New cholesterol guidelines: Worth the wait?

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New cholesterol guidelines: Worth the wait?

On November 12, 2013, a joint task force for the American College of Cardiology and American Heart Association released new guidelines for treating high blood cholesterol to reduce the risk of atherosclerotic cardiovascular disease (ASCVD) in adults.1

This document arrives after several years of intense deliberation, 12 years after the third Adult Treatment Panel (ATP III) guidelines,2 and 8 years after an ATP III update recommending that low-density lipoprotein cholesterol (LDL-C) levels be lowered aggressively (to less than 70 mg/dL) as an option in patients at high risk.3 It represents a major shift in the approach to and management of high blood cholesterol and has sparked considerable controversy.

In the following commentary, we summarize the new guidelines and the philosophy employed by the task force in generating them. We will also examine some advantages and what we believe to be several shortcomings of the new guidelines. These latter points are illustrated through case examples.

IN RANDOMIZED CONTROLLED TRIALS WE TRUST

In collaboration with the National Heart, Lung, and Blood Institute of the National Institutes of Health, the American College of Cardiology and American Heart Association formed an expert panel task force in 2008.

The task force elected to use only evidence from randomized controlled trials, systematic reviews, and meta-analyses of randomized controlled trials (and only predefined outcomes of the trials, not post hoc analyses) in formulating its recommendations, with the goal of providing the strongest possible evidence.

The authors state that “By using [randomized controlled trial] data to identify those most likely to benefit [emphasis in original] from cholesterol-lowering statin therapy, the recommendations will be of value to primary care clinicians as well as specialists concerned with ASCVD prevention. Importantly, the recommendations were designed to be easy to use in the clinical setting, facilitating the implementation of a strategy of risk assessment and treatment focused on the prevention of ASCVD.”3 They also state the guidelines are meant to “inform clinical judgment, not replace it” and that clinician judgment in addition to discussion with patients remains vital.

During the deliberations, the National Heart, Lung, and Blood Institute removed itself from participating, stating its mission no longer included drafting new guidelines. Additionally, other initial members of the task force removed themselves because of disagreement and concerns about the direction of the new guidelines.

These guidelines, and their accompanying new cardiovascular risk calculator,4 were released without a preliminary period to allow for open discussion, comment, and critique by physicians outside the panel. No attempt was made to harmonize the guidelines with previous versions (eg, ATP III) or with current international guidelines.

WHAT’S NEW IN THE GUIDELINES?

The following are the major changes in the new guidelines for treating high blood cholesterol:

  • Treatment goals for LDL-C and non-high-density lipoprotein cholesterol (non-HDL-C) are no longer recommended.
  • High-intensity and moderate-intensity statin treatment is emphasized, and low-intensity statin therapy is nearly eliminated.
  • “ASCVD” now includes stroke in addition to coronary heart disease and peripheral arterial disease.
  • Four groups are targeted for treatment (see below).
  • Nonstatin therapies have been markedly de-emphasized.
  • No guidelines are provided for treating high triglyceride levels.

The new guidelines emphasize lifestyle modification as the foundation for reducing risk, regardless of cholesterol therapy. No recommendations are given for patients with New York Heart Association class II, III, or IV heart failure or for hemodialysis patients, because there were insufficient data from randomized controlled trials to support recommendations. Similarly, the guidelines apply only to people between the ages of 40 and 75 (risk calculator ages 40–79), because the authors believed there was not enough evidence from randomized controlled trials to allow development of guidelines outside of this age range.

FOUR MAJOR STATIN TREATMENT GROUPS

The new guidelines specify four groups that merit intensive or moderately intensive statin therapy (Table 1)1:

  • People with clinical ASCVD
  • People with LDL-C levels of 190 mg/dL or higher
  • People with diabetes, age 40 to 75
  • People without diabetes, age 40 to 75, with LDL-C levels 70–189 mg/dL, and a 10-year ASCVD risk of 7.5% or higher as determined by the new risk calculator4 (which also calculates the lifetime risk of ASCVD).

Below, we will address each of these four groups and provide case scenarios to consider. In general, our major disagreements with the new recommendations pertain to the first and fourth categories.

 

 

GROUP 1: PEOPLE WITH CLINICAL ASCVD

Advantages of the new guidelines

  • They appropriately recommend statins in the highest tolerated doses as first-line treatment for this group at high risk.
  • They designate all patients with ASCVD, including those with coronary, peripheral, and cerebrovascular disease, as a high-risk group.
  • Without target LDL-C levels, treatment is simpler than before, requiring less monitoring of lipid levels. (This can also be seen as a limitation, as we discuss below.)

Limitations of the new guidelines

  • They make follow-up LDL-C levels irrelevant, seeming to assume that there is no gradation in residual risk and, thus, no need to tailor therapy to the individual.
  • Patients no longer have a goal to strive for or a way to monitor their progress.
  • The guidelines ignore the pathophysiology of coronary artery disease and evidence of residual risk in patients on both moderate-intensity and high-intensity statin therapy.
  • They also ignore the potential benefits of treating to lower LDL-C or non-HDL-C goals, thus eliminating consideration of multidrug therapy. They do not address patients with recurrent cardiovascular events already on maximal tolerated statin doses.
  • They undermine the potential development and use of new therapies for dysplipidemia in patients with ASCVD.

Case 1: Is LDL-C 110 mg/dL low enough?

A 52-year-old African American man presents with newly discovered moderate coronary artery disease that is not severe enough to warrant stenting. He has no history of hypertension, diabetes mellitus, or smoking. His systolic blood pressure is 130 mm Hg, and his body mass index is 26 kg/m2. He exercises regularly and follows a low-cholesterol diet. He has the following fasting lipid values:

  • Total cholesterol 290 mg/dL
  • HDL-C 50 mg/dL
  • Triglycerides 250 mg/dL
  • Calculated LDL-C 190 mg/dL.

Two months later, after beginning atorvastatin 80 mg daily, meeting with a nutritionist, and redoubling his dietary efforts, his fasting lipid concentrations are:

  • Total cholesterol 180 mg/dL
  • HDL-C 55 mg/dL
  • Triglycerides 75 mg/dL
  • Calculated LDL-C 110 mg/dL.

Comment: Lack of LDL-C goals is a flaw

The new guidelines call for patients with known ASCVD, such as this patient, to receive intensive statin therapy—which he got.

However, once a patient is on therapy, the new guidelines do not encourage repeating the lipid panel other than to assess compliance. With intensive therapy, we expect a reduction in LDL-C of at least 50% (Table 1), but patient-to-patient differences in response to medications are common, and without repeat testing we would have no way of gauging this patient’s residual risk.

Further, the new guidelines emphasize the lack of hard outcome data supporting the addition of another lipid-lowering drug to a statin, although they do indicate that one can consider it. In a patient at high risk, such as this one, would you be comfortable with an LDL-C value of 110 mg/dL on maximum statin therapy? Would you consider adding a nonstatin drug?

Figure 1. Scatter plot with best-fit lines of major lipid trials (statin and nonstatin trials) for both primary and secondary prevention of coronary heart disease events. Even though the trials were not designed to show differences based on a target LDL-C level, there is a clear relationship of fewer events with lower LDL-C levels.

A preponderance of data shows that LDL plays a causal role in ASCVD development and adverse events. Genetic data show that the LDL particle and the LDL receptor pathway are mechanistically linked to ASCVD pathogenesis, with lifetime exposure as a critical determinant of risk.5,6 Moreover, randomized controlled trials of statins and other studies of cholesterol-lowering show a reproducible relationship between the LDL-C level achieved and absolute risk (Figure 1).7–24 We believe the totality of data constitutes a strong rationale for targeting LDL-C and establishing goals for lowering its levels. For these reasons, we believe that removing LDL-C goals is a fundamental flaw of the new guidelines.

The reason for the lack of data from randomized controlled trials demonstrating benefits of adding therapies to statins (when LDL-C is still high) or benefits of treating to specific goals is that no such trials have been performed. Even trials of nonpharmacologic means of lowering LDL-C, such as ileal bypass, which was used in the Program on the Surgical Control of the Hyperlipidemias trial,20 provide independent evidence that lowering LDL-C reduces the risk of ASCVD (Figure 1).

In addition, trials of nonstatin drugs, such as the Coronary Drug Project,25 which tested niacin, also showed outcome benefits. On the other hand, studies such as the Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health26 and Treatment of HDL to Reduce the Incidence of Vascular Events27 trials did not show additional risk reduction when niacin was added to statin therapy. However, the study designs arguably had flaws, including requirement of aggressive LDL-lowering with statins, with LDL-C levels below 70 to 80 mg/dL before randomization.

Therefore, these trials do not tell us what to do for a patient on maximal intensive therapy who has recurrent ASCVD events or who, like our patient, has an LDL-C level higher than previous targets.

For this patient, we would recommend adding a second medication to further lower his LDL-C, but discussing with him the absence of proven benefit in clinical trials and the risks of side effects. At present, lacking LDL-C goals in the new guidelines, we are keeping with the ATP III goals to help guide therapeutic choices and individualize patient management.

GROUP 2: PEOPLE WITH LDL-C ≥ 190

Advantages of the new guidelines

  • They state that these patients should receive statins in the highest tolerated doses, which is universally accepted.

Limitations of the new guidelines

  • The new guidelines mention only that one “may consider” adding a second agent if LDL-C remains above 190 mg/dL after maximum-dose therapy. Patients with familial hypercholesterolemia or other severe forms of hypercholesterolemia typically end up on multidrug therapy to further reduce LDL-C. The absence of randomized controlled trial data in this setting to show an additive value of second and third lipid-lowering agents does not mean these agents do not provide benefit.
 

 

GROUP 3: DIABETES, AGE 40–75, LDL-C 70–189, NO CLINICAL ASCVD

Advantages of the new guidelines

  • They call for aggressive treatment of people with diabetes, a group at high risk that derives significant benefit from statin therapy, as shown in randomized controlled trials.

Limitations of the new guidelines

  • Although high-intensity statin therapy is indicated for this group, we believe that, using the new risk calculator, some patients may receive overly aggressive treatment, thus increasing the possibility of statin side effects.
  • The guidelines do not address patients younger than 40 or older than 75.
  • Diabetic patients have a high residual risk of ASCVD events, even on statin therapy. Yet the guidelines ignore the potential benefits of more aggressive LDL-lowering or non-LDL secondary targets for therapy.

Case 2: How low is too low?

A 63-year-old white woman, a nonsmoker with recently diagnosed diabetes, is seen by her primary care physician. She has hypertension, for which she takes lisinopril 5 mg daily. Her fasting lipid values are:

  • Total cholesterol 160 mg/dL
  • HDL-C 64 mg/dL
  • Triglycerides 100 mg/dL
  • Calculated LDL-C 76 mg/dL.

Her systolic blood pressure is 129 mm Hg, and based on the new risk calculator, her 10-year risk of cardiovascular disease is 10.2%. According to the new guidelines, she should be started on high-intensity statin treatment (Table 1).

Although this is an acceptable initial course of action, it necessitates close vigilance, since it may actually drive her LDL-C level too low. Randomized controlled trials have typically used an LDL-C concentration of less than or equal to 25 mg/dL as the safety cutoff. With a typical LDL-C reduction of at least 50% on high-intensity statins, our patient’s expected LDL-C level will likely be in the low 30s. We believe this would be a good outcome, provided that she tolerates the medication without adverse effects. However, responses to statins vary from patient to patient.

High-intensity statin therapy may not be necessary to reduce risk adequately in all patients who have diabetes without preexisting vascular disease. The Collaborative Atorvastatin Diabetes Study12 compared atorvastatin 10 mg vs placebo in people with type 2 diabetes, age 40 to 75, who had one or more cardiovascular risk factors but no signs or symptoms of preexisting ASCVD and who had only average or below-average cholesterol levels—precisely like this patient. The trial was terminated early because of a clear benefit (a 37% reduction in the composite end point of major adverse cardiovascular events) in the intervention group. For our patient, we believe an alternative and acceptable approach would be to begin moderate-intensity statin therapy (eg, with atorvastatin 10 mg) (Table 1).

Alternatively, in a patient with diabetes and previous atherosclerotic vascular disease or with a high 10-year risk and high LDL-C, limiting treatment to high-intensity statin therapy by itself may deny them the potential benefits of combination therapies and targeting to lower LDL-C levels or non-HDL-C secondary targets. Guidelines from the American Diabetes Association28 and the American Association of Clinical Endocrinologists29 continue to recommend an LDL-C goal of less than 70 mg/dL in patients at high risk, a non-HDL-C less than 100 mg/dL, an apolipoprotein B less than 80 mg/dL, and an LDL particle number less than 1,000 nmol/L.

GROUP 4: AGE 40–75, LDL-C 70–189, NO ASCVD, BUT 10-YEAR RISK ≥ 7.5%

Advantages of the new guidelines

  • They may reduce ASCVD events for patients at higher risk.
  • The risk calculator is easy to use and focuses on global risk, ie, all forms of ASCVD.
  • The guidelines promote discussion of risks and benefits between patients and providers.

Limitations of the new guidelines

  • The new risk calculator is controversial (see below).
  • There is potential for overtreatment, particularly in older patients.
  • There is potential for undertreatment, particularly in patients with an elevated LDL-C but whose 10-year risk is less than 7.5% because they are young.
  • The guidelines do not address patients younger than 40 or older than 75.
  • They do not take into account some traditional risk factors, such as family history, and nontraditional risk factors such as C-reactive protein as measured by ultrasensitive assays, lipoprotein(a), and apolipoprotein B.

Risk calculator controversy

The new risk calculator has aroused strong opinions on both sides of the aisle.

Shortly after the new guidelines were released, cardiologists Dr. Paul Ridker and Dr. Nancy Cook from Brigham and Women’s Hospital in Boston published analyses30 showing that the new risk calculator, which was based on older data from several large cohorts such as the Atherosclerosis Risk in Communities study,31 the Cardiovascular Health Study,32 the Coronary Artery Risk Development in Young Adults study,33 and the Framingham Heart Study,34,35 was inaccurate in other cohorts. Specifically, in more-recent cohorts (the Women’s Health Study,36 Physicians’ Health Study,37 and Women’s Health Initiative38), the new calculator overestimates the 10-year risk of ASCVD by 75% to 150%.30 Using the new calculator would make approximately 30 million more Americans eligible for statin treatment. The concern is that patients at lower risk would be treated and exposed to potential side effects of statin therapy.

In addition, the risk calculator relies heavily on age and sex and does not include other factors such as triglyceride level, family history, C-reactive protein, or lipoprotein(a). Importantly, and somewhat ironically given the otherwise absolute adherence to randomized controlled trial data for guideline development, the risk calculator has never been verified in prospective studies to adequately show that using it reduces ASCVD events.

 

 

Case 3: Overtreating a primary prevention patient

Based on the risk calculator, essentially any African American man in his early 60s with no other risk factors has a 10-year risk of ASCVD of 7.5% or higher and, according to the new guidelines, should receive at least moderate-intensity statin therapy.

For example, consider a 64-year-old African American man whose systolic blood pressure is 129 mm Hg, who does not smoke, does not have diabetes, and does not have hypertension, and whose total cholesterol level is 180 mg/dL, HDL-C 70 mg/dL, triglycerides 130 mg/dL, and calculated LDL-C 84 mg/dL. His calculated 10-year risk is, surprisingly, 7.5%.

Alternatively, his twin brother is a two-pack-per-day smoker with untreated hypertension and systolic blood pressure 150 mm Hg, with fasting total cholesterol 153 mg/dL, HDL-C 70 mg/dL, triglycerides 60 mg/dL, and LDL-C 71 mg/dL. His calculated 10-year risk is 10.5%, so according to the new guidelines, he too should receive high-intensity statin therapy. Yet this patient clearly needs better blood pressure control and smoking cessation as his primary risk-reduction efforts, not a statin. While assessing global risk is important, a shortcoming of the new guidelines is that they can inappropriately lead to treating the risk score, not individualizing the treatment to the patient. Because of the errors inherent in the risk calculator, some experts have called for a temporary halt on implementing the new guidelines until the risk calculator can be further validated. In November 2013, the American Heart Association and the American College of Cardiology reaffirmed their support of the new guidelines and recommended that they be implemented as planned. As of the time this manuscript goes to print, there are no plans to halt implementation of the new guidelines.

Case 4: Undertreating a primary prevention patient

A 25-year-old white man with no medical history has a total cholesterol level of 310 mg/dL, HDL-C 50 mg/dL, triglycerides 400 mg/dL, and calculated LDL-C 180 mg/dL. He does not smoke or have hypertension or diabetes but has a strong family history of premature coronary disease (his father died of myocardial infarction at age 42). His body mass index is 25 kg/m2. Because he is less than 40 years old, the risk calculator does not apply to him.

If we assume he remains untreated and returns at age 40 with the same clinical factors and laboratory values, his calculated 10-year risk of an ASCVD event according to the new risk calculator will still be only 3.1%. Assuming his medical history remains unchanged as he continues to age, his 10-year risk would not reach 7.5% until he is 58. Would you feel comfortable waiting 33 years before starting statin therapy in this patient?

Waiting for dyslipidemic patients to reach middle age before starting LDL-C-lowering therapy is a failure of prevention. For practical reasons, there are no data from randomized controlled trials with hard outcomes in younger people. Nevertheless, a tenet of preventive cardiology is that cumulative exposure accelerates the “vascular age” ahead of the chronological age. This case illustrates why individualized recommendations guided by LDL-C goals as a target for therapy are needed. For this 25-year-old patient, we would recommend starting an intermediate- or high-potency statin.

Case 5: Rheumatoid arthritis

A 60-year-old postmenopausal white woman with severe rheumatoid arthritis presents for cholesterol evaluation. Her total cholesterol level is 235 mg/dL, HDL-C 50 mg/dL, and LDL-C 165 mg/dL. She does not smoke or have hypertension or diabetes. Her systolic blood pressure is 110 mm Hg. She has elevated C-reactive protein on an ultrasensitive assay and elevated lipoprotein(a).

Her calculated 10-year risk of ASCVD is 3.0%. Assuming her medical history remains the same, she would not reach a calculated 10-year risk of at least 7.5% until age 70. We suggest starting moderate- or high-dose statin therapy in this case, based on data (not from randomized controlled trials) showing an increased risk of ASCVD events in patients with rheumatologic disease, increased lipoprotein(a), and inflammatory markers like C-reactive protein. However, the current guidelines do not address this scenario, other than to suggest that clinician consideration can be given to other risk markers such as these, and that these findings should be discussed in detail with the patient. The Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin trial16 showed a dramatic ASCVD risk reduction in just such patients (Figure 1).

APPLAUSE—AND RESERVATIONS

The newest guidelines for treating high blood cholesterol represent a monumental shift away from using target levels of LDL-C and non-HDL-C and toward a focus on statin intensity for patients in the four highest-risk groups.

We applaud the expert panel for its idealistic approach of using only data from randomized controlled trials, for placing more emphasis on higher-intensity statin treatment, for including stroke in the new definition of ASCVD, and for focusing more attention on treating diabetic patients more aggressively. Simplifying the guidelines is a noble goal. Emphasizing moderate-to-high-intensity statin therapy in patients at moderate-to-high risk should have substantial long-term public health benefits.

However, as we have shown in the case examples, there are significant limitations, and some patients can end up being overtreated, while others may be undertreated.

Guidelines need to be crafted by looking at all the evidence, including the pathophysiology of the disease process, not just data from randomized controlled trials. It is difficult to implement a guideline that on one hand used randomized controlled trials exclusively for recommendations, but on the other hand used an untested risk calculator to guide therapy. Randomized controlled trials are not available for every scenario.

Further, absence of randomized controlled trial data in a given scenario should not be interpreted as evidence of lack of benefit. An example of this is a primary-prevention patient under age 40 with elevated LDL-C below the 190 mg/dL cutoff who otherwise is healthy and without risk factors (eg, Case 4). By disregarding all evidence that is not from randomized controlled trials, the expert panel fails to account for the extensive pathophysiology of ASCVD, which often begins at a young age and takes decades to develop.5,6,39 An entire generation of patients who have not reached the age of inclusion in most randomized controlled trials with hard outcomes is excluded (unless the LDL-C level is very high), potentially setting back decades of progress in the field of prevention. Prevention only works if started. With childhood and young adult obesity sharply rising, we should not fail to address the under-40-year-old patient population in our guidelines.

Guidelines are designed to be expert opinion, not to dictate practice. Focusing on the individual patient instead of the general population at risk, the expert panel appropriately emphasizes the “importance of clinician judgment, weighing potential benefits, adverse effects, drug-drug interactions and patient preferences.” However, by excluding all data that do not come from randomized controlled trials, the panel neglects a very large base of knowledge and leaves many clinicians without as much expert opinion as we had hoped for.

LDL-C goals are important: they provide a scorecard to help the patient with lifestyle and dietary changes. They provide the health care provider guidance in making treatment decisions and focusing on treatment of a single patient, not a population. Moreover, if a patient has difficulty taking standard doses of statins because of side effects, the absence of LDL-C goals makes decision-making nearly impossible. We hope physicians will rely on LDL-C goals in such situations, falling back on the ATP III recommendations, although many patients may simply go untreated until they present with ASCVD or until they “age in” to a higher risk category.

We suggest caution in strict adherence to the new guidelines and instead urge physicians to consider a hybrid of the old guidelines (using the ATP III LDL-C goals) and the new ones (emphasizing global risk assessment and high-intensity statin treatment).

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Author and Disclosure Information

Chad Raymond, DO
Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic

Leslie Cho, MD
Co-Section Head, Medical Director, Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic

Michael Rocco, MD
Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic; Assistant Professor of Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH

Stanley L. Hazen, MD, PhD
Co-Section Head, Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic; Professor of Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH

Address: Stanley L. Hazen, MD, PhD, Lerner Research Institute, NC10, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195; e-mail: [email protected]

M.R. is a speaker for Abbott and Amarin.

