatry, University of Minnesota Medical Center, Minneapolis

Article PDF
Article PDF

Psychotic patient declines hospital admission, drives into an office building

Cook County (IL) Circuit Court

The patient, age 43, had been treated for mental illness for many years. He was voluntarily admitted to a hospital under the care of his psychiatrist, and was discharged at his own request a few days later. He had improved and was not considered a candidate for involuntary admission because he was not a danger to himself or others.

The patient then informed the psychiatrist that he did not want to continue treatment and said he had an appointment with a new psychiatrist within 2 weeks.

Five days later, the patient went to another hospital for voluntary admission. He was seen by an emergency room physician, who determined the patient was a candidate for voluntary admission. The patient, however, decided to leave the hospital while a bed was being arranged.

Two days later, the patient began having auditory and visual hallucinations. He then drove his car through the glass doors of an office building. No one was injured, but the patient was arrested and convicted of felony damage to property.

In his suit, the patient alleged his longtime psychiatrist was negligent and failed to properly treat him to avoid development of hallucinations. The psychiatrist argued that involuntary admission was not indicated and that the care given was appropriate.

  • A defense verdict was returned

Patient commits suicide after discharge

Cook County (IL) Circuit Court

A patient, age 45, committed suicide by taking lethal doses of medication prescribed by her psychiatrist. The patient had suffered from severe depression, personality disorder, and substance abuse. The day before her death, she went to a hospital emergency room, where she was assessed for suicide and released without the psychiatrist having been notified.

The patient’s family claimed that the psychiatrist was negligent because he did not adequately assess or monitor the patient’s clinical condition at sufficient intervals over the 3 months preceding her suicide. The family also alleged that the psychiatrist prescribed oxycodone inappropriately.

The psychiatrist argued that proper care was given and that the patient failed to provide a complete, accurate medical history at the emergency room visit and did not to consent to admission.

  • A defense verdict was returned

Could admission have prevented patient’s suicide?

Douglas County (NE) District Court

A patient in his mid-60s with a history of depression committed suicide with a gunshot wound to the head. Before his suicide, the patient was seeing a psychiatrist and psychologist for depression and emotional problems.

The patient’s family alleged the psychiatrist failed to diagnose the severity of the patient’s problems and admit him to a hospital for treatment and observation. The psychiatrist and psychologist denied negligence.

  • A defense verdict was returned

Medical malpractice law is constantly evolving to determine what constitutes “negligent care.” The legal standard requires a patient who brings a negligence claim against a psychiatrist to prove:

  • a relationship between patient and psychiatrist such that a duty of care exists
  • the duty was breached—meaning the standard of care was not met
  • the breach of duty caused the injury.

Relationship rules

The first case highlights issues surrounding the patient-psychiatrist relationship. In general, once you have agreed to treat a patient, a doctor-patient relationship and duty of care exists.

In the first case, the patient informed his longtime psychiatrist that he no longer wanted to continue care after discharge. A psychiatrist who terminates a doctor-patient relationship should provide written notice, an explanation of termination, and referrals and continue to care for the patient for a reasonable period.1 No such duty exists, however, when the patient ends treatment. Courts have found that the patient has not been abandoned when he or she voluntarily and unilaterally terminates the relationship.2,3

The relationship ends the moment the patient terminates care, unless the patient is not competent to make that unilateral decision. In that situation, your duty of care to the patient continues.2 When a competent patient terminates care, document the date and time of termination and the patient’s competence.

When relationships begin

The patient in the first case had an appointment with a new psychiatrist within 2 weeks. Is the new psychiatrist liable for what happens in the intervening period or does the relationship begin when the patient has been examined or treated? The legal question of when a physician-patient relationship is created remains problematic. Standards vary from state to state, but general principles offer some guidance.

The physician-patient relationship is a contract. The court would examine parties’ actions to ascertain their intent to determine if the patient reasonably believed that the physician—by actions or words—agreed to provide necessary medical care. Additionally, whether a relationship exists depends on the specific facts and circumstances of each situation.

 

 

There is some authority, across many jurisdictions, that a physician-patient relationship is established only when a physician conducts the initial history and physical examination. In some cases, however, the relationship has been found to exist at an earlier point, such as when a physician gave a referred patient an appointment for a consultation. When in doubt, assume the relationship exists.4

Duty of care

These cases raise areas where possible duty of care was breached:

  • negligent prescription of medication
  • failure to assess suicidal thinking.
Ethical prescribing. In the second case, the patient’s family claimed that oxycodone was prescribed inappropriately. It is unclear from the case why the psychiatrist prescribed oxycodone. Because psychiatrists generally do not prescribe narcotics, the physician may have been prescribing outside of his or her area of professional competence. A psychiatrist who regularly does this is considered to have acted unethically.5

Assessing suicide risk. Negligence in the second and third cases is based upon failure to assess suicidal thoughts. The legal system recognizes that psychiatrists cannot predict suicide,6 and mistakes in clinical judgment are not the same as negligence. Psychiatrists, however, are required to assess suicide risk and intervene appropriately.

When defending a negligence claim, the profession’s custom—reflected by the standard of care common to others with the practitioner’s training—is the benchmark against which the courts measure negligence. Therefore, take steps determined appropriate by the profession and document this risk assessment.7 For example, ask the patient about:

  • suicidal thoughts and intent
  • stressors
  • history of suicidal behavior/attempts
  • substance use
  • signs and symptoms of depression
  • bipolar disorder
  • psychosis.8
Patient dishonesty. Patients who do not disclose their suicidal thoughts might be seen as contributing to negligence. This means that despite the psychiatrist’s mistakes, the harm would not have occurred without the patient’s actions—which could include not being honest about his or her emotional condition. Contributory negligence might relieve the psychiatrist of liability or have an effect on resulting damages.9

Prescriptions. No clear line defines negligence when potentially dangerous medications are prescribed to a suicidal patient. Some psychiatrists dispense limited quantities of medications and see the patient weekly to monitor mood and medication. But even then a psychiatrist cannot prevent suicide—for example, the patient may have multiple prescribers or hoard medications. The concept of “sufficient intervals” to see a patient is determined case-by-case.

Documentation. Make suicide assessments an ongoing process. Document all aspects of the patient’s care, stability, and suicide risk, and reasons for the visit intervals. Indicate in the records your risk-benefit assessment in making treatment decisions.

Cases are selected byfrom Medical Malpractice Verdicts, Settlements & Experts, with permission of its editor, Lewis Laska of Nashville, TN (www.verdictslaska.com). Information may be incomplete in some instances, but these cases represent clinical situations that typically result in litigation.

Drug brand name

  • Oxycodone • Percocet

Psychotic patient declines hospital admission, drives into an office building

Cook County (IL) Circuit Court

The patient, age 43, had been treated for mental illness for many years. He was voluntarily admitted to a hospital under the care of his psychiatrist, and was discharged at his own request a few days later. He had improved and was not considered a candidate for involuntary admission because he was not a danger to himself or others.

The patient then informed the psychiatrist that he did not want to continue treatment and said he had an appointment with a new psychiatrist within 2 weeks.

Five days later, the patient went to another hospital for voluntary admission. He was seen by an emergency room physician, who determined the patient was a candidate for voluntary admission. The patient, however, decided to leave the hospital while a bed was being arranged.

Two days later, the patient began having auditory and visual hallucinations. He then drove his car through the glass doors of an office building. No one was injured, but the patient was arrested and convicted of felony damage to property.

In his suit, the patient alleged his longtime psychiatrist was negligent and failed to properly treat him to avoid development of hallucinations. The psychiatrist argued that involuntary admission was not indicated and that the care given was appropriate.

  • A defense verdict was returned

Patient commits suicide after discharge

Cook County (IL) Circuit Court

A patient, age 45, committed suicide by taking lethal doses of medication prescribed by her psychiatrist. The patient had suffered from severe depression, personality disorder, and substance abuse. The day before her death, she went to a hospital emergency room, where she was assessed for suicide and released without the psychiatrist having been notified.

The patient’s family claimed that the psychiatrist was negligent because he did not adequately assess or monitor the patient’s clinical condition at sufficient intervals over the 3 months preceding her suicide. The family also alleged that the psychiatrist prescribed oxycodone inappropriately.

The psychiatrist argued that proper care was given and that the patient failed to provide a complete, accurate medical history at the emergency room visit and did not to consent to admission.

  • A defense verdict was returned

Could admission have prevented patient’s suicide?

Douglas County (NE) District Court

A patient in his mid-60s with a history of depression committed suicide with a gunshot wound to the head. Before his suicide, the patient was seeing a psychiatrist and psychologist for depression and emotional problems.

The patient’s family alleged the psychiatrist failed to diagnose the severity of the patient’s problems and admit him to a hospital for treatment and observation. The psychiatrist and psychologist denied negligence.

  • A defense verdict was returned

Medical malpractice law is constantly evolving to determine what constitutes “negligent care.” The legal standard requires a patient who brings a negligence claim against a psychiatrist to prove:

  • a relationship between patient and psychiatrist such that a duty of care exists
  • the duty was breached—meaning the standard of care was not met
  • the breach of duty caused the injury.

Relationship rules

The first case highlights issues surrounding the patient-psychiatrist relationship. In general, once you have agreed to treat a patient, a doctor-patient relationship and duty of care exists.

In the first case, the patient informed his longtime psychiatrist that he no longer wanted to continue care after discharge. A psychiatrist who terminates a doctor-patient relationship should provide written notice, an explanation of termination, and referrals and continue to care for the patient for a reasonable period.1 No such duty exists, however, when the patient ends treatment. Courts have found that the patient has not been abandoned when he or she voluntarily and unilaterally terminates the relationship.2,3

The relationship ends the moment the patient terminates care, unless the patient is not competent to make that unilateral decision. In that situation, your duty of care to the patient continues.2 When a competent patient terminates care, document the date and time of termination and the patient’s competence.

When relationships begin

The patient in the first case had an appointment with a new psychiatrist within 2 weeks. Is the new psychiatrist liable for what happens in the intervening period or does the relationship begin when the patient has been examined or treated? The legal question of when a physician-patient relationship is created remains problematic. Standards vary from state to state, but general principles offer some guidance.

The physician-patient relationship is a contract. The court would examine parties’ actions to ascertain their intent to determine if the patient reasonably believed that the physician—by actions or words—agreed to provide necessary medical care. Additionally, whether a relationship exists depends on the specific facts and circumstances of each situation.