S.L.H. is named as co-inventor on pending and issued patents held by Cleveland Clinic relating to cardiovascular diagnostics and therapeutics. S.L.H. reports he has been paid as a consultant by the following companies: Cleveland Heart Lab, Esperion, Liposciences, Merck & Co., Pfizer, and Procter & Gamble. S.L.H. reports he has received research funds from Abbott, Astra Zeneca, Cleveland Heart Lab, Esperion, Liposciences, Procter & Gamble, and Takeda. S.L.H. has the right to receive royalty payments for inventions or discoveries related to cardiovascular diagnostics and therapeutics from Abbott Laboratories, Cleveland Heart Lab, Esperion, Frantz Biomarkers, and Liposciences.

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Chad Raymond, DO
Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic

Leslie Cho, MD
Co-Section Head, Medical Director, Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic

Michael Rocco, MD
Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic; Assistant Professor of Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH

Stanley L. Hazen, MD, PhD
Co-Section Head, Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic; Professor of Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH

Address: Stanley L. Hazen, MD, PhD, Lerner Research Institute, NC10, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195; e-mail: [email protected]

M.R. is a speaker for Abbott and Amarin.

S.L.H. is named as co-inventor on pending and issued patents held by Cleveland Clinic relating to cardiovascular diagnostics and therapeutics. S.L.H. reports he has been paid as a consultant by the following companies: Cleveland Heart Lab, Esperion, Liposciences, Merck & Co., Pfizer, and Procter & Gamble. S.L.H. reports he has received research funds from Abbott, Astra Zeneca, Cleveland Heart Lab, Esperion, Liposciences, Procter & Gamble, and Takeda. S.L.H. has the right to receive royalty payments for inventions or discoveries related to cardiovascular diagnostics and therapeutics from Abbott Laboratories, Cleveland Heart Lab, Esperion, Frantz Biomarkers, and Liposciences.

Author and Disclosure Information

Chad Raymond, DO
Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic

Leslie Cho, MD
Co-Section Head, Medical Director, Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic

Michael Rocco, MD
Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic; Assistant Professor of Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH

Stanley L. Hazen, MD, PhD
Co-Section Head, Section of Preventive Cardiology, Heart and Vascular Institute, Cleveland Clinic; Professor of Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH

Address: Stanley L. Hazen, MD, PhD, Lerner Research Institute, NC10, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195; e-mail: [email protected]

M.R. is a speaker for Abbott and Amarin.

S.L.H. is named as co-inventor on pending and issued patents held by Cleveland Clinic relating to cardiovascular diagnostics and therapeutics. S.L.H. reports he has been paid as a consultant by the following companies: Cleveland Heart Lab, Esperion, Liposciences, Merck & Co., Pfizer, and Procter & Gamble. S.L.H. reports he has received research funds from Abbott, Astra Zeneca, Cleveland Heart Lab, Esperion, Liposciences, Procter & Gamble, and Takeda. S.L.H. has the right to receive royalty payments for inventions or discoveries related to cardiovascular diagnostics and therapeutics from Abbott Laboratories, Cleveland Heart Lab, Esperion, Frantz Biomarkers, and Liposciences.

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On November 12, 2013, a joint task force for the American College of Cardiology and American Heart Association released new guidelines for treating high blood cholesterol to reduce the risk of atherosclerotic cardiovascular disease (ASCVD) in adults.1

This document arrives after several years of intense deliberation, 12 years after the third Adult Treatment Panel (ATP III) guidelines,2 and 8 years after an ATP III update recommending that low-density lipoprotein cholesterol (LDL-C) levels be lowered aggressively (to less than 70 mg/dL) as an option in patients at high risk.3 It represents a major shift in the approach to and management of high blood cholesterol and has sparked considerable controversy.

In the following commentary, we summarize the new guidelines and the philosophy employed by the task force in generating them. We will also examine some advantages and what we believe to be several shortcomings of the new guidelines. These latter points are illustrated through case examples.

IN RANDOMIZED CONTROLLED TRIALS WE TRUST

In collaboration with the National Heart, Lung, and Blood Institute of the National Institutes of Health, the American College of Cardiology and American Heart Association formed an expert panel task force in 2008.

The task force elected to use only evidence from randomized controlled trials, systematic reviews, and meta-analyses of randomized controlled trials (and only predefined outcomes of the trials, not post hoc analyses) in formulating its recommendations, with the goal of providing the strongest possible evidence.

The authors state that “By using [randomized controlled trial] data to identify those most likely to benefit [emphasis in original] from cholesterol-lowering statin therapy, the recommendations will be of value to primary care clinicians as well as specialists concerned with ASCVD prevention. Importantly, the recommendations were designed to be easy to use in the clinical setting, facilitating the implementation of a strategy of risk assessment and treatment focused on the prevention of ASCVD.”3 They also state the guidelines are meant to “inform clinical judgment, not replace it” and that clinician judgment in addition to discussion with patients remains vital.

During the deliberations, the National Heart, Lung, and Blood Institute removed itself from participating, stating its mission no longer included drafting new guidelines. Additionally, other initial members of the task force removed themselves because of disagreement and concerns about the direction of the new guidelines.

These guidelines, and their accompanying new cardiovascular risk calculator,4 were released without a preliminary period to allow for open discussion, comment, and critique by physicians outside the panel. No attempt was made to harmonize the guidelines with previous versions (eg, ATP III) or with current international guidelines.

WHAT’S NEW IN THE GUIDELINES?

The following are the major changes in the new guidelines for treating high blood cholesterol:

  • Treatment goals for LDL-C and non-high-density lipoprotein cholesterol (non-HDL-C) are no longer recommended.
  • High-intensity and moderate-intensity statin treatment is emphasized, and low-intensity statin therapy is nearly eliminated.
  • “ASCVD” now includes stroke in addition to coronary heart disease and peripheral arterial disease.
  • Four groups are targeted for treatment (see below).
  • Nonstatin therapies have been markedly de-emphasized.
  • No guidelines are provided for treating high triglyceride levels.

The new guidelines emphasize lifestyle modification as the foundation for reducing risk, regardless of cholesterol therapy. No recommendations are given for patients with New York Heart Association class II, III, or IV heart failure or for hemodialysis patients, because there were insufficient data from randomized controlled trials to support recommendations. Similarly, the guidelines apply only to people between the ages of 40 and 75 (risk calculator ages 40–79), because the authors believed there was not enough evidence from randomized controlled trials to allow development of guidelines outside of this age range.

FOUR MAJOR STATIN TREATMENT GROUPS

The new guidelines specify four groups that merit intensive or moderately intensive statin therapy (Table 1)1:

  • People with clinical ASCVD
  • People with LDL-C levels of 190 mg/dL or higher
  • People with diabetes, age 40 to 75
  • People without diabetes, age 40 to 75, with LDL-C levels 70–189 mg/dL, and a 10-year ASCVD risk of 7.5% or higher as determined by the new risk calculator4 (which also calculates the lifetime risk of ASCVD).

Below, we will address each of these four groups and provide case scenarios to consider. In general, our major disagreements with the new recommendations pertain to the first and fourth categories.

 

 

GROUP 1: PEOPLE WITH CLINICAL ASCVD

Advantages of the new guidelines

  • They appropriately recommend statins in the highest tolerated doses as first-line treatment for this group at high risk.
  • They designate all patients with ASCVD, including those with coronary, peripheral, and cerebrovascular disease, as a high-risk group.
  • Without target LDL-C levels, treatment is simpler than before, requiring less monitoring of lipid levels. (This can also be seen as a limitation, as we discuss below.)

Limitations of the new guidelines

  • They make follow-up LDL-C levels irrelevant, seeming to assume that there is no gradation in residual risk and, thus, no need to tailor therapy to the individual.
  • Patients no longer have a goal to strive for or a way to monitor their progress.
  • The guidelines ignore the pathophysiology of coronary artery disease and evidence of residual risk in patients on both moderate-intensity and high-intensity statin therapy.
  • They also ignore the potential benefits of treating to lower LDL-C or non-HDL-C goals, thus eliminating consideration of multidrug therapy. They do not address patients with recurrent cardiovascular events already on maximal tolerated statin doses.
  • They undermine the potential development and use of new therapies for dysplipidemia in patients with ASCVD.

Case 1: Is LDL-C 110 mg/dL low enough?

A 52-year-old African American man presents with newly discovered moderate coronary artery disease that is not severe enough to warrant stenting. He has no history of hypertension, diabetes mellitus, or smoking. His systolic blood pressure is 130 mm Hg, and his body mass index is 26 kg/m2. He exercises regularly and follows a low-cholesterol diet. He has the following fasting lipid values:

  • Total cholesterol 290 mg/dL
  • HDL-C 50 mg/dL
  • Triglycerides 250 mg/dL
  • Calculated LDL-C 190 mg/dL.

Two months later, after beginning atorvastatin 80 mg daily, meeting with a nutritionist, and redoubling his dietary efforts, his fasting lipid concentrations are:

  • Total cholesterol 180 mg/dL
  • HDL-C 55 mg/dL
  • Triglycerides 75 mg/dL
  • Calculated LDL-C 110 mg/dL.

Comment: Lack of LDL-C goals is a flaw

The new guidelines call for patients with known ASCVD, such as this patient, to receive intensive statin therapy—which he got.

However, once a patient is on therapy, the new guidelines do not encourage repeating the lipid panel other than to assess compliance. With intensive therapy, we expect a reduction in LDL-C of at least 50% (Table 1), but patient-to-patient differences in response to medications are common, and without repeat testing we would have no way of gauging this patient’s residual risk.

Further, the new guidelines emphasize the lack of hard outcome data supporting the addition of another lipid-lowering drug to a statin, although they do indicate that one can consider it. In a patient at high risk, such as this one, would you be comfortable with an LDL-C value of 110 mg/dL on maximum statin therapy? Would you consider adding a nonstatin drug?

Figure 1. Scatter plot with best-fit lines of major lipid trials (statin and nonstatin trials) for both primary and secondary prevention of coronary heart disease events. Even though the trials were not designed to show differences based on a target LDL-C level, there is a clear relationship of fewer events with lower LDL-C levels.

A preponderance of data shows that LDL plays a causal role in ASCVD development and adverse events. Genetic data show that the LDL particle and the LDL receptor pathway are mechanistically linked to ASCVD pathogenesis, with lifetime exposure as a critical determinant of risk.5,6 Moreover, randomized controlled trials of statins and other studies of cholesterol-lowering show a reproducible relationship between the LDL-C level achieved and absolute risk (Figure 1).7–24 We believe the totality of data constitutes a strong rationale for targeting LDL-C and establishing goals for lowering its levels. For these reasons, we believe that removing LDL-C goals is a fundamental flaw of the new guidelines.

The reason for the lack of data from randomized controlled trials demonstrating benefits of adding therapies to statins (when LDL-C is still high) or benefits of treating to specific goals is that no such trials have been performed. Even trials of nonpharmacologic means of lowering LDL-C, such as ileal bypass, which was used in the Program on the Surgical Control of the Hyperlipidemias trial,20 provide independent evidence that lowering LDL-C reduces the risk of ASCVD (Figure 1).

In addition, trials of nonstatin drugs, such as the Coronary Drug Project,25 which tested niacin, also showed outcome benefits. On the other hand, studies such as the Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health26 and Treatment of HDL to Reduce the Incidence of Vascular Events27 trials did not show additional risk reduction when niacin was added to statin therapy. However, the study designs arguably had flaws, including requirement of aggressive LDL-lowering with statins, with LDL-C levels below 70 to 80 mg/dL before randomization.

Therefore, these trials do not tell us what to do for a patient on maximal intensive therapy who has recurrent ASCVD events or who, like our patient, has an LDL-C level higher than previous targets.

For this patient, we would recommend adding a second medication to further lower his LDL-C, but discussing with him the absence of proven benefit in clinical trials and the risks of side effects. At present, lacking LDL-C goals in the new guidelines, we are keeping with the ATP III goals to help guide therapeutic choices and individualize patient management.

GROUP 2: PEOPLE WITH LDL-C ≥ 190

Advantages of the new guidelines

  • They state that these patients should receive statins in the highest tolerated doses, which is universally accepted.

Limitations of the new guidelines

  • The new guidelines mention only that one “may consider” adding a second agent if LDL-C remains above 190 mg/dL after maximum-dose therapy. Patients with familial hypercholesterolemia or other severe forms of hypercholesterolemia typically end up on multidrug therapy to further reduce LDL-C. The absence of randomized controlled trial data in this setting to show an additive value of second and third lipid-lowering agents does not mean these agents do not provide benefit.
 

 

GROUP 3: DIABETES, AGE 40–75, LDL-C 70–189, NO CLINICAL ASCVD

Advantages of the new guidelines

  • They call for aggressive treatment of people with diabetes, a group at high risk that derives significant benefit from statin therapy, as shown in randomized controlled trials.

Limitations of the new guidelines

  • Although high-intensity statin therapy is indicated for this group, we believe that, using the new risk calculator, some patients may receive overly aggressive treatment, thus increasing the possibility of statin side effects.
  • The guidelines do not address patients younger than 40 or older than 75.
  • Diabetic patients have a high residual risk of ASCVD events, even on statin therapy. Yet the guidelines ignore the potential benefits of more aggressive LDL-lowering or non-LDL secondary targets for therapy.

Case 2: How low is too low?

A 63-year-old white woman, a nonsmoker with recently diagnosed diabetes, is seen by her primary care physician. She has hypertension, for which she takes lisinopril 5 mg daily. Her fasting lipid values are:

  • Total cholesterol 160 mg/dL
  • HDL-C 64 mg/dL
  • Triglycerides 100 mg/dL
  • Calculated LDL-C 76 mg/dL.

Her systolic blood pressure is 129 mm Hg, and based on the new risk calculator, her 10-year risk of cardiovascular disease is 10.2%. According to the new guidelines, she should be started on high-intensity statin treatment (Table 1).

Although this is an acceptable initial course of action, it necessitates close vigilance, since it may actually drive her LDL-C level too low. Randomized controlled trials have typically used an LDL-C concentration of less than or equal to 25 mg/dL as the safety cutoff. With a typical LDL-C reduction of at least 50% on high-intensity statins, our patient’s expected LDL-C level will likely be in the low 30s. We believe this would be a good outcome, provided that she tolerates the medication without adverse effects. However, responses to statins vary from patient to patient.

High-intensity statin therapy may not be necessary to reduce risk adequately in all patients who have diabetes without preexisting vascular disease. The Collaborative Atorvastatin Diabetes Study12 compared atorvastatin 10 mg vs placebo in people with type 2 diabetes, age 40 to 75, who had one or more cardiovascular risk factors but no signs or symptoms of preexisting ASCVD and who had only average or below-average cholesterol levels—precisely like this patient. The trial was terminated early because of a clear benefit (a 37% reduction in the composite end point of major adverse cardiovascular events) in the intervention group. For our patient, we believe an alternative and acceptable approach would be to begin moderate-intensity statin therapy (eg, with atorvastatin 10 mg) (Table 1).

Alternatively, in a patient with diabetes and previous atherosclerotic vascular disease or with a high 10-year risk and high LDL-C, limiting treatment to high-intensity statin therapy by itself may deny them the potential benefits of combination therapies and targeting to lower LDL-C levels or non-HDL-C secondary targets. Guidelines from the American Diabetes Association28 and the American Association of Clinical Endocrinologists29 continue to recommend an LDL-C goal of less than 70 mg/dL in patients at high risk, a non-HDL-C less than 100 mg/dL, an apolipoprotein B less than 80 mg/dL, and an LDL particle number less than 1,000 nmol/L.

GROUP 4: AGE 40–75, LDL-C 70–189, NO ASCVD, BUT 10-YEAR RISK ≥ 7.5%

Advantages of the new guidelines

  • They may reduce ASCVD events for patients at higher risk.
  • The risk calculator is easy to use and focuses on global risk, ie, all forms of ASCVD.
  • The guidelines promote discussion of risks and benefits between patients and providers.

Limitations of the new guidelines

  • The new risk calculator is controversial (see below).
  • There is potential for overtreatment, particularly in older patients.
  • There is potential for undertreatment, particularly in patients with an elevated LDL-C but whose 10-year risk is less than 7.5% because they are young.
  • The guidelines do not address patients younger than 40 or older than 75.
  • They do not take into account some traditional risk factors, such as family history, and nontraditional risk factors such as C-reactive protein as measured by ultrasensitive assays, lipoprotein(a), and apolipoprotein B.

Risk calculator controversy

The new risk calculator has aroused strong opinions on both sides of the aisle.

Shortly after the new guidelines were released, cardiologists Dr. Paul Ridker and Dr. Nancy Cook from Brigham and Women’s Hospital in Boston published analyses30 showing that the new risk calculator, which was based on older data from several large cohorts such as the Atherosclerosis Risk in Communities study,31 the Cardiovascular Health Study,32 the Coronary Artery Risk Development in Young Adults study,33 and the Framingham Heart Study,34,35 was inaccurate in other cohorts. Specifically, in more-recent cohorts (the Women’s Health Study,36 Physicians’ Health Study,37 and Women’s Health Initiative38), the new calculator overestimates the 10-year risk of ASCVD by 75% to 150%.30 Using the new calculator would make approximately 30 million more Americans eligible for statin treatment. The concern is that patients at lower risk would be treated and exposed to potential side effects of statin therapy.

In addition, the risk calculator relies heavily on age and sex and does not include other factors such as triglyceride level, family history, C-reactive protein, or lipoprotein(a). Importantly, and somewhat ironically given the otherwise absolute adherence to randomized controlled trial data for guideline development, the risk calculator has never been verified in prospective studies to adequately show that using it reduces ASCVD events.

 

 

Case 3: Overtreating a primary prevention patient

Based on the risk calculator, essentially any African American man in his early 60s with no other risk factors has a 10-year risk of ASCVD of 7.5% or higher and, according to the new guidelines, should receive at least moderate-intensity statin therapy.

For example, consider a 64-year-old African American man whose systolic blood pressure is 129 mm Hg, who does not smoke, does not have diabetes, and does not have hypertension, and whose total cholesterol level is 180 mg/dL, HDL-C 70 mg/dL, triglycerides 130 mg/dL, and calculated LDL-C 84 mg/dL. His calculated 10-year risk is, surprisingly, 7.5%.

Alternatively, his twin brother is a two-pack-per-day smoker with untreated hypertension and systolic blood pressure 150 mm Hg, with fasting total cholesterol 153 mg/dL, HDL-C 70 mg/dL, triglycerides 60 mg/dL, and LDL-C 71 mg/dL. His calculated 10-year risk is 10.5%, so according to the new guidelines, he too should receive high-intensity statin therapy. Yet this patient clearly needs better blood pressure control and smoking cessation as his primary risk-reduction efforts, not a statin. While assessing global risk is important, a shortcoming of the new guidelines is that they can inappropriately lead to treating the risk score, not individualizing the treatment to the patient. Because of the errors inherent in the risk calculator, some experts have called for a temporary halt on implementing the new guidelines until the risk calculator can be further validated. In November 2013, the American Heart Association and the American College of Cardiology reaffirmed their support of the new guidelines and recommended that they be implemented as planned. As of the time this manuscript goes to print, there are no plans to halt implementation of the new guidelines.

Case 4: Undertreating a primary prevention patient

A 25-year-old white man with no medical history has a total cholesterol level of 310 mg/dL, HDL-C 50 mg/dL, triglycerides 400 mg/dL, and calculated LDL-C 180 mg/dL. He does not smoke or have hypertension or diabetes but has a strong family history of premature coronary disease (his father died of myocardial infarction at age 42). His body mass index is 25 kg/m2. Because he is less than 40 years old, the risk calculator does not apply to him.

If we assume he remains untreated and returns at age 40 with the same clinical factors and laboratory values, his calculated 10-year risk of an ASCVD event according to the new risk calculator will still be only 3.1%. Assuming his medical history remains unchanged as he continues to age, his 10-year risk would not reach 7.5% until he is 58. Would you feel comfortable waiting 33 years before starting statin therapy in this patient?

Waiting for dyslipidemic patients to reach middle age before starting LDL-C-lowering therapy is a failure of prevention. For practical reasons, there are no data from randomized controlled trials with hard outcomes in younger people. Nevertheless, a tenet of preventive cardiology is that cumulative exposure accelerates the “vascular age” ahead of the chronological age. This case illustrates why individualized recommendations guided by LDL-C goals as a target for therapy are needed. For this 25-year-old patient, we would recommend starting an intermediate- or high-potency statin.

Case 5: Rheumatoid arthritis

A 60-year-old postmenopausal white woman with severe rheumatoid arthritis presents for cholesterol evaluation. Her total cholesterol level is 235 mg/dL, HDL-C 50 mg/dL, and LDL-C 165 mg/dL. She does not smoke or have hypertension or diabetes. Her systolic blood pressure is 110 mm Hg. She has elevated C-reactive protein on an ultrasensitive assay and elevated lipoprotein(a).

Her calculated 10-year risk of ASCVD is 3.0%. Assuming her medical history remains the same, she would not reach a calculated 10-year risk of at least 7.5% until age 70. We suggest starting moderate- or high-dose statin therapy in this case, based on data (not from randomized controlled trials) showing an increased risk of ASCVD events in patients with rheumatologic disease, increased lipoprotein(a), and inflammatory markers like C-reactive protein. However, the current guidelines do not address this scenario, other than to suggest that clinician consideration can be given to other risk markers such as these, and that these findings should be discussed in detail with the patient. The Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin trial16 showed a dramatic ASCVD risk reduction in just such patients (Figure 1).

APPLAUSE—AND RESERVATIONS

The newest guidelines for treating high blood cholesterol represent a monumental shift away from using target levels of LDL-C and non-HDL-C and toward a focus on statin intensity for patients in the four highest-risk groups.

We applaud the expert panel for its idealistic approach of using only data from randomized controlled trials, for placing more emphasis on higher-intensity statin treatment, for including stroke in the new definition of ASCVD, and for focusing more attention on treating diabetic patients more aggressively. Simplifying the guidelines is a noble goal. Emphasizing moderate-to-high-intensity statin therapy in patients at moderate-to-high risk should have substantial long-term public health benefits.

However, as we have shown in the case examples, there are significant limitations, and some patients can end up being overtreated, while others may be undertreated.

Guidelines need to be crafted by looking at all the evidence, including the pathophysiology of the disease process, not just data from randomized controlled trials. It is difficult to implement a guideline that on one hand used randomized controlled trials exclusively for recommendations, but on the other hand used an untested risk calculator to guide therapy. Randomized controlled trials are not available for every scenario.

Further, absence of randomized controlled trial data in a given scenario should not be interpreted as evidence of lack of benefit. An example of this is a primary-prevention patient under age 40 with elevated LDL-C below the 190 mg/dL cutoff who otherwise is healthy and without risk factors (eg, Case 4). By disregarding all evidence that is not from randomized controlled trials, the expert panel fails to account for the extensive pathophysiology of ASCVD, which often begins at a young age and takes decades to develop.5,6,39 An entire generation of patients who have not reached the age of inclusion in most randomized controlled trials with hard outcomes is excluded (unless the LDL-C level is very high), potentially setting back decades of progress in the field of prevention. Prevention only works if started. With childhood and young adult obesity sharply rising, we should not fail to address the under-40-year-old patient population in our guidelines.

Guidelines are designed to be expert opinion, not to dictate practice. Focusing on the individual patient instead of the general population at risk, the expert panel appropriately emphasizes the “importance of clinician judgment, weighing potential benefits, adverse effects, drug-drug interactions and patient preferences.” However, by excluding all data that do not come from randomized controlled trials, the panel neglects a very large base of knowledge and leaves many clinicians without as much expert opinion as we had hoped for.

LDL-C goals are important: they provide a scorecard to help the patient with lifestyle and dietary changes. They provide the health care provider guidance in making treatment decisions and focusing on treatment of a single patient, not a population. Moreover, if a patient has difficulty taking standard doses of statins because of side effects, the absence of LDL-C goals makes decision-making nearly impossible. We hope physicians will rely on LDL-C goals in such situations, falling back on the ATP III recommendations, although many patients may simply go untreated until they present with ASCVD or until they “age in” to a higher risk category.

We suggest caution in strict adherence to the new guidelines and instead urge physicians to consider a hybrid of the old guidelines (using the ATP III LDL-C goals) and the new ones (emphasizing global risk assessment and high-intensity statin treatment).

On November 12, 2013, a joint task force for the American College of Cardiology and American Heart Association released new guidelines for treating high blood cholesterol to reduce the risk of atherosclerotic cardiovascular disease (ASCVD) in adults.1

This document arrives after several years of intense deliberation, 12 years after the third Adult Treatment Panel (ATP III) guidelines,2 and 8 years after an ATP III update recommending that low-density lipoprotein cholesterol (LDL-C) levels be lowered aggressively (to less than 70 mg/dL) as an option in patients at high risk.3 It represents a major shift in the approach to and management of high blood cholesterol and has sparked considerable controversy.

In the following commentary, we summarize the new guidelines and the philosophy employed by the task force in generating them. We will also examine some advantages and what we believe to be several shortcomings of the new guidelines. These latter points are illustrated through case examples.

IN RANDOMIZED CONTROLLED TRIALS WE TRUST

In collaboration with the National Heart, Lung, and Blood Institute of the National Institutes of Health, the American College of Cardiology and American Heart Association formed an expert panel task force in 2008.

The task force elected to use only evidence from randomized controlled trials, systematic reviews, and meta-analyses of randomized controlled trials (and only predefined outcomes of the trials, not post hoc analyses) in formulating its recommendations, with the goal of providing the strongest possible evidence.

The authors state that “By using [randomized controlled trial] data to identify those most likely to benefit [emphasis in original] from cholesterol-lowering statin therapy, the recommendations will be of value to primary care clinicians as well as specialists concerned with ASCVD prevention. Importantly, the recommendations were designed to be easy to use in the clinical setting, facilitating the implementation of a strategy of risk assessment and treatment focused on the prevention of ASCVD.”3 They also state the guidelines are meant to “inform clinical judgment, not replace it” and that clinician judgment in addition to discussion with patients remains vital.

During the deliberations, the National Heart, Lung, and Blood Institute removed itself from participating, stating its mission no longer included drafting new guidelines. Additionally, other initial members of the task force removed themselves because of disagreement and concerns about the direction of the new guidelines.

These guidelines, and their accompanying new cardiovascular risk calculator,4 were released without a preliminary period to allow for open discussion, comment, and critique by physicians outside the panel. No attempt was made to harmonize the guidelines with previous versions (eg, ATP III) or with current international guidelines.

WHAT’S NEW IN THE GUIDELINES?

The following are the major changes in the new guidelines for treating high blood cholesterol:

  • Treatment goals for LDL-C and non-high-density lipoprotein cholesterol (non-HDL-C) are no longer recommended.
  • High-intensity and moderate-intensity statin treatment is emphasized, and low-intensity statin therapy is nearly eliminated.
  • “ASCVD” now includes stroke in addition to coronary heart disease and peripheral arterial disease.
  • Four groups are targeted for treatment (see below).
  • Nonstatin therapies have been markedly de-emphasized.
  • No guidelines are provided for treating high triglyceride levels.

The new guidelines emphasize lifestyle modification as the foundation for reducing risk, regardless of cholesterol therapy. No recommendations are given for patients with New York Heart Association class II, III, or IV heart failure or for hemodialysis patients, because there were insufficient data from randomized controlled trials to support recommendations. Similarly, the guidelines apply only to people between the ages of 40 and 75 (risk calculator ages 40–79), because the authors believed there was not enough evidence from randomized controlled trials to allow development of guidelines outside of this age range.

FOUR MAJOR STATIN TREATMENT GROUPS

The new guidelines specify four groups that merit intensive or moderately intensive statin therapy (Table 1)1:

  • People with clinical ASCVD
  • People with LDL-C levels of 190 mg/dL or higher
  • People with diabetes, age 40 to 75
  • People without diabetes, age 40 to 75, with LDL-C levels 70–189 mg/dL, and a 10-year ASCVD risk of 7.5% or higher as determined by the new risk calculator4 (which also calculates the lifetime risk of ASCVD).

Below, we will address each of these four groups and provide case scenarios to consider. In general, our major disagreements with the new recommendations pertain to the first and fourth categories.

 

 

GROUP 1: PEOPLE WITH CLINICAL ASCVD

Advantages of the new guidelines

  • They appropriately recommend statins in the highest tolerated doses as first-line treatment for this group at high risk.
  • They designate all patients with ASCVD, including those with coronary, peripheral, and cerebrovascular disease, as a high-risk group.
  • Without target LDL-C levels, treatment is simpler than before, requiring less monitoring of lipid levels. (This can also be seen as a limitation, as we discuss below.)

Limitations of the new guidelines

  • They make follow-up LDL-C levels irrelevant, seeming to assume that there is no gradation in residual risk and, thus, no need to tailor therapy to the individual.
  • Patients no longer have a goal to strive for or a way to monitor their progress.
  • The guidelines ignore the pathophysiology of coronary artery disease and evidence of residual risk in patients on both moderate-intensity and high-intensity statin therapy.
  • They also ignore the potential benefits of treating to lower LDL-C or non-HDL-C goals, thus eliminating consideration of multidrug therapy. They do not address patients with recurrent cardiovascular events already on maximal tolerated statin doses.
  • They undermine the potential development and use of new therapies for dysplipidemia in patients with ASCVD.

Case 1: Is LDL-C 110 mg/dL low enough?

A 52-year-old African American man presents with newly discovered moderate coronary artery disease that is not severe enough to warrant stenting. He has no history of hypertension, diabetes mellitus, or smoking. His systolic blood pressure is 130 mm Hg, and his body mass index is 26 kg/m2. He exercises regularly and follows a low-cholesterol diet. He has the following fasting lipid values:

  • Total cholesterol 290 mg/dL
  • HDL-C 50 mg/dL
  • Triglycerides 250 mg/dL
  • Calculated LDL-C 190 mg/dL.

Two months later, after beginning atorvastatin 80 mg daily, meeting with a nutritionist, and redoubling his dietary efforts, his fasting lipid concentrations are:

  • Total cholesterol 180 mg/dL
  • HDL-C 55 mg/dL
  • Triglycerides 75 mg/dL
  • Calculated LDL-C 110 mg/dL.

Comment: Lack of LDL-C goals is a flaw

The new guidelines call for patients with known ASCVD, such as this patient, to receive intensive statin therapy—which he got.

However, once a patient is on therapy, the new guidelines do not encourage repeating the lipid panel other than to assess compliance. With intensive therapy, we expect a reduction in LDL-C of at least 50% (Table 1), but patient-to-patient differences in response to medications are common, and without repeat testing we would have no way of gauging this patient’s residual risk.

Further, the new guidelines emphasize the lack of hard outcome data supporting the addition of another lipid-lowering drug to a statin, although they do indicate that one can consider it. In a patient at high risk, such as this one, would you be comfortable with an LDL-C value of 110 mg/dL on maximum statin therapy? Would you consider adding a nonstatin drug?

Figure 1. Scatter plot with best-fit lines of major lipid trials (statin and nonstatin trials) for both primary and secondary prevention of coronary heart disease events. Even though the trials were not designed to show differences based on a target LDL-C level, there is a clear relationship of fewer events with lower LDL-C levels.

A preponderance of data shows that LDL plays a causal role in ASCVD development and adverse events. Genetic data show that the LDL particle and the LDL receptor pathway are mechanistically linked to ASCVD pathogenesis, with lifetime exposure as a critical determinant of risk.5,6 Moreover, randomized controlled trials of statins and other studies of cholesterol-lowering show a reproducible relationship between the LDL-C level achieved and absolute risk (Figure 1).7–24 We believe the totality of data constitutes a strong rationale for targeting LDL-C and establishing goals for lowering its levels. For these reasons, we believe that removing LDL-C goals is a fundamental flaw of the new guidelines.

The reason for the lack of data from randomized controlled trials demonstrating benefits of adding therapies to statins (when LDL-C is still high) or benefits of treating to specific goals is that no such trials have been performed. Even trials of nonpharmacologic means of lowering LDL-C, such as ileal bypass, which was used in the Program on the Surgical Control of the Hyperlipidemias trial,20 provide independent evidence that lowering LDL-C reduces the risk of ASCVD (Figure 1).

In addition, trials of nonstatin drugs, such as the Coronary Drug Project,25 which tested niacin, also showed outcome benefits. On the other hand, studies such as the Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health26 and Treatment of HDL to Reduce the Incidence of Vascular Events27 trials did not show additional risk reduction when niacin was added to statin therapy. However, the study designs arguably had flaws, including requirement of aggressive LDL-lowering with statins, with LDL-C levels below 70 to 80 mg/dL before randomization.

Therefore, these trials do not tell us what to do for a patient on maximal intensive therapy who has recurrent ASCVD events or who, like our patient, has an LDL-C level higher than previous targets.

For this patient, we would recommend adding a second medication to further lower his LDL-C, but discussing with him the absence of proven benefit in clinical trials and the risks of side effects. At present, lacking LDL-C goals in the new guidelines, we are keeping with the ATP III goals to help guide therapeutic choices and individualize patient management.

GROUP 2: PEOPLE WITH LDL-C ≥ 190

Advantages of the new guidelines

  • They state that these patients should receive statins in the highest tolerated doses, which is universally accepted.

Limitations of the new guidelines

  • The new guidelines mention only that one “may consider” adding a second agent if LDL-C remains above 190 mg/dL after maximum-dose therapy. Patients with familial hypercholesterolemia or other severe forms of hypercholesterolemia typically end up on multidrug therapy to further reduce LDL-C. The absence of randomized controlled trial data in this setting to show an additive value of second and third lipid-lowering agents does not mean these agents do not provide benefit.
 

 

GROUP 3: DIABETES, AGE 40–75, LDL-C 70–189, NO CLINICAL ASCVD

Advantages of the new guidelines

  • They call for aggressive treatment of people with diabetes, a group at high risk that derives significant benefit from statin therapy, as shown in randomized controlled trials.

Limitations of the new guidelines

  • Although high-intensity statin therapy is indicated for this group, we believe that, using the new risk calculator, some patients may receive overly aggressive treatment, thus increasing the possibility of statin side effects.
  • The guidelines do not address patients younger than 40 or older than 75.
  • Diabetic patients have a high residual risk of ASCVD events, even on statin therapy. Yet the guidelines ignore the potential benefits of more aggressive LDL-lowering or non-LDL secondary targets for therapy.

Case 2: How low is too low?

A 63-year-old white woman, a nonsmoker with recently diagnosed diabetes, is seen by her primary care physician. She has hypertension, for which she takes lisinopril 5 mg daily. Her fasting lipid values are:

  • Total cholesterol 160 mg/dL
  • HDL-C 64 mg/dL
  • Triglycerides 100 mg/dL
  • Calculated LDL-C 76 mg/dL.

Her systolic blood pressure is 129 mm Hg, and based on the new risk calculator, her 10-year risk of cardiovascular disease is 10.2%. According to the new guidelines, she should be started on high-intensity statin treatment (Table 1).

Although this is an acceptable initial course of action, it necessitates close vigilance, since it may actually drive her LDL-C level too low. Randomized controlled trials have typically used an LDL-C concentration of less than or equal to 25 mg/dL as the safety cutoff. With a typical LDL-C reduction of at least 50% on high-intensity statins, our patient’s expected LDL-C level will likely be in the low 30s. We believe this would be a good outcome, provided that she tolerates the medication without adverse effects. However, responses to statins vary from patient to patient.

High-intensity statin therapy may not be necessary to reduce risk adequately in all patients who have diabetes without preexisting vascular disease. The Collaborative Atorvastatin Diabetes Study12 compared atorvastatin 10 mg vs placebo in people with type 2 diabetes, age 40 to 75, who had one or more cardiovascular risk factors but no signs or symptoms of preexisting ASCVD and who had only average or below-average cholesterol levels—precisely like this patient. The trial was terminated early because of a clear benefit (a 37% reduction in the composite end point of major adverse cardiovascular events) in the intervention group. For our patient, we believe an alternative and acceptable approach would be to begin moderate-intensity statin therapy (eg, with atorvastatin 10 mg) (Table 1).

Alternatively, in a patient with diabetes and previous atherosclerotic vascular disease or with a high 10-year risk and high LDL-C, limiting treatment to high-intensity statin therapy by itself may deny them the potential benefits of combination therapies and targeting to lower LDL-C levels or non-HDL-C secondary targets. Guidelines from the American Diabetes Association28 and the American Association of Clinical Endocrinologists29 continue to recommend an LDL-C goal of less than 70 mg/dL in patients at high risk, a non-HDL-C less than 100 mg/dL, an apolipoprotein B less than 80 mg/dL, and an LDL particle number less than 1,000 nmol/L.

GROUP 4: AGE 40–75, LDL-C 70–189, NO ASCVD, BUT 10-YEAR RISK ≥ 7.5%

Advantages of the new guidelines

  • They may reduce ASCVD events for patients at higher risk.
  • The risk calculator is easy to use and focuses on global risk, ie, all forms of ASCVD.
  • The guidelines promote discussion of risks and benefits between patients and providers.

Limitations of the new guidelines

  • The new risk calculator is controversial (see below).
  • There is potential for overtreatment, particularly in older patients.
  • There is potential for undertreatment, particularly in patients with an elevated LDL-C but whose 10-year risk is less than 7.5% because they are young.
  • The guidelines do not address patients younger than 40 or older than 75.
  • They do not take into account some traditional risk factors, such as family history, and nontraditional risk factors such as C-reactive protein as measured by ultrasensitive assays, lipoprotein(a), and apolipoprotein B.

Risk calculator controversy

The new risk calculator has aroused strong opinions on both sides of the aisle.

Shortly after the new guidelines were released, cardiologists Dr. Paul Ridker and Dr. Nancy Cook from Brigham and Women’s Hospital in Boston published analyses30 showing that the new risk calculator, which was based on older data from several large cohorts such as the Atherosclerosis Risk in Communities study,31 the Cardiovascular Health Study,32 the Coronary Artery Risk Development in Young Adults study,33 and the Framingham Heart Study,34,35 was inaccurate in other cohorts. Specifically, in more-recent cohorts (the Women’s Health Study,36 Physicians’ Health Study,37 and Women’s Health Initiative38), the new calculator overestimates the 10-year risk of ASCVD by 75% to 150%.30 Using the new calculator would make approximately 30 million more Americans eligible for statin treatment. The concern is that patients at lower risk would be treated and exposed to potential side effects of statin therapy.

In addition, the risk calculator relies heavily on age and sex and does not include other factors such as triglyceride level, family history, C-reactive protein, or lipoprotein(a). Importantly, and somewhat ironically given the otherwise absolute adherence to randomized controlled trial data for guideline development, the risk calculator has never been verified in prospective studies to adequately show that using it reduces ASCVD events.

 

 

Case 3: Overtreating a primary prevention patient

Based on the risk calculator, essentially any African American man in his early 60s with no other risk factors has a 10-year risk of ASCVD of 7.5% or higher and, according to the new guidelines, should receive at least moderate-intensity statin therapy.

For example, consider a 64-year-old African American man whose systolic blood pressure is 129 mm Hg, who does not smoke, does not have diabetes, and does not have hypertension, and whose total cholesterol level is 180 mg/dL, HDL-C 70 mg/dL, triglycerides 130 mg/dL, and calculated LDL-C 84 mg/dL. His calculated 10-year risk is, surprisingly, 7.5%.

Alternatively, his twin brother is a two-pack-per-day smoker with untreated hypertension and systolic blood pressure 150 mm Hg, with fasting total cholesterol 153 mg/dL, HDL-C 70 mg/dL, triglycerides 60 mg/dL, and LDL-C 71 mg/dL. His calculated 10-year risk is 10.5%, so according to the new guidelines, he too should receive high-intensity statin therapy. Yet this patient clearly needs better blood pressure control and smoking cessation as his primary risk-reduction efforts, not a statin. While assessing global risk is important, a shortcoming of the new guidelines is that they can inappropriately lead to treating the risk score, not individualizing the treatment to the patient. Because of the errors inherent in the risk calculator, some experts have called for a temporary halt on implementing the new guidelines until the risk calculator can be further validated. In November 2013, the American Heart Association and the American College of Cardiology reaffirmed their support of the new guidelines and recommended that they be implemented as planned. As of the time this manuscript goes to print, there are no plans to halt implementation of the new guidelines.

Case 4: Undertreating a primary prevention patient

A 25-year-old white man with no medical history has a total cholesterol level of 310 mg/dL, HDL-C 50 mg/dL, triglycerides 400 mg/dL, and calculated LDL-C 180 mg/dL. He does not smoke or have hypertension or diabetes but has a strong family history of premature coronary disease (his father died of myocardial infarction at age 42). His body mass index is 25 kg/m2. Because he is less than 40 years old, the risk calculator does not apply to him.

If we assume he remains untreated and returns at age 40 with the same clinical factors and laboratory values, his calculated 10-year risk of an ASCVD event according to the new risk calculator will still be only 3.1%. Assuming his medical history remains unchanged as he continues to age, his 10-year risk would not reach 7.5% until he is 58. Would you feel comfortable waiting 33 years before starting statin therapy in this patient?

Waiting for dyslipidemic patients to reach middle age before starting LDL-C-lowering therapy is a failure of prevention. For practical reasons, there are no data from randomized controlled trials with hard outcomes in younger people. Nevertheless, a tenet of preventive cardiology is that cumulative exposure accelerates the “vascular age” ahead of the chronological age. This case illustrates why individualized recommendations guided by LDL-C goals as a target for therapy are needed. For this 25-year-old patient, we would recommend starting an intermediate- or high-potency statin.

Case 5: Rheumatoid arthritis

A 60-year-old postmenopausal white woman with severe rheumatoid arthritis presents for cholesterol evaluation. Her total cholesterol level is 235 mg/dL, HDL-C 50 mg/dL, and LDL-C 165 mg/dL. She does not smoke or have hypertension or diabetes. Her systolic blood pressure is 110 mm Hg. She has elevated C-reactive protein on an ultrasensitive assay and elevated lipoprotein(a).

Her calculated 10-year risk of ASCVD is 3.0%. Assuming her medical history remains the same, she would not reach a calculated 10-year risk of at least 7.5% until age 70. We suggest starting moderate- or high-dose statin therapy in this case, based on data (not from randomized controlled trials) showing an increased risk of ASCVD events in patients with rheumatologic disease, increased lipoprotein(a), and inflammatory markers like C-reactive protein. However, the current guidelines do not address this scenario, other than to suggest that clinician consideration can be given to other risk markers such as these, and that these findings should be discussed in detail with the patient. The Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin trial16 showed a dramatic ASCVD risk reduction in just such patients (Figure 1).

APPLAUSE—AND RESERVATIONS

The newest guidelines for treating high blood cholesterol represent a monumental shift away from using target levels of LDL-C and non-HDL-C and toward a focus on statin intensity for patients in the four highest-risk groups.

We applaud the expert panel for its idealistic approach of using only data from randomized controlled trials, for placing more emphasis on higher-intensity statin treatment, for including stroke in the new definition of ASCVD, and for focusing more attention on treating diabetic patients more aggressively. Simplifying the guidelines is a noble goal. Emphasizing moderate-to-high-intensity statin therapy in patients at moderate-to-high risk should have substantial long-term public health benefits.

However, as we have shown in the case examples, there are significant limitations, and some patients can end up being overtreated, while others may be undertreated.

Guidelines need to be crafted by looking at all the evidence, including the pathophysiology of the disease process, not just data from randomized controlled trials. It is difficult to implement a guideline that on one hand used randomized controlled trials exclusively for recommendations, but on the other hand used an untested risk calculator to guide therapy. Randomized controlled trials are not available for every scenario.

Further, absence of randomized controlled trial data in a given scenario should not be interpreted as evidence of lack of benefit. An example of this is a primary-prevention patient under age 40 with elevated LDL-C below the 190 mg/dL cutoff who otherwise is healthy and without risk factors (eg, Case 4). By disregarding all evidence that is not from randomized controlled trials, the expert panel fails to account for the extensive pathophysiology of ASCVD, which often begins at a young age and takes decades to develop.5,6,39 An entire generation of patients who have not reached the age of inclusion in most randomized controlled trials with hard outcomes is excluded (unless the LDL-C level is very high), potentially setting back decades of progress in the field of prevention. Prevention only works if started. With childhood and young adult obesity sharply rising, we should not fail to address the under-40-year-old patient population in our guidelines.