 

 

There is some authority, across many jurisdictions, that a physician-patient relationship is established only when a physician conducts the initial history and physical examination. In some cases, however, the relationship has been found to exist at an earlier point, such as when a physician gave a referred patient an appointment for a consultation. When in doubt, assume the relationship exists.4

Duty of care

These cases raise areas where possible duty of care was breached:

  • negligent prescription of medication
  • failure to assess suicidal thinking.
Ethical prescribing. In the second case, the patient’s family claimed that oxycodone was prescribed inappropriately. It is unclear from the case why the psychiatrist prescribed oxycodone. Because psychiatrists generally do not prescribe narcotics, the physician may have been prescribing outside of his or her area of professional competence. A psychiatrist who regularly does this is considered to have acted unethically.5

Assessing suicide risk. Negligence in the second and third cases is based upon failure to assess suicidal thoughts. The legal system recognizes that psychiatrists cannot predict suicide,6 and mistakes in clinical judgment are not the same as negligence. Psychiatrists, however, are required to assess suicide risk and intervene appropriately.

When defending a negligence claim, the profession’s custom—reflected by the standard of care common to others with the practitioner’s training—is the benchmark against which the courts measure negligence. Therefore, take steps determined appropriate by the profession and document this risk assessment.7 For example, ask the patient about:

  • suicidal thoughts and intent
  • stressors
  • history of suicidal behavior/attempts
  • substance use
  • signs and symptoms of depression
  • bipolar disorder
  • psychosis.8
Patient dishonesty. Patients who do not disclose their suicidal thoughts might be seen as contributing to negligence. This means that despite the psychiatrist’s mistakes, the harm would not have occurred without the patient’s actions—which could include not being honest about his or her emotional condition. Contributory negligence might relieve the psychiatrist of liability or have an effect on resulting damages.9

Prescriptions. No clear line defines negligence when potentially dangerous medications are prescribed to a suicidal patient. Some psychiatrists dispense limited quantities of medications and see the patient weekly to monitor mood and medication. But even then a psychiatrist cannot prevent suicide—for example, the patient may have multiple prescribers or hoard medications. The concept of “sufficient intervals” to see a patient is determined case-by-case.

Documentation. Make suicide assessments an ongoing process. Document all aspects of the patient’s care, stability, and suicide risk, and reasons for the visit intervals. Indicate in the records your risk-benefit assessment in making treatment decisions.

Cases are selected byfrom Medical Malpractice Verdicts, Settlements & Experts, with permission of its editor, Lewis Laska of Nashville, TN (www.verdictslaska.com). Information may be incomplete in some instances, but these cases represent clinical situations that typically result in litigation.

Drug brand name

  • Oxycodone • Percocet
References

1. American Medical Association Code of Medical Ethics, Opinion 8.115.

2. Knapp v. Eppright, 783 SW2d 293 (Tex 1989).

3. Saunders v. Tisher (Maine Sup. Jud. Ct. 2006).

4. Physicians Risk Management Update. The physician-patient relationship: when does it begin? Available at: http://www.phyins.com/pi/risk/updates/mayjun04.html. Accessed December 28, 2006.

5. American Psychiatric Association. Principles of medical ethics with annotations especially applicable to psychiatry. Washington, DC; 2006. Available at: http://www.psych.org/psych_pract/ethics/ppaethics.cfm. Accessed December 28, 2006.

6. Pokorny A. Prediction of suicide in psychiatric patients. Report of a prospective study. Arch Gen Psychiatry 1983;40(3):249-57.

7. Packman WL, Pennuto TO, Bongar B, Orthwein J. Legal issues of professional negligence in suicide cases. Behav Sci Law 2004;22:697-713.

8. Simon RI. The suicidal patient. In: Lifson LE, Simon RI, eds. The mental health practitioner and the law: a comprehensive handbook. Cambridge, MA: Harvard University Press; 1998:166-86.

9. Maunz v. Perales, 276 Kan. 313, 76 P.3d 1027 (Kan 2003).

References

1. American Medical Association Code of Medical Ethics, Opinion 8.115.

2. Knapp v. Eppright, 783 SW2d 293 (Tex 1989).

3. Saunders v. Tisher (Maine Sup. Jud. Ct. 2006).

4. Physicians Risk Management Update. The physician-patient relationship: when does it begin? Available at: http://www.phyins.com/pi/risk/updates/mayjun04.html. Accessed December 28, 2006.

5. American Psychiatric Association. Principles of medical ethics with annotations especially applicable to psychiatry. Washington, DC; 2006. Available at: http://www.psych.org/psych_pract/ethics/ppaethics.cfm. Accessed December 28, 2006.

6. Pokorny A. Prediction of suicide in psychiatric patients. Report of a prospective study. Arch Gen Psychiatry 1983;40(3):249-57.

7. Packman WL, Pennuto TO, Bongar B, Orthwein J. Legal issues of professional negligence in suicide cases. Behav Sci Law 2004;22:697-713.

8. Simon RI. The suicidal patient. In: Lifson LE, Simon RI, eds. The mental health practitioner and the law: a comprehensive handbook. Cambridge, MA: Harvard University Press; 1998:166-86.

9. Maunz v. Perales, 276 Kan. 313, 76 P.3d 1027 (Kan 2003).

Issue
Current Psychiatry - 06(02)
Issue
Current Psychiatry - 06(02)
Page Number
48-57
Page Number
48-57
Publications
Publications
Article Type
Display Headline
Limits of care: What events can you prevent?
Display Headline
Limits of care: What events can you prevent?
Legacy Keywords
malpractice; malpractice verdicts; liability; medicolegal issues; malpractice lawsuits; medical malpractice; negligence; documentation; suicidality; suicide risk; patient death; patient injury; psychiatric verdicts; psychiatry verdicts; assessing suicidal thinking; assessing suicidality; prescription negligence; prescription liability; doctor-patient relationship; breach of duty; duty of care; ethical prescribing; oxycodone; limits of care; Jon E. Grant; Jon Grant; Grant JE; Grant J
Legacy Keywords
malpractice; malpractice verdicts; liability; medicolegal issues; malpractice lawsuits; medical malpractice; negligence; documentation; suicidality; suicide risk; patient death; patient injury; psychiatric verdicts; psychiatry verdicts; assessing suicidal thinking; assessing suicidality; prescription negligence; prescription liability; doctor-patient relationship; breach of duty; duty of care; ethical prescribing; oxycodone; limits of care; Jon E. Grant; Jon Grant; Grant JE; Grant J
Sections
Article Source

PURLs Copyright

Inside the Article

Article PDF Media

Clarification

Article Type
Changed
Fri, 01/11/2019 - 10:06
Display Headline
Clarification

The method for skin grafting surgical defects of the nasal alar region known as the drumhead graft was invented and developed by Dr. J. Michael Wentzell of Billings, Mont. ('Drumhead' Technique May Spare Alar Graft Depressions, SKIN & ALLERGY NEWS, January 2007, p. 32). Dr. Bradley K. Draper of Billings presented Dr. Wentzell's technique at the annual meeting of the American Society for Dermatologic Surgery.

Article PDF
Author and Disclosure Information

Publications
Topics
Author and Disclosure Information

Author and Disclosure Information

Article PDF
Article PDF

The method for skin grafting surgical defects of the nasal alar region known as the drumhead graft was invented and developed by Dr. J. Michael Wentzell of Billings, Mont. ('Drumhead' Technique May Spare Alar Graft Depressions, SKIN & ALLERGY NEWS, January 2007, p. 32). Dr. Bradley K. Draper of Billings presented Dr. Wentzell's technique at the annual meeting of the American Society for Dermatologic Surgery.

The method for skin grafting surgical defects of the nasal alar region known as the drumhead graft was invented and developed by Dr. J. Michael Wentzell of Billings, Mont. ('Drumhead' Technique May Spare Alar Graft Depressions, SKIN & ALLERGY NEWS, January 2007, p. 32). Dr. Bradley K. Draper of Billings presented Dr. Wentzell's technique at the annual meeting of the American Society for Dermatologic Surgery.

Publications
Publications
Topics
Article Type
Display Headline
Clarification
Display Headline
Clarification
Article Source

PURLs Copyright

Inside the Article

Article PDF Media

Brief Report / Krinsley

Article Type
Changed
Mon, 01/02/2017 - 19:34
Display Headline
Translating evidence into practice in managing inpatient hyperglycemia

The last 15 years have brought reports in the medical literature of exciting advances in describing the relationship between hyperglycemia and adverse outcomes in a variety of clinical contexts involving acutely ill patients.19 Hyperglycemia in hospitalized patients was long thought to be an adaptive mechanism and, at least in the intensive care setting, was rarely treated below threshold values of 225‐250 mg/dL. The pioneering work of Furnary et al. and the Portland Diabetic Project was the first to demonstrate that close monitoring and treatment of hyperglycemia in diabetic patients undergoing cardiovascular surgery decreased the occurrence of deep sternal wound infections, a dreaded postoperative complication.10 A second publication documented the steady decrease in mortality among these patients over the years as the group's glycemic target was steadily lowered.11 In the last several years the mortality rate of diabetic patients undergoing cardiovascular surgery has decreased so that it now approximates that of nondiabetics, eliminating the diabetic disadvantage. This work set the stage for the landmark Leuven study, performed at Catholic University in Belgium and published by Van den Berghe's group in 2001.12 This prospective, randomized, controlled study involving 1548 mechanically ventilated patients in a surgical intensive care unit, 63% of whom had undergone cardiovascular surgery, compared the outcomes of patients treated with continuous intravenous insulin to achieve euglycemia (80‐110 mg/dL) to those of a control group that received treatment only when glucose level exceeded 210 mg/dL. The outcomes including a 37% reduction in hospital mortality in the treated group and a 40%‐50% reduction in numerous morbid conditions, including the need for renal replacement therapy, prolonged mechanical ventilation, prolonged antibiotic use, and critical illness polyneuropathy, that spawned a paradigm shift in ICU medicine. A large before‐and‐after study performed in a mixed medical‐surgical ICU of a university‐affiliated community hospital confirmed the mortality benefits of glycemic management, using a more modest target of 80‐140 mg/dL.13 Finally, a prospective, randomized, controlled trial in a medical ICU population by the Leuven investigators reported improvement in several morbidities and a mortality advantage from intensive glycemic control, targeting 80‐100 mg/dL, among patients with ICU stays longer than 3 days.14 Consequently, intensive glycemic management of critically ill patients is rapidly becoming a worldwide standard of care, presenting an array of challenges to clinicians involved in the care of these patients. This article presents an overview of the issues surrounding promulgation of protocols implementing tight glycemic control (TGC).