Guidelines are designed to be expert opinion, not to dictate practice. Focusing on the individual patient instead of the general population at risk, the expert panel appropriately emphasizes the “importance of clinician judgment, weighing potential benefits, adverse effects, drug-drug interactions and patient preferences.” However, by excluding all data that do not come from randomized controlled trials, the panel neglects a very large base of knowledge and leaves many clinicians without as much expert opinion as we had hoped for.

LDL-C goals are important: they provide a scorecard to help the patient with lifestyle and dietary changes. They provide the health care provider guidance in making treatment decisions and focusing on treatment of a single patient, not a population. Moreover, if a patient has difficulty taking standard doses of statins because of side effects, the absence of LDL-C goals makes decision-making nearly impossible. We hope physicians will rely on LDL-C goals in such situations, falling back on the ATP III recommendations, although many patients may simply go untreated until they present with ASCVD or until they “age in” to a higher risk category.

We suggest caution in strict adherence to the new guidelines and instead urge physicians to consider a hybrid of the old guidelines (using the ATP III LDL-C goals) and the new ones (emphasizing global risk assessment and high-intensity statin treatment).

References
  1. Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2013; published online Nov 13. DOI: 10.1016/j.jacc.2013.11.002.
  2. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002; 106:3143–3421.
  3. Grundy SM, Cleeman JI, Merz CN, et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Circulation 2004; 110:227–239.
  4. American Heart Association. 2013 Prevention guidelines tools. CV risk calculator. http://my.americanheart.org/professional/StatementsGuidelines/PreventionGuidelines/Prevention-Guidelines_UCM_457698_SubHomePage.jsp. Accessed December 10, 2013.
  5. Goldstein JL, Brown MS. The LDL receptor. Arterioscler Thromb Vasc Biol 2009; 29:431–438.
  6. Horton JD, Cohen JC, Hobbs HH. PCSK9: a convertase that coordinates LDL catabolism. J Lipid Res 2009; 50(suppl):S172–S177.
  7. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet 1994; 344:1383–1389.
  8. de Lemos JA, Blazing MA, Wiviott SD, et al; for the A to Z Investigators. Early intensive vs a delayed conservative simvastatin strategy in patients with acute coronary syndromes. Phase Z of the A to Z trial. JAMA 2004; 292:1307–1316.
  9. Downs JR, Clearfield M, Weis S, et al; for the AFCAPS/TexCAPS Research Group. Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels. Results of AFCAPS/TexCAPS. JAMA 1998; 279:1615–1622.
  10. Koren MJ, Hunninghake DB, on behalf of the ALLIANCE investigators. Clinical outcomes in managed-care patients with coronary heart disease treated aggressively in lipid-lowering disease management clinics. J Am Coll Cardiol 2004; 44:1772–1779.
  11. Sever PS, Dahlof B, Poulter NR, et al; ASCOT investigators. Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial - Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial. Lancet 2003; 361:1149–1158.
  12. Colhoun HM, Betteridge DJ, Durrington PN, et al; on behalf of the CARDS Investigators. Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomised placebo-controlled trial. Lancet 2004; 364:685–696.
  13. Sacks FM, Pfeffer MA, Moye LA, et al; for the Cholesterol and Recurrent Events Trial Investigators. The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels. N Engl J Med 1996; 335:1001–1009.
  14. Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20 536 high-risk individuals: a randomised placebo-controlled trial. Lancet 2002; 360:7–22.
  15. Pedersen TR, Faegeman O, Kastelein JJ, et al. Incremental Decrease in End Points Through Aggressive Lipid Lowering Study Group. High-dose atorvastatin vs usual-dose simvastatin for secondary prevention after myocardial infarction: the IDEAL study: a randomized controlled trial. JAMA 2005; 294:2437–2445.
  16. Ridker PM, Danielson E, Fonseca FAH, et al; for the JUPITER Study Group. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008; 359:2195–2207.
  17. LIPID Study Group. Prevention of cardiovascular events and death with pravastatin in patients with coronary heart disease and a broad range of initial cholesterol levels. N Engl J Med 1998; 339:1349–1357.
  18. Nakamura H, Arakawa K, Itakura H, et al; for the MEGA Study Group. Primary prevention of cardiovascular disease with pravastatin Japan (MEGA Study): a prospective rabndomised controlled trial. Lancet 2006; 368:1155–1163.
  19. Schwartz GG, Olsson AG, Ezekowitz MD, et al. Myocardial Ischemia Reduction with Aggreessive Cholesterol Lowering (MIRACL) Study Investigators. Effects of atorvastatin on early recurrent ischemic events in acute coronary syndromes: the MIRACL study: a randomized controlled trial. JAMA 2001; 285:1711–1718.
  20. Buchwald H, Varco RL, Matts JP, et al. Effect of partial ileal bypass surgery on mortality and morbidity from coronary heart disease in patients with hypercholesterolemia: report of the Program on the Surgical Control of the Hyperlipidemias (POSCH). N Engl J Med 1990; 323:946–955.
  21. Cannon CP, Braunwald E, McCabe CH, et al; for the Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 Investigators. Intensive versus moderate lipid lowering with statins after acute coronary syndromes. N Engl J Med 2004; 350:1495–1504.
  22. Baigent C, Landray MJ, Reith C, et al; SHARP Investigators. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial. Lancet 2011; 377:2181–2192.
  23. LaRosa JC, Grundy SM, Waters DD, et al. Intensive lipid lowering with atorvastatin in patients with stable coronary disease. N Engl J Med 2005; 352:1425–1435.
  24. Shepherd J, Cobbe SM, Ford I, et al; for the West of Scotland Coronary Prevention Study Group. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. N Engl J Med 1995; 333:1301–1308.
  25. Canner PL, Berge KG, Wenger NK, et al. Fifteen year mortality in Coronary Drug Project patients: long-term benefit with niacin. J Am Coll Cardiol 1989; 8:1245–1255.
  26. AIM-HIGH Investigators, Boden WE, Probstfield JL, Anderson T, et al.  Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. N Engl J Med 2011; 365:2255–2267.
  27. HPS2-Thrive Collaborative Group. HPS2-THRIVE randomized placebo-controlled trial in 25 673 high-risk patients of ER niacin/laropiprant: trial design, pre-specified muscle and liver outcomes, and reasons for stopping study treatment. Eur Heart J 2013; 34:1279–1291.
  28. American Diabetes Association. Standards of medical care in diabetes—2013. Diabetes Care 2013; 36(suppl 1):S11–S66.
  29. Garber AJ, Abrahamson MJ, Barzilay JI, et al. American Association of Clinical Endocrinologists’comprehensive diabetes management algorithm 2013 consensus statement—executive summary. Endocr Pract 2013; 19:536–557.
  30. Ridker PM, Cook NR. Statins: new American guidelines for prevention of cardiovascular disease. Lancet 2013doi: 10.1016/S0140-6736(13)62388-0. [Epub ahead of print]
  31. The ARIC investigators. The Atherosclerosis Risk in Communities (ARIC) study: design and objectives. Am J Epidemiol 1989; 129:687–702.
  32. Fried LP, Borhani NO, Enright P, et al. The Cardiovascular Health Study: design and rationale. Ann Epidemiol 1991; 1:263–276.
  33. Friedman GD, Cutter GR, Donahue RP, et al. CARDIA: study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988; 41:1105–1116.
  34. Dawber TR, Kannel WB, Lyell LP. An approach to longitudinal studies in a community: the Framingham study. Ann N Y Acad Sci 1963; 107:539–556.
  35. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families. The Framingham offspring study. Am J Epidemiol 1979; 110:281–290.
  36. Ridker PM, Cook NR, Lee IM, et al. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. N Engl J Med 2005; 352:1293–1304.
  37. Belancer C, Buring JE, Cook N, et al; The Steering Committee of the Physicians’ Health Study Research Group. Final report on the aspirin component of the ongoing Physicians’ Health Study. N Engl J Med 1989; 321:129–135.
  38. Langer R, White E, Lewis C, et al. The Women’s Health Initiative Observational Study: baseline characteristics of participants and reliability of baseline measures. Ann Epidemiol 2003; 13:S107–S121.
  39. Strong JP, Malcom GT, Oalmann MC, Wissler RW. The PDAY study: natural history, risk factors, and pathobiology. Ann N Y Acad Sci 1997; 811:226–235.
References
  1. Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2013; published online Nov 13. DOI: 10.1016/j.jacc.2013.11.002.
  2. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002; 106:3143–3421.
  3. Grundy SM, Cleeman JI, Merz CN, et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Circulation 2004; 110:227–239.
  4. American Heart Association. 2013 Prevention guidelines tools. CV risk calculator. http://my.americanheart.org/professional/StatementsGuidelines/PreventionGuidelines/Prevention-Guidelines_UCM_457698_SubHomePage.jsp. Accessed December 10, 2013.
  5. Goldstein JL, Brown MS. The LDL receptor. Arterioscler Thromb Vasc Biol 2009; 29:431–438.
  6. Horton JD, Cohen JC, Hobbs HH. PCSK9: a convertase that coordinates LDL catabolism. J Lipid Res 2009; 50(suppl):S172–S177.
  7. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet 1994; 344:1383–1389.
  8. de Lemos JA, Blazing MA, Wiviott SD, et al; for the A to Z Investigators. Early intensive vs a delayed conservative simvastatin strategy in patients with acute coronary syndromes. Phase Z of the A to Z trial. JAMA 2004; 292:1307–1316.
  9. Downs JR, Clearfield M, Weis S, et al; for the AFCAPS/TexCAPS Research Group. Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levels. Results of AFCAPS/TexCAPS. JAMA 1998; 279:1615–1622.
  10. Koren MJ, Hunninghake DB, on behalf of the ALLIANCE investigators. Clinical outcomes in managed-care patients with coronary heart disease treated aggressively in lipid-lowering disease management clinics. J Am Coll Cardiol 2004; 44:1772–1779.
  11. Sever PS, Dahlof B, Poulter NR, et al; ASCOT investigators. Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial - Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial. Lancet 2003; 361:1149–1158.
  12. Colhoun HM, Betteridge DJ, Durrington PN, et al; on behalf of the CARDS Investigators. Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomised placebo-controlled trial. Lancet 2004; 364:685–696.
  13. Sacks FM, Pfeffer MA, Moye LA, et al; for the Cholesterol and Recurrent Events Trial Investigators. The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels. N Engl J Med 1996; 335:1001–1009.
  14. Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20 536 high-risk individuals: a randomised placebo-controlled trial. Lancet 2002; 360:7–22.
  15. Pedersen TR, Faegeman O, Kastelein JJ, et al. Incremental Decrease in End Points Through Aggressive Lipid Lowering Study Group. High-dose atorvastatin vs usual-dose simvastatin for secondary prevention after myocardial infarction: the IDEAL study: a randomized controlled trial. JAMA 2005; 294:2437–2445.
  16. Ridker PM, Danielson E, Fonseca FAH, et al; for the JUPITER Study Group. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008; 359:2195–2207.
  17. LIPID Study Group. Prevention of cardiovascular events and death with pravastatin in patients with coronary heart disease and a broad range of initial cholesterol levels. N Engl J Med 1998; 339:1349–1357.
  18. Nakamura H, Arakawa K, Itakura H, et al; for the MEGA Study Group. Primary prevention of cardiovascular disease with pravastatin Japan (MEGA Study): a prospective rabndomised controlled trial. Lancet 2006; 368:1155–1163.
  19. Schwartz GG, Olsson AG, Ezekowitz MD, et al. Myocardial Ischemia Reduction with Aggreessive Cholesterol Lowering (MIRACL) Study Investigators. Effects of atorvastatin on early recurrent ischemic events in acute coronary syndromes: the MIRACL study: a randomized controlled trial. JAMA 2001; 285:1711–1718.
  20. Buchwald H, Varco RL, Matts JP, et al. Effect of partial ileal bypass surgery on mortality and morbidity from coronary heart disease in patients with hypercholesterolemia: report of the Program on the Surgical Control of the Hyperlipidemias (POSCH). N Engl J Med 1990; 323:946–955.
  21. Cannon CP, Braunwald E, McCabe CH, et al; for the Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 Investigators. Intensive versus moderate lipid lowering with statins after acute coronary syndromes. N Engl J Med 2004; 350:1495–1504.
  22. Baigent C, Landray MJ, Reith C, et al; SHARP Investigators. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial. Lancet 2011; 377:2181–2192.
  23. LaRosa JC, Grundy SM, Waters DD, et al. Intensive lipid lowering with atorvastatin in patients with stable coronary disease. N Engl J Med 2005; 352:1425–1435.
  24. Shepherd J, Cobbe SM, Ford I, et al; for the West of Scotland Coronary Prevention Study Group. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. N Engl J Med 1995; 333:1301–1308.
  25. Canner PL, Berge KG, Wenger NK, et al. Fifteen year mortality in Coronary Drug Project patients: long-term benefit with niacin. J Am Coll Cardiol 1989; 8:1245–1255.
  26. AIM-HIGH Investigators, Boden WE, Probstfield JL, Anderson T, et al.  Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. N Engl J Med 2011; 365:2255–2267.
  27. HPS2-Thrive Collaborative Group. HPS2-THRIVE randomized placebo-controlled trial in 25 673 high-risk patients of ER niacin/laropiprant: trial design, pre-specified muscle and liver outcomes, and reasons for stopping study treatment. Eur Heart J 2013; 34:1279–1291.
  28. American Diabetes Association. Standards of medical care in diabetes—2013. Diabetes Care 2013; 36(suppl 1):S11–S66.
  29. Garber AJ, Abrahamson MJ, Barzilay JI, et al. American Association of Clinical Endocrinologists’comprehensive diabetes management algorithm 2013 consensus statement—executive summary. Endocr Pract 2013; 19:536–557.
  30. Ridker PM, Cook NR. Statins: new American guidelines for prevention of cardiovascular disease. Lancet 2013doi: 10.1016/S0140-6736(13)62388-0. [Epub ahead of print]
  31. The ARIC investigators. The Atherosclerosis Risk in Communities (ARIC) study: design and objectives. Am J Epidemiol 1989; 129:687–702.
  32. Fried LP, Borhani NO, Enright P, et al. The Cardiovascular Health Study: design and rationale. Ann Epidemiol 1991; 1:263–276.
  33. Friedman GD, Cutter GR, Donahue RP, et al. CARDIA: study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988; 41:1105–1116.
  34. Dawber TR, Kannel WB, Lyell LP. An approach to longitudinal studies in a community: the Framingham study. Ann N Y Acad Sci 1963; 107:539–556.
  35. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families. The Framingham offspring study. Am J Epidemiol 1979; 110:281–290.
  36. Ridker PM, Cook NR, Lee IM, et al. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. N Engl J Med 2005; 352:1293–1304.
  37. Belancer C, Buring JE, Cook N, et al; The Steering Committee of the Physicians’ Health Study Research Group. Final report on the aspirin component of the ongoing Physicians’ Health Study. N Engl J Med 1989; 321:129–135.
  38. Langer R, White E, Lewis C, et al. The Women’s Health Initiative Observational Study: baseline characteristics of participants and reliability of baseline measures. Ann Epidemiol 2003; 13:S107–S121.
  39. Strong JP, Malcom GT, Oalmann MC, Wissler RW. The PDAY study: natural history, risk factors, and pathobiology. Ann N Y Acad Sci 1997; 811:226–235.
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(Re)turning the pages of residency: The impact of localizing resident physicians to hospital units on paging frequency

It's hard to imagine a busy urban hospital without its chorus of beepers.[1] This statement, the first sentence of an article published in 1988, rings (or beeps or buzzes) true to any resident physician today. At that time, pagers had replaced overhead paging, and provided a rapid method to contact physicians who were often scattered throughout the hospital. Still, it was an imperfect solution as the ubiquitous pager constantly interrupted patient care and other tasks, failed to prioritize information, and added to an already stressful working environment. Notably, interns were paged on average once per hour, and occasionally 5 or more times per hour, a frequency that was felt to be detrimental to patient care and to the working environment of resident physicians.[1]

Little has changed. Despite the instant, multidirectional communication platforms available today, alphanumeric paging remains a mainstay of communication between physicians and other members of the care team. Importantly, paging contributes to communication errors (eg, by failing to convey urgency, having incomplete information, or being missed entirely by coverage gaps),[2, 3] and interrupts resident workflow, thereby negatively affecting work efficiency and educational activities, and adding to perceived workload.[4, 5]

In this era of duty hour restrictions, there has been concern that residents experience increased workload due to having fewer hours to do the same amount of work.[6, 7] As such, the Accreditation Council of Graduate Medical Education emphasizes the quality of those hours, with a focus on several aspects of the resident working environment as key to improved educational and patient safety outcomes.[8, 9, 10]

Geographic localization of physicians to patient care units has been proposed as a means to improve communication and agreement on plans of care,[11, 12] and also to reduce resident workload by decreasing inefficiencies attributable to traveling throughout the hospital.[13] O'Leary, et al. (2009) found that when physicians were localized to 1 hospital unit, there was greater agreement between physicians and nurses on various aspects of care, such as planned tests and anticipated length of stay. In addition, members of the patient care team were better able to identify one another, and there was a perceived increase in face‐to‐face communication, and a perceived decrease in text paging.[11]

In consideration of these factors, in July 2011, at New YorkPresbyterian Hospital/Weill Cornell (NYPH/WC), an 800‐bed tertiary care teaching hospital in New York, New York, we geographically localized 2 internal medicine resident teams, and partially localized 2 additional teams. We investigated whether interns on teams that were geographically localized received fewer pages than interns on teams that were not localized. This study was reviewed by the institutional review board of Weill Cornell Medical College and met the requirements for exemption.

METHODS

We conducted a retrospective analysis of the number of pages received by interns during the day (7:00 am to 7:00 pm) on 5 general internal medicine teams during a 1‐month ward rotation between October 17, 2011 and November 13, 2011 at NYPH/WC. The general medicine teams were composed of 1 attending, 1 resident, and 2 interns each. Two teams were geographically localized to a 32‐bed unit (geographic localization model [GLM]). Two teams were partially localized to a 26‐bed unit, which included a respiratory care step‐down unit (partial localization model [PLM]). A fifth and final team admitted patients irrespective of their assigned bed location (standard model [SM]). Both the GLM and the PLM occasionally carried patients on other units to allow for overall census management and patient throughput. The total number of pages received by each intern over the study period was collected by retrospective analysis of electronic paging logs. Night pages (7 pm7 am) were excluded because of night float coverage. Weekend pages were excluded because data were inaccurate due to coverage for days off.

The daily number of admissions and daily census per team were recorded by physician assistants, who also assigned new patients to appropriate teams according to an admissions algorithm (see Supporting Figure 1 in the online version of this article). The percent of geographically localized patients on each team was estimated from the percentage of localized patients on the day of discharge averaged over the study period. For the SM team, percent localization was defined as the number of patients on the patient care unit that contained the team's work area.

Figure 1
Average number of pages per intern per hour for each care model. Abbreviations: GLM, geographically localized model; PLM, partial localization model; SM, standard model.

Standard multivariate linear regression techniques were used to analyze the relationship between the number of pages received per intern and the type of team, controlling for the potential effect of total census and number of admissions. The regression model was used to determine adjusted marginal point estimates and 95% confidence intervals (CIs) for the average number of pages per intern per hour for each type of team. All statistical analyses were conducted using Stata version 12 (StataCorp, College Station, TX).

RESULTS

Over the 28‐day study period, a total of 6652 pages were received by 10 interns on 5 general internal medicine teams from 7 am to 7 pm Monday through Friday. The average daily census, average daily admissions, and percent of patients localized to patient care units for the individual teams are shown in Table 1. In univariate analysis, the mean daily pages per intern were not significantly different between the 2 teams within the GLM, nor between the 2 teams in the PLM, allowing them to be combined in multivariate analysis (data not shown). The number of pages received per intern per hour, adjusted for team census and number of admissions, was 2.2 (95% CI: 2.02.4) in the GLM, 2.8 (95% CI: 2.6‐3.0) in the PLM, and 3.9 (95% CI: 3.6‐4.2) in the SM (Table 1). All of these differences were statistically significant (P<0.001).

Geographic Distribution, Census, Admissions, and Pages per Hour per Intern for Each Patient Care Model During the Study Period
Standard Model* Partial Localization Model Geographically Localized Model
  • NOTE: Abbreviations: CI, confidence interval. *One general medicine team in the standard model, and 2 each in the partial localization model and geographically localized model, with 2 interns per team.

Percent of patients localized 37% 45% 85%
Team census, mean (range per day) 16.1 (1320) 15.9 (1120) 15.6 (1119)
Team admissions, mean (range per day) 2.7 (15) 2.9 (06) 3.5 (07)
Pages per hour per intern, unadjusted, mean (95% CI) 3.9 (3.6‐4.1) 2.8 (2.6‐3.0) 2.2 (2.02.4)
Pages per hour per intern, adjusted for census and admissions, mean (95% CI) 3.9 (3.6‐4.2) 2.8 (2.6‐3.0) 2.2 (2.02.4)

Figure 1 shows the pattern of daytime paging for each model. The GLM and PLM had a similar pattern, with an initial ramp up in the first 2 hours of the day, holding steady until approximately 4 pm, and then decrease until 7 pm. The SM had a steeper initial rise, and then continued to increase slowly until a peak at 4 pm.

DISCUSSION

This study corroborates that of Singh et al. (2012), who found that geographic localization led to significantly fewer pages.[14] Our results strengthen the evidence by demonstrating that even modest differences between the percent of patients localized to a care unit led to a significant decrease in the number of pages, indicating a dose‐response effect. The paging frequency we measured is higher than described in Singh et al. (1.4 pages per hour for localized teams), yet our average census appears to be 4 patients higher, which may account for some of that difference. We also show that interns on teams whose patients are more widely scattered throughout the hospital may experience upward of 5 pages per hour, an interruption by pager every 12 minutes, all day long.

A pager interruption is not solely limited to a disruption by noxious sound or vibration. The page recipient must then read the page and respond accordingly, which may involve a phone call, placing an order, walking to another location, or other work tasks. Although some of these interruptions must be handled immediately, such as a clinically deteriorating patient, many are not urgent, and could wait until the physician's current task or thought process is complete. There is also the potentially risky assumption on the part of the sender that the message has been received and will be acted upon. Furthermore, frequent paging is a common interruption to physician workflow; interruptions contribute to increased perceived physician workload[4, 5] and are likely detrimental to patient safety.[15, 16]

The most common metrics used to measure resident workload are patient census and number of admissions,[13] but these metrics have provided a mixed and likely incomplete picture. Recent research suggests that other factors, such as work efficiency (including interruptions, time spent obtaining test results, and time in transit) and work intensity (such as the acuity and complexity of patients), contribute significantly to actual and perceived resident workload.[13]

Our analysis was a single‐site, retrospective study, which occurred over 1 month and was limited to internal medicine teams. Additionally, geographic localization logically should lead to increased face‐to‐face interruptions, which we were unable to measure with this project, but direct communication is more efficient and less prone to error, which would likely lead to fewer overall interruptions. Although we anticipate that our findings are applicable to geographically localized patient care units in other hospitals, further investigation is warranted.

The paging chorus has only grown louder over the last 25 years, with likely downstream effects on patient safety and resident education. To mitigate these effects, it is incumbent upon us to approach our training and patient care environments with a critical and creative lens, and to explore opportunities to decrease interruptions and streamline our communication systems.

Acknowledgements

The authors acknowledge the assistance with data analysis of Arthur Evans, MD, MPH, and review of the manuscript by Brendan Reilly, MD.

Disclosures: Dr. Fanucchi and Ms. Unterbrink have no conflicts of interest to disclose. Dr. Logio reports receiving royalties from McGraw‐Hill for Core Concepts in Patient Safety online modules.

Files
References
  1. Katz MH, Schroeder SA. The sounds of the hospital. Paging patterns in three teaching hospitals. N Engl J Med. 1988;319(24):15851589.
  2. Sutcliffe KM, Lewton E, Rosenthal MM. Communication failures: an insidious contributor to medical mishaps. Acad Med. 2004;79(2):186194.
  3. Espino S, Cox D, Kaplan B. Alphanumeric paging: a potential source of problems in patient care and communication. J Surg Educ. 2011;68(6):447451.
  4. Weigl M, Muller A, Zupanc A, Glaser J, Angerer P. Hospital doctors' workflow interruptions and activities: an observation study. BMJ Qual Saf. 2011;20(6):491497.
  5. Weigl M, Muller A, Vincent C, Angerer P, Sevdalis N. The association of workflow interruptions and hospital doctors' workload: a prospective observational study. BMJ Qual Saf. 2012;21(5):399407.
  6. Goitein L, Ludmerer KM. Resident workload—let's treat the disease, not just the symptom. Comment on: Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff. JAMA Intern Med. 2013;173(8):655656.
  7. Desai SV, Feldman L, Brown L, et al. Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med. 2013;173(8):649655.
  8. Philibert I, Amis S. The ACGME 2011 Duty Hour Standards: Enhancing Quality of Care, Supervision, and Resident Professional Development. Chicago, IL: Accreditation Council for Graduate Medical Education; 2011.
  9. Ulmer C, Wolman D, Johns M, eds . Institute of Medicine Resident Duty Hours: Enhancing Sleep, Supervision, and Safety. Washington, DC: National Academies Press; 2009.
  10. Schumacher DJ, Slovin SR, Riebschleger MP, Englander R, Hicks PJ, Carraccio C. Perspective: beyond counting hours: the importance of supervision, professionalism, transitions of care, and workload in residency training. Acad Med. 2012;87(7):883888.
  11. O'Leary KJ, Wayne DB, Landler MP, et al. Impact of localizing physicians to hospital units on nurse‐physician communication and agreement on the plan of care. J Gen Intern Med. 2009;24(11):12231227.
  12. Gordon MB, Melvin P, Graham D, et al. Unit‐based care teams and the frequency and quality of physician‐nurse communications. Arch Pediatr Adolesc Med. 2011;165(5):424428.
  13. Thanarajasingam U, McDonald FS, Halvorsen AJ, et al. Service census caps and unit‐based admissions: resident workload, conference attendance, duty hour compliance, and patient safety. Mayo Clin Proc. 2012;87(4):320327.
  14. Singh S, Tarima S, Rana V, et al. Impact of localizing general medical teams to a single nursing unit. J Hosp Med. 2012;7(7):551556.
  15. Coiera E. The science of interruption. BMJ Qual Saf. 2012;21(5):357360.
  16. Westbrook JI, Coiera E, Dunsmuir WT, et al. The impact of interruptions on clinical task completion. Qual Saf Health Care. 2010;19(4):284289.
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It's hard to imagine a busy urban hospital without its chorus of beepers.[1] This statement, the first sentence of an article published in 1988, rings (or beeps or buzzes) true to any resident physician today. At that time, pagers had replaced overhead paging, and provided a rapid method to contact physicians who were often scattered throughout the hospital. Still, it was an imperfect solution as the ubiquitous pager constantly interrupted patient care and other tasks, failed to prioritize information, and added to an already stressful working environment. Notably, interns were paged on average once per hour, and occasionally 5 or more times per hour, a frequency that was felt to be detrimental to patient care and to the working environment of resident physicians.[1]

Little has changed. Despite the instant, multidirectional communication platforms available today, alphanumeric paging remains a mainstay of communication between physicians and other members of the care team. Importantly, paging contributes to communication errors (eg, by failing to convey urgency, having incomplete information, or being missed entirely by coverage gaps),[2, 3] and interrupts resident workflow, thereby negatively affecting work efficiency and educational activities, and adding to perceived workload.[4, 5]

In this era of duty hour restrictions, there has been concern that residents experience increased workload due to having fewer hours to do the same amount of work.[6, 7] As such, the Accreditation Council of Graduate Medical Education emphasizes the quality of those hours, with a focus on several aspects of the resident working environment as key to improved educational and patient safety outcomes.[8, 9, 10]

Geographic localization of physicians to patient care units has been proposed as a means to improve communication and agreement on plans of care,[11, 12] and also to reduce resident workload by decreasing inefficiencies attributable to traveling throughout the hospital.[13] O'Leary, et al. (2009) found that when physicians were localized to 1 hospital unit, there was greater agreement between physicians and nurses on various aspects of care, such as planned tests and anticipated length of stay. In addition, members of the patient care team were better able to identify one another, and there was a perceived increase in face‐to‐face communication, and a perceived decrease in text paging.[11]

In consideration of these factors, in July 2011, at New YorkPresbyterian Hospital/Weill Cornell (NYPH/WC), an 800‐bed tertiary care teaching hospital in New York, New York, we geographically localized 2 internal medicine resident teams, and partially localized 2 additional teams. We investigated whether interns on teams that were geographically localized received fewer pages than interns on teams that were not localized. This study was reviewed by the institutional review board of Weill Cornell Medical College and met the requirements for exemption.

METHODS

We conducted a retrospective analysis of the number of pages received by interns during the day (7:00 am to 7:00 pm) on 5 general internal medicine teams during a 1‐month ward rotation between October 17, 2011 and November 13, 2011 at NYPH/WC. The general medicine teams were composed of 1 attending, 1 resident, and 2 interns each. Two teams were geographically localized to a 32‐bed unit (geographic localization model [GLM]). Two teams were partially localized to a 26‐bed unit, which included a respiratory care step‐down unit (partial localization model [PLM]). A fifth and final team admitted patients irrespective of their assigned bed location (standard model [SM]). Both the GLM and the PLM occasionally carried patients on other units to allow for overall census management and patient throughput. The total number of pages received by each intern over the study period was collected by retrospective analysis of electronic paging logs. Night pages (7 pm7 am) were excluded because of night float coverage. Weekend pages were excluded because data were inaccurate due to coverage for days off.

The daily number of admissions and daily census per team were recorded by physician assistants, who also assigned new patients to appropriate teams according to an admissions algorithm (see Supporting Figure 1 in the online version of this article). The percent of geographically localized patients on each team was estimated from the percentage of localized patients on the day of discharge averaged over the study period. For the SM team, percent localization was defined as the number of patients on the patient care unit that contained the team's work area.

Figure 1
Average number of pages per intern per hour for each care model. Abbreviations: GLM, geographically localized model; PLM, partial localization model; SM, standard model.

Standard multivariate linear regression techniques were used to analyze the relationship between the number of pages received per intern and the type of team, controlling for the potential effect of total census and number of admissions. The regression model was used to determine adjusted marginal point estimates and 95% confidence intervals (CIs) for the average number of pages per intern per hour for each type of team. All statistical analyses were conducted using Stata version 12 (StataCorp, College Station, TX).

RESULTS

Over the 28‐day study period, a total of 6652 pages were received by 10 interns on 5 general internal medicine teams from 7 am to 7 pm Monday through Friday. The average daily census, average daily admissions, and percent of patients localized to patient care units for the individual teams are shown in Table 1. In univariate analysis, the mean daily pages per intern were not significantly different between the 2 teams within the GLM, nor between the 2 teams in the PLM, allowing them to be combined in multivariate analysis (data not shown). The number of pages received per intern per hour, adjusted for team census and number of admissions, was 2.2 (95% CI: 2.02.4) in the GLM, 2.8 (95% CI: 2.6‐3.0) in the PLM, and 3.9 (95% CI: 3.6‐4.2) in the SM (Table 1). All of these differences were statistically significant (P<0.001).

Geographic Distribution, Census, Admissions, and Pages per Hour per Intern for Each Patient Care Model During the Study Period
Standard Model* Partial Localization Model Geographically Localized Model
  • NOTE: Abbreviations: CI, confidence interval. *One general medicine team in the standard model, and 2 each in the partial localization model and geographically localized model, with 2 interns per team.

Percent of patients localized 37% 45% 85%
Team census, mean (range per day) 16.1 (1320) 15.9 (1120) 15.6 (1119)
Team admissions, mean (range per day) 2.7 (15) 2.9 (06) 3.5 (07)
Pages per hour per intern, unadjusted, mean (95% CI) 3.9 (3.6‐4.1) 2.8 (2.6‐3.0) 2.2 (2.02.4)
Pages per hour per intern, adjusted for census and admissions, mean (95% CI) 3.9 (3.6‐4.2) 2.8 (2.6‐3.0) 2.2 (2.02.4)

Figure 1 shows the pattern of daytime paging for each model. The GLM and PLM had a similar pattern, with an initial ramp up in the first 2 hours of the day, holding steady until approximately 4 pm, and then decrease until 7 pm. The SM had a steeper initial rise, and then continued to increase slowly until a peak at 4 pm.

DISCUSSION

This study corroborates that of Singh et al. (2012), who found that geographic localization led to significantly fewer pages.[14] Our results strengthen the evidence by demonstrating that even modest differences between the percent of patients localized to a care unit led to a significant decrease in the number of pages, indicating a dose‐response effect. The paging frequency we measured is higher than described in Singh et al. (1.4 pages per hour for localized teams), yet our average census appears to be 4 patients higher, which may account for some of that difference. We also show that interns on teams whose patients are more widely scattered throughout the hospital may experience upward of 5 pages per hour, an interruption by pager every 12 minutes, all day long.

A pager interruption is not solely limited to a disruption by noxious sound or vibration. The page recipient must then read the page and respond accordingly, which may involve a phone call, placing an order, walking to another location, or other work tasks. Although some of these interruptions must be handled immediately, such as a clinically deteriorating patient, many are not urgent, and could wait until the physician's current task or thought process is complete. There is also the potentially risky assumption on the part of the sender that the message has been received and will be acted upon. Furthermore, frequent paging is a common interruption to physician workflow; interruptions contribute to increased perceived physician workload[4, 5] and are likely detrimental to patient safety.[15, 16]

The most common metrics used to measure resident workload are patient census and number of admissions,[13] but these metrics have provided a mixed and likely incomplete picture. Recent research suggests that other factors, such as work efficiency (including interruptions, time spent obtaining test results, and time in transit) and work intensity (such as the acuity and complexity of patients), contribute significantly to actual and perceived resident workload.[13]

Our analysis was a single‐site, retrospective study, which occurred over 1 month and was limited to internal medicine teams. Additionally, geographic localization logically should lead to increased face‐to‐face interruptions, which we were unable to measure with this project, but direct communication is more efficient and less prone to error, which would likely lead to fewer overall interruptions. Although we anticipate that our findings are applicable to geographically localized patient care units in other hospitals, further investigation is warranted.

The paging chorus has only grown louder over the last 25 years, with likely downstream effects on patient safety and resident education. To mitigate these effects, it is incumbent upon us to approach our training and patient care environments with a critical and creative lens, and to explore opportunities to decrease interruptions and streamline our communication systems.

Acknowledgements

The authors acknowledge the assistance with data analysis of Arthur Evans, MD, MPH, and review of the manuscript by Brendan Reilly, MD.

Disclosures: Dr. Fanucchi and Ms. Unterbrink have no conflicts of interest to disclose. Dr. Logio reports receiving royalties from McGraw‐Hill for Core Concepts in Patient Safety online modules.

It's hard to imagine a busy urban hospital without its chorus of beepers.[1] This statement, the first sentence of an article published in 1988, rings (or beeps or buzzes) true to any resident physician today. At that time, pagers had replaced overhead paging, and provided a rapid method to contact physicians who were often scattered throughout the hospital. Still, it was an imperfect solution as the ubiquitous pager constantly interrupted patient care and other tasks, failed to prioritize information, and added to an already stressful working environment. Notably, interns were paged on average once per hour, and occasionally 5 or more times per hour, a frequency that was felt to be detrimental to patient care and to the working environment of resident physicians.[1]

Little has changed. Despite the instant, multidirectional communication platforms available today, alphanumeric paging remains a mainstay of communication between physicians and other members of the care team. Importantly, paging contributes to communication errors (eg, by failing to convey urgency, having incomplete information, or being missed entirely by coverage gaps),[2, 3] and interrupts resident workflow, thereby negatively affecting work efficiency and educational activities, and adding to perceived workload.[4, 5]

In this era of duty hour restrictions, there has been concern that residents experience increased workload due to having fewer hours to do the same amount of work.[6, 7] As such, the Accreditation Council of Graduate Medical Education emphasizes the quality of those hours, with a focus on several aspects of the resident working environment as key to improved educational and patient safety outcomes.[8, 9, 10]

Geographic localization of physicians to patient care units has been proposed as a means to improve communication and agreement on plans of care,[11, 12] and also to reduce resident workload by decreasing inefficiencies attributable to traveling throughout the hospital.[13] O'Leary, et al. (2009) found that when physicians were localized to 1 hospital unit, there was greater agreement between physicians and nurses on various aspects of care, such as planned tests and anticipated length of stay. In addition, members of the patient care team were better able to identify one another, and there was a perceived increase in face‐to‐face communication, and a perceived decrease in text paging.[11]

In consideration of these factors, in July 2011, at New YorkPresbyterian Hospital/Weill Cornell (NYPH/WC), an 800‐bed tertiary care teaching hospital in New York, New York, we geographically localized 2 internal medicine resident teams, and partially localized 2 additional teams. We investigated whether interns on teams that were geographically localized received fewer pages than interns on teams that were not localized. This study was reviewed by the institutional review board of Weill Cornell Medical College and met the requirements for exemption.

METHODS

We conducted a retrospective analysis of the number of pages received by interns during the day (7:00 am to 7:00 pm) on 5 general internal medicine teams during a 1‐month ward rotation between October 17, 2011 and November 13, 2011 at NYPH/WC. The general medicine teams were composed of 1 attending, 1 resident, and 2 interns each. Two teams were geographically localized to a 32‐bed unit (geographic localization model [GLM]). Two teams were partially localized to a 26‐bed unit, which included a respiratory care step‐down unit (partial localization model [PLM]). A fifth and final team admitted patients irrespective of their assigned bed location (standard model [SM]). Both the GLM and the PLM occasionally carried patients on other units to allow for overall census management and patient throughput. The total number of pages received by each intern over the study period was collected by retrospective analysis of electronic paging logs. Night pages (7 pm7 am) were excluded because of night float coverage. Weekend pages were excluded because data were inaccurate due to coverage for days off.

The daily number of admissions and daily census per team were recorded by physician assistants, who also assigned new patients to appropriate teams according to an admissions algorithm (see Supporting Figure 1 in the online version of this article). The percent of geographically localized patients on each team was estimated from the percentage of localized patients on the day of discharge averaged over the study period. For the SM team, percent localization was defined as the number of patients on the patient care unit that contained the team's work area.

Figure 1
Average number of pages per intern per hour for each care model. Abbreviations: GLM, geographically localized model; PLM, partial localization model; SM, standard model.

Standard multivariate linear regression techniques were used to analyze the relationship between the number of pages received per intern and the type of team, controlling for the potential effect of total census and number of admissions. The regression model was used to determine adjusted marginal point estimates and 95% confidence intervals (CIs) for the average number of pages per intern per hour for each type of team. All statistical analyses were conducted using Stata version 12 (StataCorp, College Station, TX).

RESULTS

Over the 28‐day study period, a total of 6652 pages were received by 10 interns on 5 general internal medicine teams from 7 am to 7 pm Monday through Friday. The average daily census, average daily admissions, and percent of patients localized to patient care units for the individual teams are shown in Table 1. In univariate analysis, the mean daily pages per intern were not significantly different between the 2 teams within the GLM, nor between the 2 teams in the PLM, allowing them to be combined in multivariate analysis (data not shown). The number of pages received per intern per hour, adjusted for team census and number of admissions, was 2.2 (95% CI: 2.02.4) in the GLM, 2.8 (95% CI: 2.6‐3.0) in the PLM, and 3.9 (95% CI: 3.6‐4.2) in the SM (Table 1). All of these differences were statistically significant (P<0.001).

Geographic Distribution, Census, Admissions, and Pages per Hour per Intern for Each Patient Care Model During the Study Period
Standard Model* Partial Localization Model Geographically Localized Model
  • NOTE: Abbreviations: CI, confidence interval. *One general medicine team in the standard model, and 2 each in the partial localization model and geographically localized model, with 2 interns per team.

Percent of patients localized 37% 45% 85%
Team census, mean (range per day) 16.1 (1320) 15.9 (1120) 15.6 (1119)
Team admissions, mean (range per day) 2.7 (15) 2.9 (06) 3.5 (07)
Pages per hour per intern, unadjusted, mean (95% CI) 3.9 (3.6‐4.1) 2.8 (2.6‐3.0) 2.2 (2.02.4)
Pages per hour per intern, adjusted for census and admissions, mean (95% CI) 3.9 (3.6‐4.2) 2.8 (2.6‐3.0) 2.2 (2.02.4)

Figure 1 shows the pattern of daytime paging for each model. The GLM and PLM had a similar pattern, with an initial ramp up in the first 2 hours of the day, holding steady until approximately 4 pm, and then decrease until 7 pm. The SM had a steeper initial rise, and then continued to increase slowly until a peak at 4 pm.

DISCUSSION

This study corroborates that of Singh et al. (2012), who found that geographic localization led to significantly fewer pages.[14] Our results strengthen the evidence by demonstrating that even modest differences between the percent of patients localized to a care unit led to a significant decrease in the number of pages, indicating a dose‐response effect. The paging frequency we measured is higher than described in Singh et al. (1.4 pages per hour for localized teams), yet our average census appears to be 4 patients higher, which may account for some of that difference. We also show that interns on teams whose patients are more widely scattered throughout the hospital may experience upward of 5 pages per hour, an interruption by pager every 12 minutes, all day long.

A pager interruption is not solely limited to a disruption by noxious sound or vibration. The page recipient must then read the page and respond accordingly, which may involve a phone call, placing an order, walking to another location, or other work tasks. Although some of these interruptions must be handled immediately, such as a clinically deteriorating patient, many are not urgent, and could wait until the physician's current task or thought process is complete. There is also the potentially risky assumption on the part of the sender that the message has been received and will be acted upon. Furthermore, frequent paging is a common interruption to physician workflow; interruptions contribute to increased perceived physician workload[4, 5] and are likely detrimental to patient safety.[15, 16]

The most common metrics used to measure resident workload are patient census and number of admissions,[13] but these metrics have provided a mixed and likely incomplete picture. Recent research suggests that other factors, such as work efficiency (including interruptions, time spent obtaining test results, and time in transit) and work intensity (such as the acuity and complexity of patients), contribute significantly to actual and perceived resident workload.[13]

Our analysis was a single‐site, retrospective study, which occurred over 1 month and was limited to internal medicine teams. Additionally, geographic localization logically should lead to increased face‐to‐face interruptions, which we were unable to measure with this project, but direct communication is more efficient and less prone to error, which would likely lead to fewer overall interruptions. Although we anticipate that our findings are applicable to geographically localized patient care units in other hospitals, further investigation is warranted.

The paging chorus has only grown louder over the last 25 years, with likely downstream effects on patient safety and resident education. To mitigate these effects, it is incumbent upon us to approach our training and patient care environments with a critical and creative lens, and to explore opportunities to decrease interruptions and streamline our communication systems.

Acknowledgements

The authors acknowledge the assistance with data analysis of Arthur Evans, MD, MPH, and review of the manuscript by Brendan Reilly, MD.

Disclosures: Dr. Fanucchi and Ms. Unterbrink have no conflicts of interest to disclose. Dr. Logio reports receiving royalties from McGraw‐Hill for Core Concepts in Patient Safety online modules.