Building Blocks for Implementation of a Successful TGC Protocol

Data management tools

According to Curtis et al., A successful quality project requires transparent and informative data reporting. In the absence of timely and informative data reporting, interest wanes and projects lose momentum. On the other hand, actionable and interpretable data empower the ICU team, affirm that quality improvement efforts are making a difference, and increase the chances for sustainability.15

It is impossible to build a successful TGC program without proper data management tools. Conceptually, there are 2 levels of data reporting. At a minimum, an ICU must develop methods to demonstrate the effect of the protocol on glycemic levels. Optimally, there should also be a mechanism to report clinical and even financial outcomes resulting from the work. Quite simply, without ready access to these types of data it is unlikely that ICU cliniciansnurses, dieticians, and physicianswill continue to do the hard work necessary to allow a TGC program to achieve sustained success.

Examples of glycemic reports

Figure 1 shows a simple and powerful graphic used in the Stamford Hospital ICUthe mean monthly glucose value. This simple calculation does not account for severity of illness or prevalence of underlying diabetes, but it is readily understood and easy to create. The run chart below demonstrates the ICU's success in first implementing a treatment threshold of 140 mg/dL and, later, a treatment threshold of 125 mg/dL.

Figure 1
Monthly run chart of mean glucose levels.

Another tool used in the Stamford Hospital ICU is a histogram that shows the percentage of glucose values that fall within discrete increments. Figure 2 details the outcomes in 3 periods: pre‐TGC, glucose 140, and glucose 125. This type of display powerfully demonstrates how the TGC protocols resulted in a marked increase in euglycemic values and dramatically reduced marked hyperglycemia.

Figure 2
Histogram of distribution of glucose values during historic era and two treatment eras.

The ability to capture useful sorts of data like these requires the assistance of the hospital's information technology department to create a link from the laboratory database to a data repository that the ICU's glycemic champion can regularly access and that displays the data in graphic form. Purchasing a point‐of‐care data management application provides an alternative solution. These applications can provide detailed reports on a unit's glycemic control, such as those displayed in Figures 1 and 2; some also have the capacity to delineate data by unit, individual practitioner, and patient.

Outcome data

The facility of an ICU to report data on glycemic control in a timely manner fulfills the minimum data requirement for successful implementation of a TGC protocol. However, sustained success depends on the unit's capacity to report information on relevant outcomes. It is not enough for an ICU director to be able to tell the hospital administration that the mean glucose level has decreased, from 160 to 135 mg/dL, for example, 6 months after institution of such a labor‐intensive program. The more relevant information is whether this intervention has had an effect on severity‐adjusted mortality, length of stay, and important comorbid conditions such as ICU‐acquired infections.

With innumerable measures that an ICU nursing or medical director might want to track, how should the measures to use be chosen?

A data set for a beginner might include the following parameters: demographics, including age, sex, and, possibly, ethnicity; admission and discharge dates and times; length of stay (LOS), ideally measured in exact time rather than number of calendar days; diagnosis; and ICU and hospital survival. The ICU data manager must develop a system to validate each patient's final discharge status from the hospital; some patients survive the ICU stay but die before hospital discharge, which therefore affects the ICU's hospital mortality rate.

The intermediate level of outcome reporting might include 2 additional elements: severity scoring and detailed information about episodes of mechanical ventilation. The most widely used models for scoring the severity of illness of ICU patients include the Acute Physiology and Chronic Health Evaluation (APACHE), the Simplified Acute Physiology Score (SAPS), and the Mortality Prediction Model (MPM).1620 The APACHE II system is the most widely quoted in the medical literature but is based on a validation cohort more than 25 years old.16 The scoring algorithms for APACHE III and APACHE IV have been released on the Web; the most recent iteration, APACHE IV, was developed using data from more than 100,000 admissions to a variety of types of ICUs between January 1, 2002, and December 31, 2003, and also includes predictions for ICU LOS.18 Use of these tools allows the ICU clinician to benchmark the unit's performance against this large heterogeneous group of ICU patients treated using contemporary ICU practice patterns. Important features of mechanical ventilation episodes worth tracking include: time of start and finish of each episode (to calculate ventilator LOS); whether the patient had an unplanned extubation; the percentage of patients who required reintubation after planned extubation; tracheostomy rate; and the use of continuous intravenous sedatives or paralytics.

An advanced data outcome system would be linked to various hospital data silos, allowing capture of all laboratory, pharmacy, and radiology charges into the ICU database, allowing financial analysis of ICU performance. Another link would funnel all important laboratory results into the database. Additional types of useful data include: ultimate discharge status of the patient (eg, home, skilled nursing facility, rehabilitation facility, another acute care hospital); procedures done in the ICU; infections acquired in the ICU; and comorbidities based on ICD‐9 codes. Several examples of the output possible with the use of the advanced data outcome system developed for use in the Stamford Hospital ICU are reported later in this article.

Protocol‐driven collaborative culture

Successful implementation of TGC is most likely in an environment that embraces standardized care using evidence‐based best practices. All routine aspects of care in the Stamford Hospital ICU are protocol driven. Some examples include deep‐vein thrombosis prophylaxis, stress ulcer prophylaxis, ventilator weaning, ventilator sedation, enteral nutrition, and potassium, phosphate, and magnesium repletion. These protocols were all in place when discussions began in the ICU about how to create a TGC protocol. The nurses were comfortable using protocols, and there were no longer any counterproductive arguments about physician autonomy of treatment decisions centered on these basic care issues. These factors facilitated adoption of the TGC protocol. Finally, the strength of the relationship binding the nursing and medical leadership of the ICU was fundamental to the program's success. A complex initiative such as TGC mandates that these parties share the same vision for the ICU.

Overcoming resistance

Adoption of TGC by an ICU will undoubtedly encounter resistance from the staff. The factors responsible for this are very real. An understanding and patient attitude by the unit's leadership will greatly facilitate implementation. Factors that are the basis for this resistance in part include:

  • TGC represents a fundamental paradigm shift in ICU care. Until recently, hyperglycemia, even at levels as high as 200‐250 mg/dL, has until recently been tolerated and ignored, as it has been considered a normal adaptive response to acute and severe illness.

  • Doing TGC correctly is hard work. This work includes the logistics of monitoring, explaining to families and patients the reasons for frequent finger sticks or blood testing (But Grandma isn't even a diabetic), being aware of the potential for significant discomfort to the patient, and having to make treatment decisions in response to all the newly acquired data.

  • Fear of hypoglycemia. Nurses want to protect, and not hurt, their patients. Insulin therapy, especially when targeting euglycemia or near‐euglycemia, is potentially dangerous.

An effective educational program directed to the staff, including nurses, staff physicians, and pharmacists, will help surmount this resistance. The components of this educational program should include: the basis in the medical literature for instituting intensive programs to monitor and treat patient glycemic levels; a review of the insulin formulations (subcutaneous, intravenous, long acting, and short acting) with emphasis on the different pharmacokinetic implications underlying their use; and a detailed analysis of factors associated with hypoglycemia.21, 22

Specific Issues Regarding TGC Implementation

Setting the glycemic target

What is the correct glycemic target? Van den Berghe et al. used a treatment threshold of 110 mg/dL for both her surgical ICU and medical ICU studies. The Stamford Hospital ICU trial, with a mixed population of medical, surgical, and cardiac patients, targeted 140 mg/dL.13

A detailed review of a very large cohort of patients treated in the Stamford Hospital ICU suggests that patients who achieve low euglycemia have the best survival (see Fig. 3). This analysis used APACHE methodology to analyze expected and actual mortality in relation to each patient's mean glucose during the ICU stay. The APACHE III and IV mortality prediction models use age, presence or absence of a group of important comorbidities, admitting diagnosis to the ICU, length of time in the ICU before ICU admission, location of the patient prior to ICU admission, and the most abnormal values of a large group of physiological parameters during the first 24 hours of ICU admission to derive a discrete prediction of hospital mortality for that patient. A standardized mortality ratio (SMR) can be calculated by dividing the patients' actual hospital mortality rate by the mean of all the individual predictions of mortality (SMR = actual/predicted mortality). A value less than 1 suggests that the patients in the observed cohort had a lower mortality rate than that predicted by the model.

Figure 3
Standardized mortality ratio related to mean glucose level during ICU stay.

Patients who achieved euglycemia (<110 mg/dL) in the surgical ICU study of Van den Berghe et al. also had the lowest mortality rates as well as the lowest incidence of the various comorbidities measured compared to those with intermediate blood glucose levels (110‐150 mg/dL). Those with the worst glycemic control (blood glucose > 150 mg/dL) had the highest mortality rate and the highest incidence of various serious comorbid conditions.23

Although available data support a euglycemic target, is this unequivocally the correct target for an ICU beginning TGC implementation? Not necessarily. Targeting 110 mg/dL requires an intensity of treatment that may be intimidating to an ICU staff, especially one without experience managing protocols. Moreover, the lower the glycemic target, the greater the risk for iatrogenic hypoglycemia. An ICU considering implementation of a TGC protocol might consider staged adoption. The initial target might be as high as 175 mg/dL. As the clinicians gain experience using the protocol, including acquiring and reporting data, the treatment threshold could be lowered. The Stamford Hospital ICU staff, with more than 5 years of experience developing a model of standardized care using evidence‐based best‐practice patient care protocols, spent several months arguing about the glycemic target when TGC was first discussed following publication of the initial Van den Berghe study.12 The director of Critical Care wanted to replicate Van den Berghe's work and urged a target of 110 mg/dL. The nurses refused. A compromise was reached: a 140 mg/dL treatment threshold. This confirms an important lesson: the ICU team must choose an achievable goal. It is noteworthy that after 2 years of successful use of the glucose 140 protocol, the Stamford Hospital ICU nurses initiated a revision of the protocol, deciding they wanted to target 125 mg/dL. Figure 4 illustrates the glycemic and mortality results comparing the last 3 years before TGC with the glucose 140 and glucose 125 periods.

Figure 4
Mortality rate and mean glucose levels of patients admitted to Stamford Hospital ICU during three years of the historic era and the two treatment eras.

Choosing a protocol

After choosing a glycemic target, the ICU leadership must agree on a protocol to achieve the objective. TGC protocols can be broadly characterized as directive or nondirective.

The Stamford Hospital ICU TGC protocol is an example of a nondirective protocol.13 The nursing staff considers the document a starting point for therapy decisions. Many patients receive insulin dosing at variance with the guidelines established by the document. A nurse is empowered to make these treatment decisions. This is not dissimilar to the process ICU nurses use when titrating a vasopressor to achieve a targeted goal for mean arterial pressure. Nondirective protocols are most suitable for ICU staffs that have had considerable prior experience using nurse‐driven protocols in an environment that supports and accepts standardized care.

A number of directive protocols have been published in the literature.24 Their unifying feature is the goal of prescribing a specific insulin dose for each set of circumstances a nurse may encounter. The patient's previous glucose level and the rate of change in glucose level are considered, and the document typically details the choices for insulin dosing in several columns based on the patient's previously documented sensitivity to insulin. Although this sort of protocol can be helpful in providing explicit guidance with insulin dosing, its complexity may impede adoption.

Another option is the use of tools that have been developed to assist an ICU in initiating and promulgating TGC protocols, including software applications that automatically calculate insulin dosing. Finally, work has been initiated on the development of monitors that provide near‐continuous monitoring of glucose levels at bedside.25, 26 Adoption of such monitoring will facilitate the implementation of TGC protocols because of its impact on eliminating the workflow burdens of intensive glycemic monitoring as well as markedly diminishing the risk of hypoglycemia.

Hypoglycemia

In the Van den Berghe et al. surgical ICU study, severe hypoglycemia, defined as a glucose level less than 40 mg/dL, occurred at least once among 5.1% of the patients in the intensively treated group versus in 0.8% of the patients in the conventionally treated group.12 The hypoglycemia was described as transient, a result of the frequency of monitoring during the study, and was not associated with overt adverse consequences. The incidence of severe hypoglycemia (<40 mg/dL) was described differently in the Stamford Hospital trial: 0.35% of all the values obtained during the baseline period, compared to 0.34% of those obtained during the treatment period, again without any overt adverse consequences.13 Nevertheless, it is not known with certainty whether having even a single episode of severe hypoglycemia independently contributes to the risk of mortality.

Vreisendorp recently identified a group of predisposing factors for the development of severe hypoglycemia among ICU patients undergoing TGC.21 The most important include: a decrease in the administration of nutrition without a concomitant change in insulin dosing; diabetes mellitus; insulin treatment; sepsis; inotropic support; and renal failure. The Stamford Hospital ICU TGC protocol document now includes a black box warning highlighting renal failure (associated with decreased clearance of administered insulin), hepatic failure, and sepsis (associated with decreased hepatic gluconeogenesis) as major risk factors for severe hypoglycemia. Ongoing reinforcement is necessary to encourage the ICU staff recognize these risk factors for severe hypoglycemia and respond by adopting more conservative insulin dosing and instituting more frequent glucose monitoring.

Economic Benefits of TGC

Recently published data support the economic benefits of intensive glycemic management. Van den Berghe et al. quantified costs attributable to ICU days, mechanical ventilation, and use of antibiotics, vasopressors, intotropic agents, and transfusions in the 2 treatment groups in their surgical ICU study. The savings per patient in the intensively treated group totaled $2638; mean LOS was 6.6 days.27, 28 Data from the Stamford Hospital ICU trial was analyzed differently, with quantification of all laboratory, pharmacy, and diagnostic imaging costs, as well as costs associated with ICU days, mechanical ventilation and days in the hospital after ICU discharge.29 The savings per patient in the intensively treated group totaled $1560. Notably, this occurred in the context of a much shorter LOS than that seen in the Belgian trial; mean and median LOS were only 3.4 and 1.7 days, respectively.

CONCLUSIONS

Intensive glycemic management of critically ill patients is emerging as a standard of care, based on data demonstrating its effectiveness in reducing mortality, morbidity, and costs. Intensive care unit staffs need to make important choices about the type of protocol most suitable for use, the glycemic target, and the mechanisms for avoiding hypoglycemia. The implementation of appropriate data management tools in a protocol‐driven environment that supports standardization of care will facilitate adoption of TGC.

References
  1. Nasraway SA.Hyperglycemia during critical illness.J Parenter Enteral Nutr.2006;30:254258.
  2. Capes SE,Hunt D,Malmberg K, et al.Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview.Lancet.2000;355:773778.
  3. Malmberg K.Prospective randomised study of intensive insulin treatment on long term survival after acute myocardial infarction in patients with diabetes mellitus.DIGAMI (Diabetes Mellitus, Insulin Glucose Infusion in Acute Myocardial Infarction) Study Group.BMJ.1997;314:15121515.
  4. Capes SE,Hunt D,Malmberg K, et al.Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview.Stroke.2001;32:24262432.
  5. Bruno A,Levine SR,Frankel MR, et al.Admission glucose level and clinical outcomes in the NINDS rt‐PA Stroke Trial.Neurology.2002;59:669674.
  6. Estrada CA,Young JA,Nifong LW, et al.Outcomes and perioperative hyperglycemia in patients with or without diabetes mellitus undergoing coronary artery bypass grafting.Ann Thorac Surg.2003;75:13921399.
  7. Yendamuri S,Fulda GJ,Tinkoff GH.Admission hyperglycemia as a prognostic indicator in trauma.J Trauma.2003;55:3338.
  8. Coursin DB,Connery LE,Ketzler JT.Perioperative diabetic and hyperglycemic management issues.Crit Care Med.2004;32:S116S125.
  9. Krinsley JS.Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.Mayo Clinic Proc.2003;78:14711478.
  10. Furnary AP,Zerr KJ,Grunkemeier GL, et al.Continuous intravenous insulin infusion reduces the incidence of deep sternal wound infection in diabetic patients after cardiac surgical procedures.Ann Thorac Surg.1999;67:352360.
  11. Furnary AP,Gao G,Grunkemeier GL, et al.Continuous insulin infusion reduces mortality in patients with diabetes undergoing coronary artery bypass grafting.J Thorac Cardiovasc Surg.2003;125:10071021.
  12. Van den Berghe G,Wouters P,Weekers F, et al.Intensive insulin therapy in the critically ill patients.N Engl J Med.2001;345:13591367.
  13. Krinsley JS.Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79:9921000.
  14. Van den Berghe G,Wilmer A,Hermans G, et al.Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354:449461.
  15. Curtis JR,Cook DF,Wall RJ, et al.Intensive care unit quality improvement: A “how‐to” guide for the interdisciplinary team.Crit Care Med.2006;34:211218.
  16. Knaus WA,Draper EA,Wagner DP, et al.APACHE II. A severity of disease classification system.Crit Care Med.1985;13:818829.
  17. Knaus WA,Wagner DP,Draper EA, et al.The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest.1991;100:16191636.
  18. http://www.cerner.com/public/Cerner_3.asp?id=3562. Accessed December 12,2006.
  19. Aegerter P,Boumendil A,Retbi A, et al.SAPS II revisited.Int Care Med.2005;31:416423.
  20. Lemeshow S,Teres D,Klar J, et al.Mortality probability models (MPM II) based on an international cohort of intensive care unit patients.JAMA.1993;270:247886.
  21. Vriesendorp TM,van Santen S,DeVries JH, et al.Predisposing factors for hypoglycemia in the intensive care unit.Crit Care Med.2006;34:96101.
  22. Vriesendorp TM,DeVries JH,van Santen S, et al.Evaluation of short‐term outcomes of hypoglycemia in the intensive care unit.Crit Care Med.2006;34:27141218.
  23. Van den Berghe G,Wouters PJ,Bouillon R, et al.Outcome benefit of intensive insulin therapy in the critically ill: Insulin dose versus glycemic control.Crit Care Med.2003;31:359366.
  24. http://www.glycemiccontrol.net/Published_Protocols.htm. Accessed December 12,2006.
  25. Krinsley JS,Hall D,Zheng P, et al.Validation of the OptiScanner, a new continuous glucose monitor.Crit Care Med.2005;33:S265.
  26. Krinsley JS,Zheng, P,Hall D, et al.ICU validation of the OptiScanner, a continuous glucose monitoring device.Crit Care Med.2006;34:A67.
  27. Van den Berghe G,Wouters P,Kesteloot K, et al.Analysis of healthcare resource utilization with intensive insulin therapy in critically ill patients.Crit Care Med.2006;34:612616.
  28. Krinsley JS.A simple intervention that saves lives and money.Crit Care Med.2006;34:896.
  29. Krinsley JS,Jones RL.Cost analysis of intensive glycemic control in critically ill adult patients.Chest.2006;129:644650.
Article PDF
Page Number
13-19
Sections
Article PDF
Article PDF

The last 15 years have brought reports in the medical literature of exciting advances in describing the relationship between hyperglycemia and adverse outcomes in a variety of clinical contexts involving acutely ill patients.19 Hyperglycemia in hospitalized patients was long thought to be an adaptive mechanism and, at least in the intensive care setting, was rarely treated below threshold values of 225‐250 mg/dL. The pioneering work of Furnary et al. and the Portland Diabetic Project was the first to demonstrate that close monitoring and treatment of hyperglycemia in diabetic patients undergoing cardiovascular surgery decreased the occurrence of deep sternal wound infections, a dreaded postoperative complication.10 A second publication documented the steady decrease in mortality among these patients over the years as the group's glycemic target was steadily lowered.11 In the last several years the mortality rate of diabetic patients undergoing cardiovascular surgery has decreased so that it now approximates that of nondiabetics, eliminating the diabetic disadvantage. This work set the stage for the landmark Leuven study, performed at Catholic University in Belgium and published by Van den Berghe's group in 2001.12 This prospective, randomized, controlled study involving 1548 mechanically ventilated patients in a surgical intensive care unit, 63% of whom had undergone cardiovascular surgery, compared the outcomes of patients treated with continuous intravenous insulin to achieve euglycemia (80‐110 mg/dL) to those of a control group that received treatment only when glucose level exceeded 210 mg/dL. The outcomes including a 37% reduction in hospital mortality in the treated group and a 40%‐50% reduction in numerous morbid conditions, including the need for renal replacement therapy, prolonged mechanical ventilation, prolonged antibiotic use, and critical illness polyneuropathy, that spawned a paradigm shift in ICU medicine. A large before‐and‐after study performed in a mixed medical‐surgical ICU of a university‐affiliated community hospital confirmed the mortality benefits of glycemic management, using a more modest target of 80‐140 mg/dL.13 Finally, a prospective, randomized, controlled trial in a medical ICU population by the Leuven investigators reported improvement in several morbidities and a mortality advantage from intensive glycemic control, targeting 80‐100 mg/dL, among patients with ICU stays longer than 3 days.14 Consequently, intensive glycemic management of critically ill patients is rapidly becoming a worldwide standard of care, presenting an array of challenges to clinicians involved in the care of these patients. This article presents an overview of the issues surrounding promulgation of protocols implementing tight glycemic control (TGC).