References
  1. Katz MH, Schroeder SA. The sounds of the hospital. Paging patterns in three teaching hospitals. N Engl J Med. 1988;319(24):15851589.
  2. Sutcliffe KM, Lewton E, Rosenthal MM. Communication failures: an insidious contributor to medical mishaps. Acad Med. 2004;79(2):186194.
  3. Espino S, Cox D, Kaplan B. Alphanumeric paging: a potential source of problems in patient care and communication. J Surg Educ. 2011;68(6):447451.
  4. Weigl M, Muller A, Zupanc A, Glaser J, Angerer P. Hospital doctors' workflow interruptions and activities: an observation study. BMJ Qual Saf. 2011;20(6):491497.
  5. Weigl M, Muller A, Vincent C, Angerer P, Sevdalis N. The association of workflow interruptions and hospital doctors' workload: a prospective observational study. BMJ Qual Saf. 2012;21(5):399407.
  6. Goitein L, Ludmerer KM. Resident workload—let's treat the disease, not just the symptom. Comment on: Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff. JAMA Intern Med. 2013;173(8):655656.
  7. Desai SV, Feldman L, Brown L, et al. Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med. 2013;173(8):649655.
  8. Philibert I, Amis S. The ACGME 2011 Duty Hour Standards: Enhancing Quality of Care, Supervision, and Resident Professional Development. Chicago, IL: Accreditation Council for Graduate Medical Education; 2011.
  9. Ulmer C, Wolman D, Johns M, eds . Institute of Medicine Resident Duty Hours: Enhancing Sleep, Supervision, and Safety. Washington, DC: National Academies Press; 2009.
  10. Schumacher DJ, Slovin SR, Riebschleger MP, Englander R, Hicks PJ, Carraccio C. Perspective: beyond counting hours: the importance of supervision, professionalism, transitions of care, and workload in residency training. Acad Med. 2012;87(7):883888.
  11. O'Leary KJ, Wayne DB, Landler MP, et al. Impact of localizing physicians to hospital units on nurse‐physician communication and agreement on the plan of care. J Gen Intern Med. 2009;24(11):12231227.
  12. Gordon MB, Melvin P, Graham D, et al. Unit‐based care teams and the frequency and quality of physician‐nurse communications. Arch Pediatr Adolesc Med. 2011;165(5):424428.
  13. Thanarajasingam U, McDonald FS, Halvorsen AJ, et al. Service census caps and unit‐based admissions: resident workload, conference attendance, duty hour compliance, and patient safety. Mayo Clin Proc. 2012;87(4):320327.
  14. Singh S, Tarima S, Rana V, et al. Impact of localizing general medical teams to a single nursing unit. J Hosp Med. 2012;7(7):551556.
  15. Coiera E. The science of interruption. BMJ Qual Saf. 2012;21(5):357360.
  16. Westbrook JI, Coiera E, Dunsmuir WT, et al. The impact of interruptions on clinical task completion. Qual Saf Health Care. 2010;19(4):284289.
References
  1. Katz MH, Schroeder SA. The sounds of the hospital. Paging patterns in three teaching hospitals. N Engl J Med. 1988;319(24):15851589.
  2. Sutcliffe KM, Lewton E, Rosenthal MM. Communication failures: an insidious contributor to medical mishaps. Acad Med. 2004;79(2):186194.
  3. Espino S, Cox D, Kaplan B. Alphanumeric paging: a potential source of problems in patient care and communication. J Surg Educ. 2011;68(6):447451.
  4. Weigl M, Muller A, Zupanc A, Glaser J, Angerer P. Hospital doctors' workflow interruptions and activities: an observation study. BMJ Qual Saf. 2011;20(6):491497.
  5. Weigl M, Muller A, Vincent C, Angerer P, Sevdalis N. The association of workflow interruptions and hospital doctors' workload: a prospective observational study. BMJ Qual Saf. 2012;21(5):399407.
  6. Goitein L, Ludmerer KM. Resident workload—let's treat the disease, not just the symptom. Comment on: Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff. JAMA Intern Med. 2013;173(8):655656.
  7. Desai SV, Feldman L, Brown L, et al. Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med. 2013;173(8):649655.
  8. Philibert I, Amis S. The ACGME 2011 Duty Hour Standards: Enhancing Quality of Care, Supervision, and Resident Professional Development. Chicago, IL: Accreditation Council for Graduate Medical Education; 2011.
  9. Ulmer C, Wolman D, Johns M, eds . Institute of Medicine Resident Duty Hours: Enhancing Sleep, Supervision, and Safety. Washington, DC: National Academies Press; 2009.
  10. Schumacher DJ, Slovin SR, Riebschleger MP, Englander R, Hicks PJ, Carraccio C. Perspective: beyond counting hours: the importance of supervision, professionalism, transitions of care, and workload in residency training. Acad Med. 2012;87(7):883888.
  11. O'Leary KJ, Wayne DB, Landler MP, et al. Impact of localizing physicians to hospital units on nurse‐physician communication and agreement on the plan of care. J Gen Intern Med. 2009;24(11):12231227.
  12. Gordon MB, Melvin P, Graham D, et al. Unit‐based care teams and the frequency and quality of physician‐nurse communications. Arch Pediatr Adolesc Med. 2011;165(5):424428.
  13. Thanarajasingam U, McDonald FS, Halvorsen AJ, et al. Service census caps and unit‐based admissions: resident workload, conference attendance, duty hour compliance, and patient safety. Mayo Clin Proc. 2012;87(4):320327.
  14. Singh S, Tarima S, Rana V, et al. Impact of localizing general medical teams to a single nursing unit. J Hosp Med. 2012;7(7):551556.
  15. Coiera E. The science of interruption. BMJ Qual Saf. 2012;21(5):357360.
  16. Westbrook JI, Coiera E, Dunsmuir WT, et al. The impact of interruptions on clinical task completion. Qual Saf Health Care. 2010;19(4):284289.
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(Re)turning the pages of residency: The impact of localizing resident physicians to hospital units on paging frequency
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Improving Admission Process Efficiency

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Tempering pediatric hospitalist supervision of residents improves admission process efficiency without decreasing quality of care

Maintaining high‐quality patient care, optimizing patient safety, and providing adequate trainee supervision has been an area of debate in medical education recently, and many physicians remain concerned that excessive regulation and duty hour restrictions may prevent residents from obtaining sufficient experience and developing an appropriate sense of autonomy.[1, 2, 3, 4] However, pediatric hospital medicine (PHM) has seen dramatic increases in evening and nighttime in‐house attending coverage, and the trend is expected to continue.[5, 6] Whether it be for financial, educational, or patient‐centered reasons, increased in‐house attending coverage at an academic medical setting, almost by definition, increases direct resident supervision.[7]

Increased supervision may result in better educational outcomes,[8] but many forces, such as night float systems and electronic medical records (EMRs), pull residents away from the bedside, leaving them with fewer opportunities to make decisions and a reduced sense of personal responsibility and patient ownership. Experiential learning is of great value in medical training, and without this, residents may exit their training with less confidence and competence, only rarely having been able to make important medical decisions on their own.[9, 10]

Counter to the shift toward increased supervision, we recently amended our process for pediatric admissions to the PHM service by transitioning from mandatory to on‐demand attending input during the admissions process. We hypothesized that this would improve its efficiency by encouraging residents to develop an increased sense of patient ownership and would not significantly impact patient care.

METHODS

Setting

This cohort study was conducted at the Golisano Children's Hospital (GCH) at the University of Rochester in Rochester, New York. The pediatric residency program at this tertiary care center includes 48 pediatric residents and 21 medicinepediatric residents. The PHM division, comprised of 8 pediatric hospitalists, provides care to approximately one‐third of the children with medical illnesses admitted to GCH. During the daytime, PHM attendings provide in‐house supervision for 2 resident teams, each consisting of a senior resident and 2 interns. At night, PHM attendings take calls from home. Residents are encouraged to contact attendings, available by cell phone and pager, with questions or concerns regarding patient care. The institutional review board of the University of Rochester Medical Center approved this study and informed consent was waived.

Process Change

Prior to the change, a pediatric emergency department (ED) provider at GCH directly contacted the PHM attending for all admissions to the PHM service (Figure 1). If the PHM attending accepted the admission, the ED provider then notified the pediatric admitting officer (PAO), a third‐year pediatric or fourth‐year medicinepediatric resident, who either performed or delegated the admission duties (eg, history and physical exam, admission orders).

Figure 1
Admission process for patients admitted to PHM service in pre‐ and post‐intervention cohorts. Abbreviations: ED, emergency department; PAO, pediatric admitting officer; PHM, pediatric hospital medicine.

On June 18, 2012, a new process for pediatric admissions was implemented (Figure 1). The ED provider now called the PAO, and not the attending, to discuss an admission to the PHM service. The PAO was empowered to accept the patient on behalf of the PHM attending, and perform or delegate the admission duties. During daytime hours (7:00 am5:00 pm), the PAO was expected to alert the PHM attending of the admission to allow the attending to see the patient on the day of admission. The PHM attending discussed the case with the admitting resident after the resident had an opportunity to assess the patient and formulate a management plan. During evening hours (5:00 pm10:00 pm), the admitting resident was expected to contact the PHM attending on call after evaluating the patient and developing a plan. Overnight (10:00 pm7:00 am), the PAO was given discretion as to whether she/he needed to contact the PHM attending on call; the PHM service attending then saw the patient in the morning. Residents were strongly encouraged to call the PHM attending with any questions or concerns or if they did not feel an admission was appropriate to the PHM service.

Study Population

The study population included all patients <19 years of age admitted to the PHM service from the ED. The pre‐ and post‐intervention cohorts included patients admitted from July 1, 2011 to September 30, 2011 and July 1, 2012 to September 30, 2012, respectively. These dates were chosen because residents are least experienced in the summer months, and hence we would predict the greatest disparity during this time. Patients who were directly admitted via transport from an outside facility, office or from home, or who were transferred from another service within GCH were excluded. Patients were identified from administrative databases.

Data Collection

Date and time of admission, severity of illness (SOI) scores, and risk of mortality (ROM) scores were obtained from the administrative dataset. The EMR was then used to extract the following variables: gender; date and time of the ED provider's admission request and first inpatient resident order; date and time of patient discharge, defined as the time the after‐visit summary was finalized by an inpatient provider; and the number of rapid response team (RRT) activations within 24 hours of the first inpatient resident order. The order time difference was calculated by subtracting the date and time of the ED provider admission request from the first inpatient order. Cases in which the order time difference was negative were excluded from the order time analysis due to the possibility that some extenuating circumstance for these patients, not related to the admission process, caused the early inpatient order. Length of stay (LOS) was calculated as the difference between the date and time of ED admission request and date and time of patient discharge.

The first 24 hours of each admission were reviewed independently by 3 PHM attending investigators. Neither reviewer evaluated a chart for which he had cosigned the admission note. Charts were assessed to determine whether a reasonable standard of care (SOC) was provided by the inpatient resident during admission. For instances in which SOC was not felt to have been provided by the resident, the chart was reviewed by the second investigator. If there was disagreement between the 2 investigators, a third PHM attending was used to determine the majority opinion. Due to the nature of data collected, it was not possible to blind reviewers.

PHM attending investigators also assessed how often the inpatient resident's antibiotic choice was changed by the admitting PHM attending. This evaluation excluded topical antibiotics and antibiotics not related to the admitting diagnosis (eg, continuation of outpatient antibiotics for otitis media). A change in antibiotics was defined as a change in class or a change within classes, initiation, or discontinuation of an antibiotic by the attending. Switching the route of administration was considered a change if it was not done as part of the transition to discharge. Antibiotic choice was considered in agreement if a change was made by the PHM attending based on new patient information that was not available to the admitting inpatient resident if it could be reasonably concluded that the attending would have otherwise agreed with the original choice. If this determination could not be made, the antibiotic agreement was classified as unknown. Data regarding antibiotic agreement were analyzed in 2 ways. The first included all patients for which agreement could be determined. For this analysis, if a patient was not prescribed an antibiotic by the resident or attending, there was considered to have been antibiotic agreement. The second analysis included only the patients for whom an antibiotic was started by the inpatient resident or admitting attending.

Finally, RRT activations within the first 24 hours of admission in the 2012 cohort were evaluated to determine whether the RRT could have been prevented by the original admission process. This determination was made via majority opinion of 3 PHM attendings who each independently reviewed the cases.

Statistical Analysis

The distributions of continuous variables (eg, order time difference, LOS) and the ordinal variables (ROM and SOI) were compared using Wilcoxon rank sum tests. 2 tests or Fisher exact tests were used to assess the differences in categorical variables (eg, SOC, gender). All tests were 2‐sided, and the significance level was set at 0.05. Analyses were conducted using the SAS statistical package version 9.3 (SAS Institute Inc., Cary, NC) and SPSS version 21 (IBM/SPSS, Armonk, NY).

RESULTS

The initial search identified 532 admissions. Of these, 140 were excluded (72 were via route other than the ED, 44 were not admitted to PHM, 14 were outside the study period, and 10 did not meet age criteria). Therefore, 182 admissions in the 2011 cohort and 210 admissions in the 2012 cohort were included. For all patients in the 2012 cohort, the correct admission process was followed.

Demographic characteristics between cohorts were similar (Table 1). Data for ROM and SOI were available for 141 (78%) 2011 patients and for 169 (81%) 2012 patients. The distribution of patients over the study months differed between cohorts. Age, gender, ROM, and SOI were not significantly different.

Characteristics of Children Admitted to the Pediatric Hospital Medicine Service
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range. *Patients admitted between 10:00 pm and 7:00 am.

Male gender, n (%)107 (59)105 (50)0.082
Median age, y (IQR)2 (010)2 (07)0.689
Month admitted, n (%)  0.002
July60 (33)87 (41) 
August57 (31)81 (39) 
September65 (36)42 (20) 
Nighttime admission, n (%)*71 (39)90 (43)0.440
Risk of mortality, n (%)  0.910
1, lowest risk114 (81)138 (82) 
222 (16)23 (14) 
35 (4)6 (4) 
4, highest risk0 (0)2 (1) 
Severity of illness, n (%)  0.095
1, lowest severity60 (43)86 (51) 
254 (38)62 (37) 
325 (18)15 (9) 
4, highest severity2 (1)6 (4) 

The median difference in time from the ED provider admission request to the first inpatient resident order was roughly half as long in 2012 than in 2011 (123 vs 62 minutes, P<0.001) (Table 2). There were 12 cases in which the inpatient order came prior to the ED admission request in 2012 and 2 cases in 2011, and these were excluded from the order time difference analysis. LOS was not significantly different between groups (P=0.348). There were no differences in the frequency of antibiotic changes when all patients were considered or in the subgroup in whom antibiotics were prescribed by either the resident or attending. The number of cases for which the admitting resident's plan was deemed not to have met standard of care were few and not significantly different (P=1). None of these patients experienced harm as a result, and in all cases, SOC was determined to have been provided by the admitting PHM attending. The frequency of RRT calls within the first 24 hours of admission on PHM patients was not significantly different (P=0.114).

Comparison of Patient Cohorts Admitted to Pediatric Hospital Medicine Before and After the Change in Admission Procedure
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range; RRT, rapid response team.

  • Cases in which the time difference between orders was negative were excluded.

  • P value was calculated using Wilcoxon rank sum test.

Time from admission decision to first inpatient order, min, median (IQR)a123 (70188)62 (30105)<0.001
Length of stay, h, median (IQR)b44 (3167)41 (2271)0.348
Change by attending to resident's antibiotic choice in all patients, n (%)13/182 (7)18/210 (9)0.617
Change by attending to resident's antibiotic choice in patients who received antibiotics, n (%)13/97 (13)18/96 (19)0.312
Resident met standard of care, n (%)180/182 (99)207/210 (99)1
RRT called within first 24 hours, n (%)2/182 (1)8/210 (4)0.114

When only patients admitted during the night in 2011 and 2012 were compared, results were consistent with the overall finding that there was a shorter time to inpatient admission order without a difference in other studied variables (Table 3).

Comparison of Nighttime Admissions Between Cohorts (n=161)
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range; RRT, rapid response team.

  • Cases in which the time difference between orders was negative were excluded.

  • P value was calculated using Wilcoxon rank sum test.

Time from admission decision to first inpatient order, min, median (IQR)ab90 (40151)42 (1767)0.002
Length of stay, h, median (IQR)b53 (3461)36 (1769)0.307
Change by attending to resident's antibiotic choice in all patients, n (%)7/70 (10)7/88 (8)1
Resident met standard of care, n (%)70/71 (99)88/90 (98)1
RRT called within first 24 hours, n (%)2/71 (3)6/90 (7)0.468

DISCUSSION

The purpose of this study was to evaluate an admission process that removed an ineffective method of attending oversight and allowed residents an opportunity to develop patient care plans prior to attending input. The key change from the original process was removing the step in which the ED provider contacted the PHM attending for new admissions, thus eliminating mandatory inpatient attending input, removing an impediment to workflow, and empowering inpatient pediatric residents to assess new patients and develop management plans. Our data show a reduction in the time difference between the ED admission request and the inpatient resident's first order by more than an hour, indicating a more efficient admission process. Although one might expect that eliminating the act of a phone call would shorten this time by a few minutes, it cannot account for the extent of the difference we found. We postulate that an increased sense of accountability motivated inpatient residents to evaluate and begin management sooner, a topic that requires further exploration.

A more efficient admission process benefits emergency medicine residents and other ED providers as well. It is well documented that ED crowding is associated with decreased quality of care,[11, 12] and ED efficiency is receiving increased attention with newly reportable quality metrics such as Admit Decision Time to Emergency Department Departure Time for Admitted Patients.[13]

Our data do not attenuate the importance of hospitalists in patient care, as evidenced by the fact that PHM attendings continued to frequently amend the residents' antibiotic choicethe only variable we evaluated in terms of change in planand recognized several cases in which the residents' plan did not meet standard of care. Furthermore, attendings continued to be available by phone and pager for guidance and education when needed or requested by the residents. Instead, our data show that removing mandated attending input at the time of admission did not significantly impact major patient outcomes, which may partly be attributable to the general safety of the inpatient pediatric wards.[14, 15] In our study, a comprehensive analysis of patient harm was not possible given the variable list and infrequency with which SOC was not met or RRTs were called. Furthermore, our residency program continues to comply with national pediatric residency requirements for nighttime supervision.[7]

Our PHM division, which had previously allocated 2 hours of attending clinical time per call night, now averages <15 minutes. These data conflict with the current trend in PHM toward more, rather than less, direct attending oversight. Many PHM divisions have moved toward 24/7 in‐house coverage,[5] a situation that often results in shiftwork and multiple handoffs. Removing the in‐house attending overnight would allow for the rapidly growing PHM subspecialty to allocate hospitalists elsewhere depending on their scholarly needs, particularly as divisions seek to become increasingly involved in medical education, research, and hospital leadership.[16, 17] Although one might posit a financial benefit to having in‐house attendings determine the appropriateness of an admission overnight, we identified no case in which the insurance denied an admission.

Safety equivalence of an in‐house to on‐call attending is poorly studied in PHM. However, even in intensive care units, where the majority of morbidity and mortality occur, it is unclear that the presence of an attending, let alone mandating phone calls, positively impacts survival. One prospective trial failed to demonstrate a difference in patient outcomes in the critical care setting when comparing mandated attending in‐house involvement to optional attending availability by phone.[18] Furthermore, several studies have found no association with time of admission and mortality, implying there is no criticality specifically requiring nighttime coverage.[19, 20]

One adult study of nocturnists showed that residents felt they had more contact with attendings who were in‐house than attendings taking home calls.[21] However, when the residents were asked why they did not contact the attending, the only difference between at‐home and in‐house attendings was that for attendings available by phone, residents were less likely to know who to call and were hesitant to wake the attending.

This study had several limitations. First, we could not effectively blind reviewers; a salient point given that the reviewers benefited from the new system with a reduced nighttime workload. We attempted to minimize this bias by employing multiple independent evaluations followed by group consensus whenever possible. Second, even though we had 3 hospitalists independently review each 2012 RRT to determine whether it was preventable by the prior system, this task was prone to retrospective bias. Third, there was a significant difference in the month of admission between cohorts. Rather than biasing toward our observed time difference, the fact that more patients were admitted in July 2012the beginning of the academic yearmay have decreased our observed difference given that residents were less experienced. Forth, this study used certain measurable outcomes as proxies for quality of care and patient harm and was likely underpowered to truly detect a difference in some of the more infrequent variables. Furthermore, we did not evaluate other potential harms, such as cost. Fifth, we did not evaluate whether or not the new process changed ED provider behavior (ie, an ED provider may wait longer to request admission overnight given that the PHM attending is not mandated to provide input until the morning). Finally, although LOS was used as a balancing measure, it would likely have taken major events or omissions during the admission process to cause it to change significantly, and therefore the lack of statistical difference in this metric does not necessarily imply that more subtle aspects of care were the same between groups. We also chose not to include readmission rate for this reason, as any change could not conclusively be attributed to the new admission process.

CONCLUSION

Increasing resident autonomy by removing mandated input during PHM admissions makes the process more efficient and results in no significant changes to major patient outcomes. These data may be used by rapidly growing PHM divisions to redefine faculty clinical responsibilities, particularly at night.

ACKNOWLEDGMENTS

Disclosures: This project was supported by the University of Rochester CTSA award number UL1 TR000042 from the National Center for Advancing Translational Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors report no conflicts of interest.