Building Blocks for Implementation of a Successful TGC Protocol

Data management tools

According to Curtis et al., A successful quality project requires transparent and informative data reporting. In the absence of timely and informative data reporting, interest wanes and projects lose momentum. On the other hand, actionable and interpretable data empower the ICU team, affirm that quality improvement efforts are making a difference, and increase the chances for sustainability.15

It is impossible to build a successful TGC program without proper data management tools. Conceptually, there are 2 levels of data reporting. At a minimum, an ICU must develop methods to demonstrate the effect of the protocol on glycemic levels. Optimally, there should also be a mechanism to report clinical and even financial outcomes resulting from the work. Quite simply, without ready access to these types of data it is unlikely that ICU cliniciansnurses, dieticians, and physicianswill continue to do the hard work necessary to allow a TGC program to achieve sustained success.

Examples of glycemic reports

Figure 1 shows a simple and powerful graphic used in the Stamford Hospital ICUthe mean monthly glucose value. This simple calculation does not account for severity of illness or prevalence of underlying diabetes, but it is readily understood and easy to create. The run chart below demonstrates the ICU's success in first implementing a treatment threshold of 140 mg/dL and, later, a treatment threshold of 125 mg/dL.

Figure 1
Monthly run chart of mean glucose levels.

Another tool used in the Stamford Hospital ICU is a histogram that shows the percentage of glucose values that fall within discrete increments. Figure 2 details the outcomes in 3 periods: pre‐TGC, glucose 140, and glucose 125. This type of display powerfully demonstrates how the TGC protocols resulted in a marked increase in euglycemic values and dramatically reduced marked hyperglycemia.

Figure 2
Histogram of distribution of glucose values during historic era and two treatment eras.

The ability to capture useful sorts of data like these requires the assistance of the hospital's information technology department to create a link from the laboratory database to a data repository that the ICU's glycemic champion can regularly access and that displays the data in graphic form. Purchasing a point‐of‐care data management application provides an alternative solution. These applications can provide detailed reports on a unit's glycemic control, such as those displayed in Figures 1 and 2; some also have the capacity to delineate data by unit, individual practitioner, and patient.

Outcome data

The facility of an ICU to report data on glycemic control in a timely manner fulfills the minimum data requirement for successful implementation of a TGC protocol. However, sustained success depends on the unit's capacity to report information on relevant outcomes. It is not enough for an ICU director to be able to tell the hospital administration that the mean glucose level has decreased, from 160 to 135 mg/dL, for example, 6 months after institution of such a labor‐intensive program. The more relevant information is whether this intervention has had an effect on severity‐adjusted mortality, length of stay, and important comorbid conditions such as ICU‐acquired infections.

With innumerable measures that an ICU nursing or medical director might want to track, how should the measures to use be chosen?

A data set for a beginner might include the following parameters: demographics, including age, sex, and, possibly, ethnicity; admission and discharge dates and times; length of stay (LOS), ideally measured in exact time rather than number of calendar days; diagnosis; and ICU and hospital survival. The ICU data manager must develop a system to validate each patient's final discharge status from the hospital; some patients survive the ICU stay but die before hospital discharge, which therefore affects the ICU's hospital mortality rate.

The intermediate level of outcome reporting might include 2 additional elements: severity scoring and detailed information about episodes of mechanical ventilation. The most widely used models for scoring the severity of illness of ICU patients include the Acute Physiology and Chronic Health Evaluation (APACHE), the Simplified Acute Physiology Score (SAPS), and the Mortality Prediction Model (MPM).1620 The APACHE II system is the most widely quoted in the medical literature but is based on a validation cohort more than 25 years old.16 The scoring algorithms for APACHE III and APACHE IV have been released on the Web; the most recent iteration, APACHE IV, was developed using data from more than 100,000 admissions to a variety of types of ICUs between January 1, 2002, and December 31, 2003, and also includes predictions for ICU LOS.18 Use of these tools allows the ICU clinician to benchmark the unit's performance against this large heterogeneous group of ICU patients treated using contemporary ICU practice patterns. Important features of mechanical ventilation episodes worth tracking include: time of start and finish of each episode (to calculate ventilator LOS); whether the patient had an unplanned extubation; the percentage of patients who required reintubation after planned extubation; tracheostomy rate; and the use of continuous intravenous sedatives or paralytics.

An advanced data outcome system would be linked to various hospital data silos, allowing capture of all laboratory, pharmacy, and radiology charges into the ICU database, allowing financial analysis of ICU performance. Another link would funnel all important laboratory results into the database. Additional types of useful data include: ultimate discharge status of the patient (eg, home, skilled nursing facility, rehabilitation facility, another acute care hospital); procedures done in the ICU; infections acquired in the ICU; and comorbidities based on ICD‐9 codes. Several examples of the output possible with the use of the advanced data outcome system developed for use in the Stamford Hospital ICU are reported later in this article.

Protocol‐driven collaborative culture

Successful implementation of TGC is most likely in an environment that embraces standardized care using evidence‐based best practices. All routine aspects of care in the Stamford Hospital ICU are protocol driven. Some examples include deep‐vein thrombosis prophylaxis, stress ulcer prophylaxis, ventilator weaning, ventilator sedation, enteral nutrition, and potassium, phosphate, and magnesium repletion. These protocols were all in place when discussions began in the ICU about how to create a TGC protocol. The nurses were comfortable using protocols, and there were no longer any counterproductive arguments about physician autonomy of treatment decisions centered on these basic care issues. These factors facilitated adoption of the TGC protocol. Finally, the strength of the relationship binding the nursing and medical leadership of the ICU was fundamental to the program's success. A complex initiative such as TGC mandates that these parties share the same vision for the ICU.

Overcoming resistance

Adoption of TGC by an ICU will undoubtedly encounter resistance from the staff. The factors responsible for this are very real. An understanding and patient attitude by the unit's leadership will greatly facilitate implementation. Factors that are the basis for this resistance in part include:

  • TGC represents a fundamental paradigm shift in ICU care. Until recently, hyperglycemia, even at levels as high as 200‐250 mg/dL, has until recently been tolerated and ignored, as it has been considered a normal adaptive response to acute and severe illness.

  • Doing TGC correctly is hard work. This work includes the logistics of monitoring, explaining to families and patients the reasons for frequent finger sticks or blood testing (But Grandma isn't even a diabetic), being aware of the potential for significant discomfort to the patient, and having to make treatment decisions in response to all the newly acquired data.

  • Fear of hypoglycemia. Nurses want to protect, and not hurt, their patients. Insulin therapy, especially when targeting euglycemia or near‐euglycemia, is potentially dangerous.

An effective educational program directed to the staff, including nurses, staff physicians, and pharmacists, will help surmount this resistance. The components of this educational program should include: the basis in the medical literature for instituting intensive programs to monitor and treat patient glycemic levels; a review of the insulin formulations (subcutaneous, intravenous, long acting, and short acting) with emphasis on the different pharmacokinetic implications underlying their use; and a detailed analysis of factors associated with hypoglycemia.21, 22

Specific Issues Regarding TGC Implementation

Setting the glycemic target

What is the correct glycemic target? Van den Berghe et al. used a treatment threshold of 110 mg/dL for both her surgical ICU and medical ICU studies. The Stamford Hospital ICU trial, with a mixed population of medical, surgical, and cardiac patients, targeted 140 mg/dL.13

A detailed review of a very large cohort of patients treated in the Stamford Hospital ICU suggests that patients who achieve low euglycemia have the best survival (see Fig. 3). This analysis used APACHE methodology to analyze expected and actual mortality in relation to each patient's mean glucose during the ICU stay. The APACHE III and IV mortality prediction models use age, presence or absence of a group of important comorbidities, admitting diagnosis to the ICU, length of time in the ICU before ICU admission, location of the patient prior to ICU admission, and the most abnormal values of a large group of physiological parameters during the first 24 hours of ICU admission to derive a discrete prediction of hospital mortality for that patient. A standardized mortality ratio (SMR) can be calculated by dividing the patients' actual hospital mortality rate by the mean of all the individual predictions of mortality (SMR = actual/predicted mortality). A value less than 1 suggests that the patients in the observed cohort had a lower mortality rate than that predicted by the model.

Figure 3
Standardized mortality ratio related to mean glucose level during ICU stay.

Patients who achieved euglycemia (<110 mg/dL) in the surgical ICU study of Van den Berghe et al. also had the lowest mortality rates as well as the lowest incidence of the various comorbidities measured compared to those with intermediate blood glucose levels (110‐150 mg/dL). Those with the worst glycemic control (blood glucose > 150 mg/dL) had the highest mortality rate and the highest incidence of various serious comorbid conditions.23

Although available data support a euglycemic target, is this unequivocally the correct target for an ICU beginning TGC implementation? Not necessarily. Targeting 110 mg/dL requires an intensity of treatment that may be intimidating to an ICU staff, especially one without experience managing protocols. Moreover, the lower the glycemic target, the greater the risk for iatrogenic hypoglycemia. An ICU considering implementation of a TGC protocol might consider staged adoption. The initial target might be as high as 175 mg/dL. As the clinicians gain experience using the protocol, including acquiring and reporting data, the treatment threshold could be lowered. The Stamford Hospital ICU staff, with more than 5 years of experience developing a model of standardized care using evidence‐based best‐practice patient care protocols, spent several months arguing about the glycemic target when TGC was first discussed following publication of the initial Van den Berghe study.12 The director of Critical Care wanted to replicate Van den Berghe's work and urged a target of 110 mg/dL. The nurses refused. A compromise was reached: a 140 mg/dL treatment threshold. This confirms an important lesson: the ICU team must choose an achievable goal. It is noteworthy that after 2 years of successful use of the glucose 140 protocol, the Stamford Hospital ICU nurses initiated a revision of the protocol, deciding they wanted to target 125 mg/dL. Figure 4 illustrates the glycemic and mortality results comparing the last 3 years before TGC with the glucose 140 and glucose 125 periods.