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References
  1. Accreditation Council for Graduate Medical Education Task Force on Quality Care and Professionalism. The ACGME 2011 duty hour standards: enhancing quality of care, supervision, and resident professional development. Accreditation Council for Graduate Medical Education, Chicago, IL; 2011. Available at: http://www.acgme.org/acgmeweb/Portals/0/PDFs/jgme‐monograph[1].pdf. Last accessed on December 18, 2013.
  2. Moonesinghe SR, Lowery J, Shahi N, Millen A, Beard JD. Impact of reduction in working hours for doctors in training on postgraduate medical education and patients' outcomes: systemic review. BMJ. 2011;342:d1580.
  3. Feig BA, Hasso AN. ACGME 2011 duty‐hour guidelines: consequences expected by radiology residency directors and chief residents. J Am Coll Radiol. 2012;9(11):820827.
  4. Chiong W. Justifying patient risks associated with medical education. JAMA. 2007;298(9):10461048.
  5. Gosdin C, Simmons J, Yau C, Sucharew H, Carlson D, Paciorkowski N. Survey of academic pediatric hospitalist programs in the U.S.: organizational, administrative and financial factors. J Hosp Med. 2013;8(6):285291.
  6. Oshimura J, Sperring J, Bauer BD, Rauch DA. Inpatient staffing within pediatric residency programs: work hour restrictions and the evolving role of the pediatric hospitalist. J Hosp Med. 2012;7(4):299303.
  7. ACGME Program Requirements for Graduate Medical Education in Pediatrics. ACGME Approved: September 30, 2012; Effective: July 1, 2013. Available at: http://www.acgme.org/acgmeweb/Portals/0/PFAssets/2013‐PR‐FAQ‐PIF/320_pediatrics_07012013.pdf. Accessed September 17, 2013.
  8. Farnan JM, Petty LA, Georgitis E, et al. A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428442.
  9. Kerlin MP, Halpern SD. Twenty‐four‐hour intensivist staffing in teaching hospitals: tension between safety today and safety tomorrow. Chest. 2012;141(5):13151320.
  10. Fred HL. Medical education on the brink: 62 years of front‐line observations and opinions. Tex Heart Inst J. 2012;39(3):322329.
  11. Pines JM, Hollander JE. Emergency department crowding is associated with poor care for patients with severe pain. Ann Emerg Med. 2008;51:67.
  12. Bernstein SL, Aronsky D, Duseja R, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med. 2009;16(1):110.
  13. The Specifications Manual for National Hospital Inpatient Quality Measures. A Collaboration of the Centers for Medicare 128(1):7278.
  14. Sharek PJ, Parast LM, Leong K, et al. Effect of a rapid response team on hospital‐wide mortality and code rates outside the ICU in a Children's Hospital. JAMA. 2007;298(19):22672274.
  15. Section on Hospital Medicine. Guiding principles for Pediatric Hospital Medicine programs. Pediatrics. 2013;132(4):782786. SHM fact sheet: about hospital medicine. http://www.hospitalmedicine.org/AM/Template.cfm?Section=Media_Kit42(5):120126.
  16. Kerlin MP, Small DS, Cooney E, et al. A randomized trial of nighttime physician staffing in an intensive care unit. N Engl J Med. 2013;368(23):22012209.
  17. Cavallazzi R, Marik PE, Hirani A, Pachinburavan M, Vasu TS, Leiby BE. Association between time of admission to the ICU and mortality: a systematic review and meta‐analysis. Chest. 2010;138(1):6875.
  18. Numa A, Williams G, Awad J, Duffy B. After‐hours admissions are not associated with increased risk‐adjusted mortality in pediatric intensive care. Intensive Care Med. 2008;34(1):148151.
  19. Haber LA, Lau CY, Sharpe BA, Arora VM, Farnan JM, Ranji SR. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606610.
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Maintaining high‐quality patient care, optimizing patient safety, and providing adequate trainee supervision has been an area of debate in medical education recently, and many physicians remain concerned that excessive regulation and duty hour restrictions may prevent residents from obtaining sufficient experience and developing an appropriate sense of autonomy.[1, 2, 3, 4] However, pediatric hospital medicine (PHM) has seen dramatic increases in evening and nighttime in‐house attending coverage, and the trend is expected to continue.[5, 6] Whether it be for financial, educational, or patient‐centered reasons, increased in‐house attending coverage at an academic medical setting, almost by definition, increases direct resident supervision.[7]

Increased supervision may result in better educational outcomes,[8] but many forces, such as night float systems and electronic medical records (EMRs), pull residents away from the bedside, leaving them with fewer opportunities to make decisions and a reduced sense of personal responsibility and patient ownership. Experiential learning is of great value in medical training, and without this, residents may exit their training with less confidence and competence, only rarely having been able to make important medical decisions on their own.[9, 10]

Counter to the shift toward increased supervision, we recently amended our process for pediatric admissions to the PHM service by transitioning from mandatory to on‐demand attending input during the admissions process. We hypothesized that this would improve its efficiency by encouraging residents to develop an increased sense of patient ownership and would not significantly impact patient care.

METHODS

Setting

This cohort study was conducted at the Golisano Children's Hospital (GCH) at the University of Rochester in Rochester, New York. The pediatric residency program at this tertiary care center includes 48 pediatric residents and 21 medicinepediatric residents. The PHM division, comprised of 8 pediatric hospitalists, provides care to approximately one‐third of the children with medical illnesses admitted to GCH. During the daytime, PHM attendings provide in‐house supervision for 2 resident teams, each consisting of a senior resident and 2 interns. At night, PHM attendings take calls from home. Residents are encouraged to contact attendings, available by cell phone and pager, with questions or concerns regarding patient care. The institutional review board of the University of Rochester Medical Center approved this study and informed consent was waived.

Process Change

Prior to the change, a pediatric emergency department (ED) provider at GCH directly contacted the PHM attending for all admissions to the PHM service (Figure 1). If the PHM attending accepted the admission, the ED provider then notified the pediatric admitting officer (PAO), a third‐year pediatric or fourth‐year medicinepediatric resident, who either performed or delegated the admission duties (eg, history and physical exam, admission orders).

Figure 1
Admission process for patients admitted to PHM service in pre‐ and post‐intervention cohorts. Abbreviations: ED, emergency department; PAO, pediatric admitting officer; PHM, pediatric hospital medicine.

On June 18, 2012, a new process for pediatric admissions was implemented (Figure 1). The ED provider now called the PAO, and not the attending, to discuss an admission to the PHM service. The PAO was empowered to accept the patient on behalf of the PHM attending, and perform or delegate the admission duties. During daytime hours (7:00 am5:00 pm), the PAO was expected to alert the PHM attending of the admission to allow the attending to see the patient on the day of admission. The PHM attending discussed the case with the admitting resident after the resident had an opportunity to assess the patient and formulate a management plan. During evening hours (5:00 pm10:00 pm), the admitting resident was expected to contact the PHM attending on call after evaluating the patient and developing a plan. Overnight (10:00 pm7:00 am), the PAO was given discretion as to whether she/he needed to contact the PHM attending on call; the PHM service attending then saw the patient in the morning. Residents were strongly encouraged to call the PHM attending with any questions or concerns or if they did not feel an admission was appropriate to the PHM service.

Study Population

The study population included all patients <19 years of age admitted to the PHM service from the ED. The pre‐ and post‐intervention cohorts included patients admitted from July 1, 2011 to September 30, 2011 and July 1, 2012 to September 30, 2012, respectively. These dates were chosen because residents are least experienced in the summer months, and hence we would predict the greatest disparity during this time. Patients who were directly admitted via transport from an outside facility, office or from home, or who were transferred from another service within GCH were excluded. Patients were identified from administrative databases.

Data Collection

Date and time of admission, severity of illness (SOI) scores, and risk of mortality (ROM) scores were obtained from the administrative dataset. The EMR was then used to extract the following variables: gender; date and time of the ED provider's admission request and first inpatient resident order; date and time of patient discharge, defined as the time the after‐visit summary was finalized by an inpatient provider; and the number of rapid response team (RRT) activations within 24 hours of the first inpatient resident order. The order time difference was calculated by subtracting the date and time of the ED provider admission request from the first inpatient order. Cases in which the order time difference was negative were excluded from the order time analysis due to the possibility that some extenuating circumstance for these patients, not related to the admission process, caused the early inpatient order. Length of stay (LOS) was calculated as the difference between the date and time of ED admission request and date and time of patient discharge.

The first 24 hours of each admission were reviewed independently by 3 PHM attending investigators. Neither reviewer evaluated a chart for which he had cosigned the admission note. Charts were assessed to determine whether a reasonable standard of care (SOC) was provided by the inpatient resident during admission. For instances in which SOC was not felt to have been provided by the resident, the chart was reviewed by the second investigator. If there was disagreement between the 2 investigators, a third PHM attending was used to determine the majority opinion. Due to the nature of data collected, it was not possible to blind reviewers.

PHM attending investigators also assessed how often the inpatient resident's antibiotic choice was changed by the admitting PHM attending. This evaluation excluded topical antibiotics and antibiotics not related to the admitting diagnosis (eg, continuation of outpatient antibiotics for otitis media). A change in antibiotics was defined as a change in class or a change within classes, initiation, or discontinuation of an antibiotic by the attending. Switching the route of administration was considered a change if it was not done as part of the transition to discharge. Antibiotic choice was considered in agreement if a change was made by the PHM attending based on new patient information that was not available to the admitting inpatient resident if it could be reasonably concluded that the attending would have otherwise agreed with the original choice. If this determination could not be made, the antibiotic agreement was classified as unknown. Data regarding antibiotic agreement were analyzed in 2 ways. The first included all patients for which agreement could be determined. For this analysis, if a patient was not prescribed an antibiotic by the resident or attending, there was considered to have been antibiotic agreement. The second analysis included only the patients for whom an antibiotic was started by the inpatient resident or admitting attending.

Finally, RRT activations within the first 24 hours of admission in the 2012 cohort were evaluated to determine whether the RRT could have been prevented by the original admission process. This determination was made via majority opinion of 3 PHM attendings who each independently reviewed the cases.

Statistical Analysis

The distributions of continuous variables (eg, order time difference, LOS) and the ordinal variables (ROM and SOI) were compared using Wilcoxon rank sum tests. 2 tests or Fisher exact tests were used to assess the differences in categorical variables (eg, SOC, gender). All tests were 2‐sided, and the significance level was set at 0.05. Analyses were conducted using the SAS statistical package version 9.3 (SAS Institute Inc., Cary, NC) and SPSS version 21 (IBM/SPSS, Armonk, NY).

RESULTS

The initial search identified 532 admissions. Of these, 140 were excluded (72 were via route other than the ED, 44 were not admitted to PHM, 14 were outside the study period, and 10 did not meet age criteria). Therefore, 182 admissions in the 2011 cohort and 210 admissions in the 2012 cohort were included. For all patients in the 2012 cohort, the correct admission process was followed.

Demographic characteristics between cohorts were similar (Table 1). Data for ROM and SOI were available for 141 (78%) 2011 patients and for 169 (81%) 2012 patients. The distribution of patients over the study months differed between cohorts. Age, gender, ROM, and SOI were not significantly different.

Characteristics of Children Admitted to the Pediatric Hospital Medicine Service
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range. *Patients admitted between 10:00 pm and 7:00 am.

Male gender, n (%)107 (59)105 (50)0.082
Median age, y (IQR)2 (010)2 (07)0.689
Month admitted, n (%)  0.002
July60 (33)87 (41) 
August57 (31)81 (39) 
September65 (36)42 (20) 
Nighttime admission, n (%)*71 (39)90 (43)0.440
Risk of mortality, n (%)  0.910
1, lowest risk114 (81)138 (82) 
222 (16)23 (14) 
35 (4)6 (4) 
4, highest risk0 (0)2 (1) 
Severity of illness, n (%)  0.095
1, lowest severity60 (43)86 (51) 
254 (38)62 (37) 
325 (18)15 (9) 
4, highest severity2 (1)6 (4) 

The median difference in time from the ED provider admission request to the first inpatient resident order was roughly half as long in 2012 than in 2011 (123 vs 62 minutes, P<0.001) (Table 2). There were 12 cases in which the inpatient order came prior to the ED admission request in 2012 and 2 cases in 2011, and these were excluded from the order time difference analysis. LOS was not significantly different between groups (P=0.348). There were no differences in the frequency of antibiotic changes when all patients were considered or in the subgroup in whom antibiotics were prescribed by either the resident or attending. The number of cases for which the admitting resident's plan was deemed not to have met standard of care were few and not significantly different (P=1). None of these patients experienced harm as a result, and in all cases, SOC was determined to have been provided by the admitting PHM attending. The frequency of RRT calls within the first 24 hours of admission on PHM patients was not significantly different (P=0.114).

Comparison of Patient Cohorts Admitted to Pediatric Hospital Medicine Before and After the Change in Admission Procedure
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range; RRT, rapid response team.

  • Cases in which the time difference between orders was negative were excluded.

  • P value was calculated using Wilcoxon rank sum test.

Time from admission decision to first inpatient order, min, median (IQR)a123 (70188)62 (30105)<0.001
Length of stay, h, median (IQR)b44 (3167)41 (2271)0.348
Change by attending to resident's antibiotic choice in all patients, n (%)13/182 (7)18/210 (9)0.617
Change by attending to resident's antibiotic choice in patients who received antibiotics, n (%)13/97 (13)18/96 (19)0.312
Resident met standard of care, n (%)180/182 (99)207/210 (99)1
RRT called within first 24 hours, n (%)2/182 (1)8/210 (4)0.114

When only patients admitted during the night in 2011 and 2012 were compared, results were consistent with the overall finding that there was a shorter time to inpatient admission order without a difference in other studied variables (Table 3).

Comparison of Nighttime Admissions Between Cohorts (n=161)
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range; RRT, rapid response team.

  • Cases in which the time difference between orders was negative were excluded.

  • P value was calculated using Wilcoxon rank sum test.

Time from admission decision to first inpatient order, min, median (IQR)ab90 (40151)42 (1767)0.002
Length of stay, h, median (IQR)b53 (3461)36 (1769)0.307
Change by attending to resident's antibiotic choice in all patients, n (%)7/70 (10)7/88 (8)1
Resident met standard of care, n (%)70/71 (99)88/90 (98)1
RRT called within first 24 hours, n (%)2/71 (3)6/90 (7)0.468

DISCUSSION

The purpose of this study was to evaluate an admission process that removed an ineffective method of attending oversight and allowed residents an opportunity to develop patient care plans prior to attending input. The key change from the original process was removing the step in which the ED provider contacted the PHM attending for new admissions, thus eliminating mandatory inpatient attending input, removing an impediment to workflow, and empowering inpatient pediatric residents to assess new patients and develop management plans. Our data show a reduction in the time difference between the ED admission request and the inpatient resident's first order by more than an hour, indicating a more efficient admission process. Although one might expect that eliminating the act of a phone call would shorten this time by a few minutes, it cannot account for the extent of the difference we found. We postulate that an increased sense of accountability motivated inpatient residents to evaluate and begin management sooner, a topic that requires further exploration.

A more efficient admission process benefits emergency medicine residents and other ED providers as well. It is well documented that ED crowding is associated with decreased quality of care,[11, 12] and ED efficiency is receiving increased attention with newly reportable quality metrics such as Admit Decision Time to Emergency Department Departure Time for Admitted Patients.[13]

Our data do not attenuate the importance of hospitalists in patient care, as evidenced by the fact that PHM attendings continued to frequently amend the residents' antibiotic choicethe only variable we evaluated in terms of change in planand recognized several cases in which the residents' plan did not meet standard of care. Furthermore, attendings continued to be available by phone and pager for guidance and education when needed or requested by the residents. Instead, our data show that removing mandated attending input at the time of admission did not significantly impact major patient outcomes, which may partly be attributable to the general safety of the inpatient pediatric wards.[14, 15] In our study, a comprehensive analysis of patient harm was not possible given the variable list and infrequency with which SOC was not met or RRTs were called. Furthermore, our residency program continues to comply with national pediatric residency requirements for nighttime supervision.[7]

Our PHM division, which had previously allocated 2 hours of attending clinical time per call night, now averages <15 minutes. These data conflict with the current trend in PHM toward more, rather than less, direct attending oversight. Many PHM divisions have moved toward 24/7 in‐house coverage,[5] a situation that often results in shiftwork and multiple handoffs. Removing the in‐house attending overnight would allow for the rapidly growing PHM subspecialty to allocate hospitalists elsewhere depending on their scholarly needs, particularly as divisions seek to become increasingly involved in medical education, research, and hospital leadership.[16, 17] Although one might posit a financial benefit to having in‐house attendings determine the appropriateness of an admission overnight, we identified no case in which the insurance denied an admission.

Safety equivalence of an in‐house to on‐call attending is poorly studied in PHM. However, even in intensive care units, where the majority of morbidity and mortality occur, it is unclear that the presence of an attending, let alone mandating phone calls, positively impacts survival. One prospective trial failed to demonstrate a difference in patient outcomes in the critical care setting when comparing mandated attending in‐house involvement to optional attending availability by phone.[18] Furthermore, several studies have found no association with time of admission and mortality, implying there is no criticality specifically requiring nighttime coverage.[19, 20]

One adult study of nocturnists showed that residents felt they had more contact with attendings who were in‐house than attendings taking home calls.[21] However, when the residents were asked why they did not contact the attending, the only difference between at‐home and in‐house attendings was that for attendings available by phone, residents were less likely to know who to call and were hesitant to wake the attending.

This study had several limitations. First, we could not effectively blind reviewers; a salient point given that the reviewers benefited from the new system with a reduced nighttime workload. We attempted to minimize this bias by employing multiple independent evaluations followed by group consensus whenever possible. Second, even though we had 3 hospitalists independently review each 2012 RRT to determine whether it was preventable by the prior system, this task was prone to retrospective bias. Third, there was a significant difference in the month of admission between cohorts. Rather than biasing toward our observed time difference, the fact that more patients were admitted in July 2012the beginning of the academic yearmay have decreased our observed difference given that residents were less experienced. Forth, this study used certain measurable outcomes as proxies for quality of care and patient harm and was likely underpowered to truly detect a difference in some of the more infrequent variables. Furthermore, we did not evaluate other potential harms, such as cost. Fifth, we did not evaluate whether or not the new process changed ED provider behavior (ie, an ED provider may wait longer to request admission overnight given that the PHM attending is not mandated to provide input until the morning). Finally, although LOS was used as a balancing measure, it would likely have taken major events or omissions during the admission process to cause it to change significantly, and therefore the lack of statistical difference in this metric does not necessarily imply that more subtle aspects of care were the same between groups. We also chose not to include readmission rate for this reason, as any change could not conclusively be attributed to the new admission process.

CONCLUSION

Increasing resident autonomy by removing mandated input during PHM admissions makes the process more efficient and results in no significant changes to major patient outcomes. These data may be used by rapidly growing PHM divisions to redefine faculty clinical responsibilities, particularly at night.

ACKNOWLEDGMENTS

Disclosures: This project was supported by the University of Rochester CTSA award number UL1 TR000042 from the National Center for Advancing Translational Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors report no conflicts of interest.

Maintaining high‐quality patient care, optimizing patient safety, and providing adequate trainee supervision has been an area of debate in medical education recently, and many physicians remain concerned that excessive regulation and duty hour restrictions may prevent residents from obtaining sufficient experience and developing an appropriate sense of autonomy.[1, 2, 3, 4] However, pediatric hospital medicine (PHM) has seen dramatic increases in evening and nighttime in‐house attending coverage, and the trend is expected to continue.[5, 6] Whether it be for financial, educational, or patient‐centered reasons, increased in‐house attending coverage at an academic medical setting, almost by definition, increases direct resident supervision.[7]

Increased supervision may result in better educational outcomes,[8] but many forces, such as night float systems and electronic medical records (EMRs), pull residents away from the bedside, leaving them with fewer opportunities to make decisions and a reduced sense of personal responsibility and patient ownership. Experiential learning is of great value in medical training, and without this, residents may exit their training with less confidence and competence, only rarely having been able to make important medical decisions on their own.[9, 10]

Counter to the shift toward increased supervision, we recently amended our process for pediatric admissions to the PHM service by transitioning from mandatory to on‐demand attending input during the admissions process. We hypothesized that this would improve its efficiency by encouraging residents to develop an increased sense of patient ownership and would not significantly impact patient care.

METHODS

Setting

This cohort study was conducted at the Golisano Children's Hospital (GCH) at the University of Rochester in Rochester, New York. The pediatric residency program at this tertiary care center includes 48 pediatric residents and 21 medicinepediatric residents. The PHM division, comprised of 8 pediatric hospitalists, provides care to approximately one‐third of the children with medical illnesses admitted to GCH. During the daytime, PHM attendings provide in‐house supervision for 2 resident teams, each consisting of a senior resident and 2 interns. At night, PHM attendings take calls from home. Residents are encouraged to contact attendings, available by cell phone and pager, with questions or concerns regarding patient care. The institutional review board of the University of Rochester Medical Center approved this study and informed consent was waived.

Process Change

Prior to the change, a pediatric emergency department (ED) provider at GCH directly contacted the PHM attending for all admissions to the PHM service (Figure 1). If the PHM attending accepted the admission, the ED provider then notified the pediatric admitting officer (PAO), a third‐year pediatric or fourth‐year medicinepediatric resident, who either performed or delegated the admission duties (eg, history and physical exam, admission orders).

Figure 1
Admission process for patients admitted to PHM service in pre‐ and post‐intervention cohorts. Abbreviations: ED, emergency department; PAO, pediatric admitting officer; PHM, pediatric hospital medicine.

On June 18, 2012, a new process for pediatric admissions was implemented (Figure 1). The ED provider now called the PAO, and not the attending, to discuss an admission to the PHM service. The PAO was empowered to accept the patient on behalf of the PHM attending, and perform or delegate the admission duties. During daytime hours (7:00 am5:00 pm), the PAO was expected to alert the PHM attending of the admission to allow the attending to see the patient on the day of admission. The PHM attending discussed the case with the admitting resident after the resident had an opportunity to assess the patient and formulate a management plan. During evening hours (5:00 pm10:00 pm), the admitting resident was expected to contact the PHM attending on call after evaluating the patient and developing a plan. Overnight (10:00 pm7:00 am), the PAO was given discretion as to whether she/he needed to contact the PHM attending on call; the PHM service attending then saw the patient in the morning. Residents were strongly encouraged to call the PHM attending with any questions or concerns or if they did not feel an admission was appropriate to the PHM service.

Study Population

The study population included all patients <19 years of age admitted to the PHM service from the ED. The pre‐ and post‐intervention cohorts included patients admitted from July 1, 2011 to September 30, 2011 and July 1, 2012 to September 30, 2012, respectively. These dates were chosen because residents are least experienced in the summer months, and hence we would predict the greatest disparity during this time. Patients who were directly admitted via transport from an outside facility, office or from home, or who were transferred from another service within GCH were excluded. Patients were identified from administrative databases.

Data Collection

Date and time of admission, severity of illness (SOI) scores, and risk of mortality (ROM) scores were obtained from the administrative dataset. The EMR was then used to extract the following variables: gender; date and time of the ED provider's admission request and first inpatient resident order; date and time of patient discharge, defined as the time the after‐visit summary was finalized by an inpatient provider; and the number of rapid response team (RRT) activations within 24 hours of the first inpatient resident order. The order time difference was calculated by subtracting the date and time of the ED provider admission request from the first inpatient order. Cases in which the order time difference was negative were excluded from the order time analysis due to the possibility that some extenuating circumstance for these patients, not related to the admission process, caused the early inpatient order. Length of stay (LOS) was calculated as the difference between the date and time of ED admission request and date and time of patient discharge.

The first 24 hours of each admission were reviewed independently by 3 PHM attending investigators. Neither reviewer evaluated a chart for which he had cosigned the admission note. Charts were assessed to determine whether a reasonable standard of care (SOC) was provided by the inpatient resident during admission. For instances in which SOC was not felt to have been provided by the resident, the chart was reviewed by the second investigator. If there was disagreement between the 2 investigators, a third PHM attending was used to determine the majority opinion. Due to the nature of data collected, it was not possible to blind reviewers.