Figure 4
Mortality rate and mean glucose levels of patients admitted to Stamford Hospital ICU during three years of the historic era and the two treatment eras.

Choosing a protocol

After choosing a glycemic target, the ICU leadership must agree on a protocol to achieve the objective. TGC protocols can be broadly characterized as directive or nondirective.

The Stamford Hospital ICU TGC protocol is an example of a nondirective protocol.13 The nursing staff considers the document a starting point for therapy decisions. Many patients receive insulin dosing at variance with the guidelines established by the document. A nurse is empowered to make these treatment decisions. This is not dissimilar to the process ICU nurses use when titrating a vasopressor to achieve a targeted goal for mean arterial pressure. Nondirective protocols are most suitable for ICU staffs that have had considerable prior experience using nurse‐driven protocols in an environment that supports and accepts standardized care.

A number of directive protocols have been published in the literature.24 Their unifying feature is the goal of prescribing a specific insulin dose for each set of circumstances a nurse may encounter. The patient's previous glucose level and the rate of change in glucose level are considered, and the document typically details the choices for insulin dosing in several columns based on the patient's previously documented sensitivity to insulin. Although this sort of protocol can be helpful in providing explicit guidance with insulin dosing, its complexity may impede adoption.

Another option is the use of tools that have been developed to assist an ICU in initiating and promulgating TGC protocols, including software applications that automatically calculate insulin dosing. Finally, work has been initiated on the development of monitors that provide near‐continuous monitoring of glucose levels at bedside.25, 26 Adoption of such monitoring will facilitate the implementation of TGC protocols because of its impact on eliminating the workflow burdens of intensive glycemic monitoring as well as markedly diminishing the risk of hypoglycemia.

Hypoglycemia

In the Van den Berghe et al. surgical ICU study, severe hypoglycemia, defined as a glucose level less than 40 mg/dL, occurred at least once among 5.1% of the patients in the intensively treated group versus in 0.8% of the patients in the conventionally treated group.12 The hypoglycemia was described as transient, a result of the frequency of monitoring during the study, and was not associated with overt adverse consequences. The incidence of severe hypoglycemia (<40 mg/dL) was described differently in the Stamford Hospital trial: 0.35% of all the values obtained during the baseline period, compared to 0.34% of those obtained during the treatment period, again without any overt adverse consequences.13 Nevertheless, it is not known with certainty whether having even a single episode of severe hypoglycemia independently contributes to the risk of mortality.

Vreisendorp recently identified a group of predisposing factors for the development of severe hypoglycemia among ICU patients undergoing TGC.21 The most important include: a decrease in the administration of nutrition without a concomitant change in insulin dosing; diabetes mellitus; insulin treatment; sepsis; inotropic support; and renal failure. The Stamford Hospital ICU TGC protocol document now includes a black box warning highlighting renal failure (associated with decreased clearance of administered insulin), hepatic failure, and sepsis (associated with decreased hepatic gluconeogenesis) as major risk factors for severe hypoglycemia. Ongoing reinforcement is necessary to encourage the ICU staff recognize these risk factors for severe hypoglycemia and respond by adopting more conservative insulin dosing and instituting more frequent glucose monitoring.

Economic Benefits of TGC

Recently published data support the economic benefits of intensive glycemic management. Van den Berghe et al. quantified costs attributable to ICU days, mechanical ventilation, and use of antibiotics, vasopressors, intotropic agents, and transfusions in the 2 treatment groups in their surgical ICU study. The savings per patient in the intensively treated group totaled $2638; mean LOS was 6.6 days.27, 28 Data from the Stamford Hospital ICU trial was analyzed differently, with quantification of all laboratory, pharmacy, and diagnostic imaging costs, as well as costs associated with ICU days, mechanical ventilation and days in the hospital after ICU discharge.29 The savings per patient in the intensively treated group totaled $1560. Notably, this occurred in the context of a much shorter LOS than that seen in the Belgian trial; mean and median LOS were only 3.4 and 1.7 days, respectively.

CONCLUSIONS

Intensive glycemic management of critically ill patients is emerging as a standard of care, based on data demonstrating its effectiveness in reducing mortality, morbidity, and costs. Intensive care unit staffs need to make important choices about the type of protocol most suitable for use, the glycemic target, and the mechanisms for avoiding hypoglycemia. The implementation of appropriate data management tools in a protocol‐driven environment that supports standardization of care will facilitate adoption of TGC.

The last 15 years have brought reports in the medical literature of exciting advances in describing the relationship between hyperglycemia and adverse outcomes in a variety of clinical contexts involving acutely ill patients.19 Hyperglycemia in hospitalized patients was long thought to be an adaptive mechanism and, at least in the intensive care setting, was rarely treated below threshold values of 225‐250 mg/dL. The pioneering work of Furnary et al. and the Portland Diabetic Project was the first to demonstrate that close monitoring and treatment of hyperglycemia in diabetic patients undergoing cardiovascular surgery decreased the occurrence of deep sternal wound infections, a dreaded postoperative complication.10 A second publication documented the steady decrease in mortality among these patients over the years as the group's glycemic target was steadily lowered.11 In the last several years the mortality rate of diabetic patients undergoing cardiovascular surgery has decreased so that it now approximates that of nondiabetics, eliminating the diabetic disadvantage. This work set the stage for the landmark Leuven study, performed at Catholic University in Belgium and published by Van den Berghe's group in 2001.12 This prospective, randomized, controlled study involving 1548 mechanically ventilated patients in a surgical intensive care unit, 63% of whom had undergone cardiovascular surgery, compared the outcomes of patients treated with continuous intravenous insulin to achieve euglycemia (80‐110 mg/dL) to those of a control group that received treatment only when glucose level exceeded 210 mg/dL. The outcomes including a 37% reduction in hospital mortality in the treated group and a 40%‐50% reduction in numerous morbid conditions, including the need for renal replacement therapy, prolonged mechanical ventilation, prolonged antibiotic use, and critical illness polyneuropathy, that spawned a paradigm shift in ICU medicine. A large before‐and‐after study performed in a mixed medical‐surgical ICU of a university‐affiliated community hospital confirmed the mortality benefits of glycemic management, using a more modest target of 80‐140 mg/dL.13 Finally, a prospective, randomized, controlled trial in a medical ICU population by the Leuven investigators reported improvement in several morbidities and a mortality advantage from intensive glycemic control, targeting 80‐100 mg/dL, among patients with ICU stays longer than 3 days.14 Consequently, intensive glycemic management of critically ill patients is rapidly becoming a worldwide standard of care, presenting an array of challenges to clinicians involved in the care of these patients. This article presents an overview of the issues surrounding promulgation of protocols implementing tight glycemic control (TGC).

Building Blocks for Implementation of a Successful TGC Protocol

Data management tools

According to Curtis et al., A successful quality project requires transparent and informative data reporting. In the absence of timely and informative data reporting, interest wanes and projects lose momentum. On the other hand, actionable and interpretable data empower the ICU team, affirm that quality improvement efforts are making a difference, and increase the chances for sustainability.15

It is impossible to build a successful TGC program without proper data management tools. Conceptually, there are 2 levels of data reporting. At a minimum, an ICU must develop methods to demonstrate the effect of the protocol on glycemic levels. Optimally, there should also be a mechanism to report clinical and even financial outcomes resulting from the work. Quite simply, without ready access to these types of data it is unlikely that ICU cliniciansnurses, dieticians, and physicianswill continue to do the hard work necessary to allow a TGC program to achieve sustained success.

Examples of glycemic reports

Figure 1 shows a simple and powerful graphic used in the Stamford Hospital ICUthe mean monthly glucose value. This simple calculation does not account for severity of illness or prevalence of underlying diabetes, but it is readily understood and easy to create. The run chart below demonstrates the ICU's success in first implementing a treatment threshold of 140 mg/dL and, later, a treatment threshold of 125 mg/dL.

Figure 1
Monthly run chart of mean glucose levels.

Another tool used in the Stamford Hospital ICU is a histogram that shows the percentage of glucose values that fall within discrete increments. Figure 2 details the outcomes in 3 periods: pre‐TGC, glucose 140, and glucose 125. This type of display powerfully demonstrates how the TGC protocols resulted in a marked increase in euglycemic values and dramatically reduced marked hyperglycemia.

Figure 2
Histogram of distribution of glucose values during historic era and two treatment eras.

The ability to capture useful sorts of data like these requires the assistance of the hospital's information technology department to create a link from the laboratory database to a data repository that the ICU's glycemic champion can regularly access and that displays the data in graphic form. Purchasing a point‐of‐care data management application provides an alternative solution. These applications can provide detailed reports on a unit's glycemic control, such as those displayed in Figures 1 and 2; some also have the capacity to delineate data by unit, individual practitioner, and patient.

Outcome data

The facility of an ICU to report data on glycemic control in a timely manner fulfills the minimum data requirement for successful implementation of a TGC protocol. However, sustained success depends on the unit's capacity to report information on relevant outcomes. It is not enough for an ICU director to be able to tell the hospital administration that the mean glucose level has decreased, from 160 to 135 mg/dL, for example, 6 months after institution of such a labor‐intensive program. The more relevant information is whether this intervention has had an effect on severity‐adjusted mortality, length of stay, and important comorbid conditions such as ICU‐acquired infections.

With innumerable measures that an ICU nursing or medical director might want to track, how should the measures to use be chosen?

A data set for a beginner might include the following parameters: demographics, including age, sex, and, possibly, ethnicity; admission and discharge dates and times; length of stay (LOS), ideally measured in exact time rather than number of calendar days; diagnosis; and ICU and hospital survival. The ICU data manager must develop a system to validate each patient's final discharge status from the hospital; some patients survive the ICU stay but die before hospital discharge, which therefore affects the ICU's hospital mortality rate.

The intermediate level of outcome reporting might include 2 additional elements: severity scoring and detailed information about episodes of mechanical ventilation. The most widely used models for scoring the severity of illness of ICU patients include the Acute Physiology and Chronic Health Evaluation (APACHE), the Simplified Acute Physiology Score (SAPS), and the Mortality Prediction Model (MPM).1620 The APACHE II system is the most widely quoted in the medical literature but is based on a validation cohort more than 25 years old.16 The scoring algorithms for APACHE III and APACHE IV have been released on the Web; the most recent iteration, APACHE IV, was developed using data from more than 100,000 admissions to a variety of types of ICUs between January 1, 2002, and December 31, 2003, and also includes predictions for ICU LOS.18 Use of these tools allows the ICU clinician to benchmark the unit's performance against this large heterogeneous group of ICU patients treated using contemporary ICU practice patterns. Important features of mechanical ventilation episodes worth tracking include: time of start and finish of each episode (to calculate ventilator LOS); whether the patient had an unplanned extubation; the percentage of patients who required reintubation after planned extubation; tracheostomy rate; and the use of continuous intravenous sedatives or paralytics.

An advanced data outcome system would be linked to various hospital data silos, allowing capture of all laboratory, pharmacy, and radiology charges into the ICU database, allowing financial analysis of ICU performance. Another link would funnel all important laboratory results into the database. Additional types of useful data include: ultimate discharge status of the patient (eg, home, skilled nursing facility, rehabilitation facility, another acute care hospital); procedures done in the ICU; infections acquired in the ICU; and comorbidities based on ICD‐9 codes. Several examples of the output possible with the use of the advanced data outcome system developed for use in the Stamford Hospital ICU are reported later in this article.

Protocol‐driven collaborative culture

Successful implementation of TGC is most likely in an environment that embraces standardized care using evidence‐based best practices. All routine aspects of care in the Stamford Hospital ICU are protocol driven. Some examples include deep‐vein thrombosis prophylaxis, stress ulcer prophylaxis, ventilator weaning, ventilator sedation, enteral nutrition, and potassium, phosphate, and magnesium repletion. These protocols were all in place when discussions began in the ICU about how to create a TGC protocol. The nurses were comfortable using protocols, and there were no longer any counterproductive arguments about physician autonomy of treatment decisions centered on these basic care issues. These factors facilitated adoption of the TGC protocol. Finally, the strength of the relationship binding the nursing and medical leadership of the ICU was fundamental to the program's success. A complex initiative such as TGC mandates that these parties share the same vision for the ICU.

Overcoming resistance

Adoption of TGC by an ICU will undoubtedly encounter resistance from the staff. The factors responsible for this are very real. An understanding and patient attitude by the unit's leadership will greatly facilitate implementation. Factors that are the basis for this resistance in part include:

  • TGC represents a fundamental paradigm shift in ICU care. Until recently, hyperglycemia, even at levels as high as 200‐250 mg/dL, has until recently been tolerated and ignored, as it has been considered a normal adaptive response to acute and severe illness.

  • Doing TGC correctly is hard work. This work includes the logistics of monitoring, explaining to families and patients the reasons for frequent finger sticks or blood testing (But Grandma isn't even a diabetic), being aware of the potential for significant discomfort to the patient, and having to make treatment decisions in response to all the newly acquired data.

  • Fear of hypoglycemia. Nurses want to protect, and not hurt, their patients. Insulin therapy, especially when targeting euglycemia or near‐euglycemia, is potentially dangerous.

An effective educational program directed to the staff, including nurses, staff physicians, and pharmacists, will help surmount this resistance. The components of this educational program should include: the basis in the medical literature for instituting intensive programs to monitor and treat patient glycemic levels; a review of the insulin formulations (subcutaneous, intravenous, long acting, and short acting) with emphasis on the different pharmacokinetic implications underlying their use; and a detailed analysis of factors associated with hypoglycemia.21, 22

Specific Issues Regarding TGC Implementation

Setting the glycemic target

What is the correct glycemic target? Van den Berghe et al. used a treatment threshold of 110 mg/dL for both her surgical ICU and medical ICU studies. The Stamford Hospital ICU trial, with a mixed population of medical, surgical, and cardiac patients, targeted 140 mg/dL.13

A detailed review of a very large cohort of patients treated in the Stamford Hospital ICU suggests that patients who achieve low euglycemia have the best survival (see Fig. 3). This analysis used APACHE methodology to analyze expected and actual mortality in relation to each patient's mean glucose during the ICU stay. The APACHE III and IV mortality prediction models use age, presence or absence of a group of important comorbidities, admitting diagnosis to the ICU, length of time in the ICU before ICU admission, location of the patient prior to ICU admission, and the most abnormal values of a large group of physiological parameters during the first 24 hours of ICU admission to derive a discrete prediction of hospital mortality for that patient. A standardized mortality ratio (SMR) can be calculated by dividing the patients' actual hospital mortality rate by the mean of all the individual predictions of mortality (SMR = actual/predicted mortality). A value less than 1 suggests that the patients in the observed cohort had a lower mortality rate than that predicted by the model.

Figure 3
Standardized mortality ratio related to mean glucose level during ICU stay.

Patients who achieved euglycemia (<110 mg/dL) in the surgical ICU study of Van den Berghe et al. also had the lowest mortality rates as well as the lowest incidence of the various comorbidities measured compared to those with intermediate blood glucose levels (110‐150 mg/dL). Those with the worst glycemic control (blood glucose > 150 mg/dL) had the highest mortality rate and the highest incidence of various serious comorbid conditions.23

Although available data support a euglycemic target, is this unequivocally the correct target for an ICU beginning TGC implementation? Not necessarily. Targeting 110 mg/dL requires an intensity of treatment that may be intimidating to an ICU staff, especially one without experience managing protocols. Moreover, the lower the glycemic target, the greater the risk for iatrogenic hypoglycemia. An ICU considering implementation of a TGC protocol might consider staged adoption. The initial target might be as high as 175 mg/dL. As the clinicians gain experience using the protocol, including acquiring and reporting data, the treatment threshold could be lowered. The Stamford Hospital ICU staff, with more than 5 years of experience developing a model of standardized care using evidence‐based best‐practice patient care protocols, spent several months arguing about the glycemic target when TGC was first discussed following publication of the initial Van den Berghe study.12 The director of Critical Care wanted to replicate Van den Berghe's work and urged a target of 110 mg/dL. The nurses refused. A compromise was reached: a 140 mg/dL treatment threshold. This confirms an important lesson: the ICU team must choose an achievable goal. It is noteworthy that after 2 years of successful use of the glucose 140 protocol, the Stamford Hospital ICU nurses initiated a revision of the protocol, deciding they wanted to target 125 mg/dL. Figure 4 illustrates the glycemic and mortality results comparing the last 3 years before TGC with the glucose 140 and glucose 125 periods.

Figure 4
Mortality rate and mean glucose levels of patients admitted to Stamford Hospital ICU during three years of the historic era and the two treatment eras.

Choosing a protocol

After choosing a glycemic target, the ICU leadership must agree on a protocol to achieve the objective. TGC protocols can be broadly characterized as directive or nondirective.

The Stamford Hospital ICU TGC protocol is an example of a nondirective protocol.13 The nursing staff considers the document a starting point for therapy decisions. Many patients receive insulin dosing at variance with the guidelines established by the document. A nurse is empowered to make these treatment decisions. This is not dissimilar to the process ICU nurses use when titrating a vasopressor to achieve a targeted goal for mean arterial pressure. Nondirective protocols are most suitable for ICU staffs that have had considerable prior experience using nurse‐driven protocols in an environment that supports and accepts standardized care.

A number of directive protocols have been published in the literature.24 Their unifying feature is the goal of prescribing a specific insulin dose for each set of circumstances a nurse may encounter. The patient's previous glucose level and the rate of change in glucose level are considered, and the document typically details the choices for insulin dosing in several columns based on the patient's previously documented sensitivity to insulin. Although this sort of protocol can be helpful in providing explicit guidance with insulin dosing, its complexity may impede adoption.

Another option is the use of tools that have been developed to assist an ICU in initiating and promulgating TGC protocols, including software applications that automatically calculate insulin dosing. Finally, work has been initiated on the development of monitors that provide near‐continuous monitoring of glucose levels at bedside.25, 26 Adoption of such monitoring will facilitate the implementation of TGC protocols because of its impact on eliminating the workflow burdens of intensive glycemic monitoring as well as markedly diminishing the risk of hypoglycemia.

Hypoglycemia

In the Van den Berghe et al. surgical ICU study, severe hypoglycemia, defined as a glucose level less than 40 mg/dL, occurred at least once among 5.1% of the patients in the intensively treated group versus in 0.8% of the patients in the conventionally treated group.12 The hypoglycemia was described as transient, a result of the frequency of monitoring during the study, and was not associated with overt adverse consequences. The incidence of severe hypoglycemia (<40 mg/dL) was described differently in the Stamford Hospital trial: 0.35% of all the values obtained during the baseline period, compared to 0.34% of those obtained during the treatment period, again without any overt adverse consequences.13 Nevertheless, it is not known with certainty whether having even a single episode of severe hypoglycemia independently contributes to the risk of mortality.

Vreisendorp recently identified a group of predisposing factors for the development of severe hypoglycemia among ICU patients undergoing TGC.21 The most important include: a decrease in the administration of nutrition without a concomitant change in insulin dosing; diabetes mellitus; insulin treatment; sepsis; inotropic support; and renal failure. The Stamford Hospital ICU TGC protocol document now includes a black box warning highlighting renal failure (associated with decreased clearance of administered insulin), hepatic failure, and sepsis (associated with decreased hepatic gluconeogenesis) as major risk factors for severe hypoglycemia. Ongoing reinforcement is necessary to encourage the ICU staff recognize these risk factors for severe hypoglycemia and respond by adopting more conservative insulin dosing and instituting more frequent glucose monitoring.

Economic Benefits of TGC

Recently published data support the economic benefits of intensive glycemic management. Van den Berghe et al. quantified costs attributable to ICU days, mechanical ventilation, and use of antibiotics, vasopressors, intotropic agents, and transfusions in the 2 treatment groups in their surgical ICU study. The savings per patient in the intensively treated group totaled $2638; mean LOS was 6.6 days.27, 28 Data from the Stamford Hospital ICU trial was analyzed differently, with quantification of all laboratory, pharmacy, and diagnostic imaging costs, as well as costs associated with ICU days, mechanical ventilation and days in the hospital after ICU discharge.29 The savings per patient in the intensively treated group totaled $1560. Notably, this occurred in the context of a much shorter LOS than that seen in the Belgian trial; mean and median LOS were only 3.4 and 1.7 days, respectively.

CONCLUSIONS

Intensive glycemic management of critically ill patients is emerging as a standard of care, based on data demonstrating its effectiveness in reducing mortality, morbidity, and costs. Intensive care unit staffs need to make important choices about the type of protocol most suitable for use, the glycemic target, and the mechanisms for avoiding hypoglycemia. The implementation of appropriate data management tools in a protocol‐driven environment that supports standardization of care will facilitate adoption of TGC.

References
  1. Nasraway SA.Hyperglycemia during critical illness.J Parenter Enteral Nutr.2006;30:254258.
  2. Capes SE,Hunt D,Malmberg K, et al.Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview.Lancet.2000;355:773778.
  3. Malmberg K.Prospective randomised study of intensive insulin treatment on long term survival after acute myocardial infarction in patients with diabetes mellitus.DIGAMI (Diabetes Mellitus, Insulin Glucose Infusion in Acute Myocardial Infarction) Study Group.BMJ.1997;314:15121515.
  4. Capes SE,Hunt D,Malmberg K, et al.Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview.Stroke.2001;32:24262432.
  5. Bruno A,Levine SR,Frankel MR, et al.Admission glucose level and clinical outcomes in the NINDS rt‐PA Stroke Trial.Neurology.2002;59:669674.
  6. Estrada CA,Young JA,Nifong LW, et al.Outcomes and perioperative hyperglycemia in patients with or without diabetes mellitus undergoing coronary artery bypass grafting.Ann Thorac Surg.2003;75:13921399.
  7. Yendamuri S,Fulda GJ,Tinkoff GH.Admission hyperglycemia as a prognostic indicator in trauma.J Trauma.2003;55:3338.
  8. Coursin DB,Connery LE,Ketzler JT.Perioperative diabetic and hyperglycemic management issues.Crit Care Med.2004;32:S116S125.
  9. Krinsley JS.Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.Mayo Clinic Proc.2003;78:14711478.
  10. Furnary AP,Zerr KJ,Grunkemeier GL, et al.Continuous intravenous insulin infusion reduces the incidence of deep sternal wound infection in diabetic patients after cardiac surgical procedures.Ann Thorac Surg.1999;67:352360.
  11. Furnary AP,Gao G,Grunkemeier GL, et al.Continuous insulin infusion reduces mortality in patients with diabetes undergoing coronary artery bypass grafting.J Thorac Cardiovasc Surg.2003;125:10071021.
  12. Van den Berghe G,Wouters P,Weekers F, et al.Intensive insulin therapy in the critically ill patients.N Engl J Med.2001;345:13591367.
  13. Krinsley JS.Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79:9921000.
  14. Van den Berghe G,Wilmer A,Hermans G, et al.Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354:449461.
  15. Curtis JR,Cook DF,Wall RJ, et al.Intensive care unit quality improvement: A “how‐to” guide for the interdisciplinary team.Crit Care Med.2006;34:211218.
  16. Knaus WA,Draper EA,Wagner DP, et al.APACHE II. A severity of disease classification system.Crit Care Med.1985;13:818829.
  17. Knaus WA,Wagner DP,Draper EA, et al.The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest.1991;100:16191636.
  18. http://www.cerner.com/public/Cerner_3.asp?id=3562. Accessed December 12,2006.
  19. Aegerter P,Boumendil A,Retbi A, et al.SAPS II revisited.Int Care Med.2005;31:416423.
  20. Lemeshow S,Teres D,Klar J, et al.Mortality probability models (MPM II) based on an international cohort of intensive care unit patients.JAMA.1993;270:247886.
  21. Vriesendorp TM,van Santen S,DeVries JH, et al.Predisposing factors for hypoglycemia in the intensive care unit.Crit Care Med.2006;34:96101.
  22. Vriesendorp TM,DeVries JH,van Santen S, et al.Evaluation of short‐term outcomes of hypoglycemia in the intensive care unit.Crit Care Med.2006;34:27141218.
  23. Van den Berghe G,Wouters PJ,Bouillon R, et al.Outcome benefit of intensive insulin therapy in the critically ill: Insulin dose versus glycemic control.Crit Care Med.2003;31:359366.
  24. http://www.glycemiccontrol.net/Published_Protocols.htm. Accessed December 12,2006.
  25. Krinsley JS,Hall D,Zheng P, et al.Validation of the OptiScanner, a new continuous glucose monitor.Crit Care Med.2005;33:S265.
  26. Krinsley JS,Zheng, P,Hall D, et al.ICU validation of the OptiScanner, a continuous glucose monitoring device.Crit Care Med.2006;34:A67.
  27. Van den Berghe G,Wouters P,Kesteloot K, et al.Analysis of healthcare resource utilization with intensive insulin therapy in critically ill patients.Crit Care Med.2006;34:612616.
  28. Krinsley JS.A simple intervention that saves lives and money.Crit Care Med.2006;34:896.
  29. Krinsley JS,Jones RL.Cost analysis of intensive glycemic control in critically ill adult patients.Chest.2006;129:644650.
References
  1. Nasraway SA.Hyperglycemia during critical illness.J Parenter Enteral Nutr.2006;30:254258.
  2. Capes SE,Hunt D,Malmberg K, et al.Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview.Lancet.2000;355:773778.
  3. Malmberg K.Prospective randomised study of intensive insulin treatment on long term survival after acute myocardial infarction in patients with diabetes mellitus.DIGAMI (Diabetes Mellitus, Insulin Glucose Infusion in Acute Myocardial Infarction) Study Group.BMJ.1997;314:15121515.
  4. Capes SE,Hunt D,Malmberg K, et al.Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview.Stroke.2001;32:24262432.
  5. Bruno A,Levine SR,Frankel MR, et al.Admission glucose level and clinical outcomes in the NINDS rt‐PA Stroke Trial.Neurology.2002;59:669674.
  6. Estrada CA,Young JA,Nifong LW, et al.Outcomes and perioperative hyperglycemia in patients with or without diabetes mellitus undergoing coronary artery bypass grafting.Ann Thorac Surg.2003;75:13921399.
  7. Yendamuri S,Fulda GJ,Tinkoff GH.Admission hyperglycemia as a prognostic indicator in trauma.J Trauma.2003;55:3338.
  8. Coursin DB,Connery LE,Ketzler JT.Perioperative diabetic and hyperglycemic management issues.Crit Care Med.2004;32:S116S125.
  9. Krinsley JS.Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.Mayo Clinic Proc.2003;78:14711478.
  10. Furnary AP,Zerr KJ,Grunkemeier GL, et al.Continuous intravenous insulin infusion reduces the incidence of deep sternal wound infection in diabetic patients after cardiac surgical procedures.Ann Thorac Surg.1999;67:352360.
  11. Furnary AP,Gao G,Grunkemeier GL, et al.Continuous insulin infusion reduces mortality in patients with diabetes undergoing coronary artery bypass grafting.J Thorac Cardiovasc Surg.2003;125:10071021.
  12. Van den Berghe G,Wouters P,Weekers F, et al.Intensive insulin therapy in the critically ill patients.N Engl J Med.2001;345:13591367.
  13. Krinsley JS.Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79:9921000.
  14. Van den Berghe G,Wilmer A,Hermans G, et al.Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354:449461.
  15. Curtis JR,Cook DF,Wall RJ, et al.Intensive care unit quality improvement: A “how‐to” guide for the interdisciplinary team.Crit Care Med.2006;34:211218.
  16. Knaus WA,Draper EA,Wagner DP, et al.APACHE II. A severity of disease classification system.Crit Care Med.1985;13:818829.
  17. Knaus WA,Wagner DP,Draper EA, et al.The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest.1991;100:16191636.
  18. http://www.cerner.com/public/Cerner_3.asp?id=3562. Accessed December 12,2006.
  19. Aegerter P,Boumendil A,Retbi A, et al.SAPS II revisited.Int Care Med.2005;31:416423.
  20. Lemeshow S,Teres D,Klar J, et al.Mortality probability models (MPM II) based on an international cohort of intensive care unit patients.JAMA.1993;270:247886.
  21. Vriesendorp TM,van Santen S,DeVries JH, et al.Predisposing factors for hypoglycemia in the intensive care unit.Crit Care Med.2006;34:96101.
  22. Vriesendorp TM,DeVries JH,van Santen S, et al.Evaluation of short‐term outcomes of hypoglycemia in the intensive care unit.Crit Care Med.2006;34:27141218.
  23. Van den Berghe G,Wouters PJ,Bouillon R, et al.Outcome benefit of intensive insulin therapy in the critically ill: Insulin dose versus glycemic control.Crit Care Med.2003;31:359366.
  24. http://www.glycemiccontrol.net/Published_Protocols.htm. Accessed December 12,2006.
  25. Krinsley JS,Hall D,Zheng P, et al.Validation of the OptiScanner, a new continuous glucose monitor.Crit Care Med.2005;33:S265.
  26. Krinsley JS,Zheng, P,Hall D, et al.ICU validation of the OptiScanner, a continuous glucose monitoring device.Crit Care Med.2006;34:A67.
  27. Van den Berghe G,Wouters P,Kesteloot K, et al.Analysis of healthcare resource utilization with intensive insulin therapy in critically ill patients.Crit Care Med.2006;34:612616.
  28. Krinsley JS.A simple intervention that saves lives and money.Crit Care Med.2006;34:896.
  29. Krinsley JS,Jones RL.Cost analysis of intensive glycemic control in critically ill adult patients.Chest.2006;129:644650.
Page Number
13-19
Page Number
13-19
Article Type
Display Headline
Translating evidence into practice in managing inpatient hyperglycemia
Display Headline
Translating evidence into practice in managing inpatient hyperglycemia
Sections
Article Source
Copyright © 2007 Society of Hospital Medicine
Disallow All Ads
Correspondence Location
190 West Broad St., Stamford, Connecticut 06902
Content Gating
Gated (full article locked unless allowed per User)
Gating Strategy
First Peek Free
Article PDF Media