PHM attending investigators also assessed how often the inpatient resident's antibiotic choice was changed by the admitting PHM attending. This evaluation excluded topical antibiotics and antibiotics not related to the admitting diagnosis (eg, continuation of outpatient antibiotics for otitis media). A change in antibiotics was defined as a change in class or a change within classes, initiation, or discontinuation of an antibiotic by the attending. Switching the route of administration was considered a change if it was not done as part of the transition to discharge. Antibiotic choice was considered in agreement if a change was made by the PHM attending based on new patient information that was not available to the admitting inpatient resident if it could be reasonably concluded that the attending would have otherwise agreed with the original choice. If this determination could not be made, the antibiotic agreement was classified as unknown. Data regarding antibiotic agreement were analyzed in 2 ways. The first included all patients for which agreement could be determined. For this analysis, if a patient was not prescribed an antibiotic by the resident or attending, there was considered to have been antibiotic agreement. The second analysis included only the patients for whom an antibiotic was started by the inpatient resident or admitting attending.

Finally, RRT activations within the first 24 hours of admission in the 2012 cohort were evaluated to determine whether the RRT could have been prevented by the original admission process. This determination was made via majority opinion of 3 PHM attendings who each independently reviewed the cases.

Statistical Analysis

The distributions of continuous variables (eg, order time difference, LOS) and the ordinal variables (ROM and SOI) were compared using Wilcoxon rank sum tests. 2 tests or Fisher exact tests were used to assess the differences in categorical variables (eg, SOC, gender). All tests were 2‐sided, and the significance level was set at 0.05. Analyses were conducted using the SAS statistical package version 9.3 (SAS Institute Inc., Cary, NC) and SPSS version 21 (IBM/SPSS, Armonk, NY).

RESULTS

The initial search identified 532 admissions. Of these, 140 were excluded (72 were via route other than the ED, 44 were not admitted to PHM, 14 were outside the study period, and 10 did not meet age criteria). Therefore, 182 admissions in the 2011 cohort and 210 admissions in the 2012 cohort were included. For all patients in the 2012 cohort, the correct admission process was followed.

Demographic characteristics between cohorts were similar (Table 1). Data for ROM and SOI were available for 141 (78%) 2011 patients and for 169 (81%) 2012 patients. The distribution of patients over the study months differed between cohorts. Age, gender, ROM, and SOI were not significantly different.

Characteristics of Children Admitted to the Pediatric Hospital Medicine Service
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range. *Patients admitted between 10:00 pm and 7:00 am.

Male gender, n (%)107 (59)105 (50)0.082
Median age, y (IQR)2 (010)2 (07)0.689
Month admitted, n (%)  0.002
July60 (33)87 (41) 
August57 (31)81 (39) 
September65 (36)42 (20) 
Nighttime admission, n (%)*71 (39)90 (43)0.440
Risk of mortality, n (%)  0.910
1, lowest risk114 (81)138 (82) 
222 (16)23 (14) 
35 (4)6 (4) 
4, highest risk0 (0)2 (1) 
Severity of illness, n (%)  0.095
1, lowest severity60 (43)86 (51) 
254 (38)62 (37) 
325 (18)15 (9) 
4, highest severity2 (1)6 (4) 

The median difference in time from the ED provider admission request to the first inpatient resident order was roughly half as long in 2012 than in 2011 (123 vs 62 minutes, P<0.001) (Table 2). There were 12 cases in which the inpatient order came prior to the ED admission request in 2012 and 2 cases in 2011, and these were excluded from the order time difference analysis. LOS was not significantly different between groups (P=0.348). There were no differences in the frequency of antibiotic changes when all patients were considered or in the subgroup in whom antibiotics were prescribed by either the resident or attending. The number of cases for which the admitting resident's plan was deemed not to have met standard of care were few and not significantly different (P=1). None of these patients experienced harm as a result, and in all cases, SOC was determined to have been provided by the admitting PHM attending. The frequency of RRT calls within the first 24 hours of admission on PHM patients was not significantly different (P=0.114).

Comparison of Patient Cohorts Admitted to Pediatric Hospital Medicine Before and After the Change in Admission Procedure
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range; RRT, rapid response team.

  • Cases in which the time difference between orders was negative were excluded.

  • P value was calculated using Wilcoxon rank sum test.

Time from admission decision to first inpatient order, min, median (IQR)a123 (70188)62 (30105)<0.001
Length of stay, h, median (IQR)b44 (3167)41 (2271)0.348
Change by attending to resident's antibiotic choice in all patients, n (%)13/182 (7)18/210 (9)0.617
Change by attending to resident's antibiotic choice in patients who received antibiotics, n (%)13/97 (13)18/96 (19)0.312
Resident met standard of care, n (%)180/182 (99)207/210 (99)1
RRT called within first 24 hours, n (%)2/182 (1)8/210 (4)0.114

When only patients admitted during the night in 2011 and 2012 were compared, results were consistent with the overall finding that there was a shorter time to inpatient admission order without a difference in other studied variables (Table 3).

Comparison of Nighttime Admissions Between Cohorts (n=161)
Variable20112012P Value
  • NOTE: Abbreviations: IQR, interquartile range; RRT, rapid response team.

  • Cases in which the time difference between orders was negative were excluded.

  • P value was calculated using Wilcoxon rank sum test.

Time from admission decision to first inpatient order, min, median (IQR)ab90 (40151)42 (1767)0.002
Length of stay, h, median (IQR)b53 (3461)36 (1769)0.307
Change by attending to resident's antibiotic choice in all patients, n (%)7/70 (10)7/88 (8)1
Resident met standard of care, n (%)70/71 (99)88/90 (98)1
RRT called within first 24 hours, n (%)2/71 (3)6/90 (7)0.468

DISCUSSION

The purpose of this study was to evaluate an admission process that removed an ineffective method of attending oversight and allowed residents an opportunity to develop patient care plans prior to attending input. The key change from the original process was removing the step in which the ED provider contacted the PHM attending for new admissions, thus eliminating mandatory inpatient attending input, removing an impediment to workflow, and empowering inpatient pediatric residents to assess new patients and develop management plans. Our data show a reduction in the time difference between the ED admission request and the inpatient resident's first order by more than an hour, indicating a more efficient admission process. Although one might expect that eliminating the act of a phone call would shorten this time by a few minutes, it cannot account for the extent of the difference we found. We postulate that an increased sense of accountability motivated inpatient residents to evaluate and begin management sooner, a topic that requires further exploration.

A more efficient admission process benefits emergency medicine residents and other ED providers as well. It is well documented that ED crowding is associated with decreased quality of care,[11, 12] and ED efficiency is receiving increased attention with newly reportable quality metrics such as Admit Decision Time to Emergency Department Departure Time for Admitted Patients.[13]

Our data do not attenuate the importance of hospitalists in patient care, as evidenced by the fact that PHM attendings continued to frequently amend the residents' antibiotic choicethe only variable we evaluated in terms of change in planand recognized several cases in which the residents' plan did not meet standard of care. Furthermore, attendings continued to be available by phone and pager for guidance and education when needed or requested by the residents. Instead, our data show that removing mandated attending input at the time of admission did not significantly impact major patient outcomes, which may partly be attributable to the general safety of the inpatient pediatric wards.[14, 15] In our study, a comprehensive analysis of patient harm was not possible given the variable list and infrequency with which SOC was not met or RRTs were called. Furthermore, our residency program continues to comply with national pediatric residency requirements for nighttime supervision.[7]

Our PHM division, which had previously allocated 2 hours of attending clinical time per call night, now averages <15 minutes. These data conflict with the current trend in PHM toward more, rather than less, direct attending oversight. Many PHM divisions have moved toward 24/7 in‐house coverage,[5] a situation that often results in shiftwork and multiple handoffs. Removing the in‐house attending overnight would allow for the rapidly growing PHM subspecialty to allocate hospitalists elsewhere depending on their scholarly needs, particularly as divisions seek to become increasingly involved in medical education, research, and hospital leadership.[16, 17] Although one might posit a financial benefit to having in‐house attendings determine the appropriateness of an admission overnight, we identified no case in which the insurance denied an admission.

Safety equivalence of an in‐house to on‐call attending is poorly studied in PHM. However, even in intensive care units, where the majority of morbidity and mortality occur, it is unclear that the presence of an attending, let alone mandating phone calls, positively impacts survival. One prospective trial failed to demonstrate a difference in patient outcomes in the critical care setting when comparing mandated attending in‐house involvement to optional attending availability by phone.[18] Furthermore, several studies have found no association with time of admission and mortality, implying there is no criticality specifically requiring nighttime coverage.[19, 20]

One adult study of nocturnists showed that residents felt they had more contact with attendings who were in‐house than attendings taking home calls.[21] However, when the residents were asked why they did not contact the attending, the only difference between at‐home and in‐house attendings was that for attendings available by phone, residents were less likely to know who to call and were hesitant to wake the attending.

This study had several limitations. First, we could not effectively blind reviewers; a salient point given that the reviewers benefited from the new system with a reduced nighttime workload. We attempted to minimize this bias by employing multiple independent evaluations followed by group consensus whenever possible. Second, even though we had 3 hospitalists independently review each 2012 RRT to determine whether it was preventable by the prior system, this task was prone to retrospective bias. Third, there was a significant difference in the month of admission between cohorts. Rather than biasing toward our observed time difference, the fact that more patients were admitted in July 2012the beginning of the academic yearmay have decreased our observed difference given that residents were less experienced. Forth, this study used certain measurable outcomes as proxies for quality of care and patient harm and was likely underpowered to truly detect a difference in some of the more infrequent variables. Furthermore, we did not evaluate other potential harms, such as cost. Fifth, we did not evaluate whether or not the new process changed ED provider behavior (ie, an ED provider may wait longer to request admission overnight given that the PHM attending is not mandated to provide input until the morning). Finally, although LOS was used as a balancing measure, it would likely have taken major events or omissions during the admission process to cause it to change significantly, and therefore the lack of statistical difference in this metric does not necessarily imply that more subtle aspects of care were the same between groups. We also chose not to include readmission rate for this reason, as any change could not conclusively be attributed to the new admission process.

CONCLUSION

Increasing resident autonomy by removing mandated input during PHM admissions makes the process more efficient and results in no significant changes to major patient outcomes. These data may be used by rapidly growing PHM divisions to redefine faculty clinical responsibilities, particularly at night.

ACKNOWLEDGMENTS

Disclosures: This project was supported by the University of Rochester CTSA award number UL1 TR000042 from the National Center for Advancing Translational Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors report no conflicts of interest.

References
  1. Accreditation Council for Graduate Medical Education Task Force on Quality Care and Professionalism. The ACGME 2011 duty hour standards: enhancing quality of care, supervision, and resident professional development. Accreditation Council for Graduate Medical Education, Chicago, IL; 2011. Available at: http://www.acgme.org/acgmeweb/Portals/0/PDFs/jgme‐monograph[1].pdf. Last accessed on December 18, 2013.
  2. Moonesinghe SR, Lowery J, Shahi N, Millen A, Beard JD. Impact of reduction in working hours for doctors in training on postgraduate medical education and patients' outcomes: systemic review. BMJ. 2011;342:d1580.
  3. Feig BA, Hasso AN. ACGME 2011 duty‐hour guidelines: consequences expected by radiology residency directors and chief residents. J Am Coll Radiol. 2012;9(11):820827.
  4. Chiong W. Justifying patient risks associated with medical education. JAMA. 2007;298(9):10461048.
  5. Gosdin C, Simmons J, Yau C, Sucharew H, Carlson D, Paciorkowski N. Survey of academic pediatric hospitalist programs in the U.S.: organizational, administrative and financial factors. J Hosp Med. 2013;8(6):285291.
  6. Oshimura J, Sperring J, Bauer BD, Rauch DA. Inpatient staffing within pediatric residency programs: work hour restrictions and the evolving role of the pediatric hospitalist. J Hosp Med. 2012;7(4):299303.
  7. ACGME Program Requirements for Graduate Medical Education in Pediatrics. ACGME Approved: September 30, 2012; Effective: July 1, 2013. Available at: http://www.acgme.org/acgmeweb/Portals/0/PFAssets/2013‐PR‐FAQ‐PIF/320_pediatrics_07012013.pdf. Accessed September 17, 2013.
  8. Farnan JM, Petty LA, Georgitis E, et al. A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428442.
  9. Kerlin MP, Halpern SD. Twenty‐four‐hour intensivist staffing in teaching hospitals: tension between safety today and safety tomorrow. Chest. 2012;141(5):13151320.
  10. Fred HL. Medical education on the brink: 62 years of front‐line observations and opinions. Tex Heart Inst J. 2012;39(3):322329.
  11. Pines JM, Hollander JE. Emergency department crowding is associated with poor care for patients with severe pain. Ann Emerg Med. 2008;51:67.
  12. Bernstein SL, Aronsky D, Duseja R, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med. 2009;16(1):110.
  13. The Specifications Manual for National Hospital Inpatient Quality Measures. A Collaboration of the Centers for Medicare 128(1):7278.
  14. Sharek PJ, Parast LM, Leong K, et al. Effect of a rapid response team on hospital‐wide mortality and code rates outside the ICU in a Children's Hospital. JAMA. 2007;298(19):22672274.
  15. Section on Hospital Medicine. Guiding principles for Pediatric Hospital Medicine programs. Pediatrics. 2013;132(4):782786. SHM fact sheet: about hospital medicine. http://www.hospitalmedicine.org/AM/Template.cfm?Section=Media_Kit42(5):120126.
  16. Kerlin MP, Small DS, Cooney E, et al. A randomized trial of nighttime physician staffing in an intensive care unit. N Engl J Med. 2013;368(23):22012209.
  17. Cavallazzi R, Marik PE, Hirani A, Pachinburavan M, Vasu TS, Leiby BE. Association between time of admission to the ICU and mortality: a systematic review and meta‐analysis. Chest. 2010;138(1):6875.
  18. Numa A, Williams G, Awad J, Duffy B. After‐hours admissions are not associated with increased risk‐adjusted mortality in pediatric intensive care. Intensive Care Med. 2008;34(1):148151.
  19. Haber LA, Lau CY, Sharpe BA, Arora VM, Farnan JM, Ranji SR. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606610.
References
  1. Accreditation Council for Graduate Medical Education Task Force on Quality Care and Professionalism. The ACGME 2011 duty hour standards: enhancing quality of care, supervision, and resident professional development. Accreditation Council for Graduate Medical Education, Chicago, IL; 2011. Available at: http://www.acgme.org/acgmeweb/Portals/0/PDFs/jgme‐monograph[1].pdf. Last accessed on December 18, 2013.
  2. Moonesinghe SR, Lowery J, Shahi N, Millen A, Beard JD. Impact of reduction in working hours for doctors in training on postgraduate medical education and patients' outcomes: systemic review. BMJ. 2011;342:d1580.
  3. Feig BA, Hasso AN. ACGME 2011 duty‐hour guidelines: consequences expected by radiology residency directors and chief residents. J Am Coll Radiol. 2012;9(11):820827.
  4. Chiong W. Justifying patient risks associated with medical education. JAMA. 2007;298(9):10461048.
  5. Gosdin C, Simmons J, Yau C, Sucharew H, Carlson D, Paciorkowski N. Survey of academic pediatric hospitalist programs in the U.S.: organizational, administrative and financial factors. J Hosp Med. 2013;8(6):285291.
  6. Oshimura J, Sperring J, Bauer BD, Rauch DA. Inpatient staffing within pediatric residency programs: work hour restrictions and the evolving role of the pediatric hospitalist. J Hosp Med. 2012;7(4):299303.
  7. ACGME Program Requirements for Graduate Medical Education in Pediatrics. ACGME Approved: September 30, 2012; Effective: July 1, 2013. Available at: http://www.acgme.org/acgmeweb/Portals/0/PFAssets/2013‐PR‐FAQ‐PIF/320_pediatrics_07012013.pdf. Accessed September 17, 2013.
  8. Farnan JM, Petty LA, Georgitis E, et al. A systematic review: the effect of clinical supervision on patient and residency education outcomes. Acad Med. 2012;87(4):428442.
  9. Kerlin MP, Halpern SD. Twenty‐four‐hour intensivist staffing in teaching hospitals: tension between safety today and safety tomorrow. Chest. 2012;141(5):13151320.
  10. Fred HL. Medical education on the brink: 62 years of front‐line observations and opinions. Tex Heart Inst J. 2012;39(3):322329.
  11. Pines JM, Hollander JE. Emergency department crowding is associated with poor care for patients with severe pain. Ann Emerg Med. 2008;51:67.
  12. Bernstein SL, Aronsky D, Duseja R, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med. 2009;16(1):110.
  13. The Specifications Manual for National Hospital Inpatient Quality Measures. A Collaboration of the Centers for Medicare 128(1):7278.
  14. Sharek PJ, Parast LM, Leong K, et al. Effect of a rapid response team on hospital‐wide mortality and code rates outside the ICU in a Children's Hospital. JAMA. 2007;298(19):22672274.
  15. Section on Hospital Medicine. Guiding principles for Pediatric Hospital Medicine programs. Pediatrics. 2013;132(4):782786. SHM fact sheet: about hospital medicine. http://www.hospitalmedicine.org/AM/Template.cfm?Section=Media_Kit42(5):120126.
  16. Kerlin MP, Small DS, Cooney E, et al. A randomized trial of nighttime physician staffing in an intensive care unit. N Engl J Med. 2013;368(23):22012209.
  17. Cavallazzi R, Marik PE, Hirani A, Pachinburavan M, Vasu TS, Leiby BE. Association between time of admission to the ICU and mortality: a systematic review and meta‐analysis. Chest. 2010;138(1):6875.
  18. Numa A, Williams G, Awad J, Duffy B. After‐hours admissions are not associated with increased risk‐adjusted mortality in pediatric intensive care. Intensive Care Med. 2008;34(1):148151.
  19. Haber LA, Lau CY, Sharpe BA, Arora VM, Farnan JM, Ranji SR. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606610.
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Journal of Hospital Medicine - 9(2)
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Tempering pediatric hospitalist supervision of residents improves admission process efficiency without decreasing quality of care
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Address for correspondence and reprint requests: Eric Biondi, MD, Department of Pediatrics, University of Rochester Medical Center, 601 Elmwood Ave., Box 667, Rochester, NY 14620; Telephone: 585‐276‐4113; Fax: 585‐276‐1128; E‐mail: [email protected]
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Bringing CME to the Bedside

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Returning hospitalists to their formative training environment for CME: The UCSF Hospitalist Mini‐College

Hospitalists, and physicians in general, recognize the need for continuing medical education (CME) to update their knowledge and skills to provide the best possible care for patients. Interactive and personalized learning activities provide the most effective approaches for maintaining or improving physician competency.[1, 2] Despite guidelines that recommend a shift of CME from the traditional large lecture format to case‐based and highly interactive learning techniques,[3] this has been challenging to achieve in practice.

In this issue of the Journal of Hospital Medicine, Sehgal and collaborators at the University of California, San Francisco (UCSF) report innovative and highly appealing CME activity that provides a short, focused experience for the practicing hospitalist seeking to update his or her skills.[4] The UCSF Hospitalist Mini‐College (UHMC) embraced the principles for creation of effective CME by conducting needs assessment from community hospitalists and constructing a program that provides focused, interactive, small‐group, intensive experiences and then evaluating the experience to improve subsequent iterations of the Mini‐College. The UHMC immerses participants in a relatively intense experience that includes close interaction with prominent faculty, hands‐on bedside experiences, practical skills, and attendance at sessions (resident report, morbidity and mortality conferences) that are part of every resident trainee's experience. Participants would be linked to their previous learning activities. As the authors point out, there may be a powerful stimulus to learning when practicing physicians return to the milieu of training environments. This observation deserves further investigation.

The report does not provide evidence that participation in the Mini‐College improved patient outcomes or physician performance in practice; these outcome measures remain elusive and an aspirational goal in medical education research. However, experienced clinician educators have come to recognize and adopt effective interventions that simply make sense in the same fashion that it makes sense to use a parachute when jumping out of an airplane in flight.[5] The UHMC makes sense. The medical education literature is replete with articles describing educational innovations and their 1‐ to 2‐year outcomes, leaving the reader wondering about sustainability. It is reassuring that Sehgal et al. report 5 years of experience with the UHMC, and that the program has consistently had a waiting list of hospitalists who want to participate despite the expense. Although it requires patience on the part of educational innovators, this report helps set a standard for reporting enduring innovation in the education arena.

The article provides a description that is sufficiently detailed for other academic medical centers to replicate the intervention or to effectively adapt the principles of the intervention for the needs of their local hospitalist community. The authors should be congratulated for sharing the details of their program and for sharing powerful comments by participants. For hospitalist medical educators interested in sharing details of effective and sustained innovations, publication of this article emphasizes the Journal of Hospital Medicine's interest in disseminating these important projects.

In summary, the report on the UHMC model challenges all of us in academic hospital medicine to think creatively about how to provide effective, engaging, and exciting learning opportunities beyond the years of medical school and residency training.

References
  1. Bloom BS. Effects of continuing medical education on improving physician clinical care and patient health: a review of systematic reviews. Int J Technol Assess Health Care. 2005;21:380385.
  2. Dorman T, Miller BM. Continuing medical education: the link between physician learning and health care outcomes. Acad Med. 2011;86:1339.
  3. Davis N, Davis D, Bloch R. Continuing medical education: AMEE Education Guide No. 35. Med Teach. 2008;30:652666.
  4. Sehgal NL, Wachter RM, Vidyarthi AR. Bringing continuing medical education to the bedside: The University of California, San Francisco hospitalist mini‐college. J HospMed. 2014;9:129134.
  5. Smith GC, Pell JP. Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials. BMJ. 2003;327:14591461.
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Article PDF
Article PDF

Hospitalists, and physicians in general, recognize the need for continuing medical education (CME) to update their knowledge and skills to provide the best possible care for patients. Interactive and personalized learning activities provide the most effective approaches for maintaining or improving physician competency.[1, 2] Despite guidelines that recommend a shift of CME from the traditional large lecture format to case‐based and highly interactive learning techniques,[3] this has been challenging to achieve in practice.

In this issue of the Journal of Hospital Medicine, Sehgal and collaborators at the University of California, San Francisco (UCSF) report innovative and highly appealing CME activity that provides a short, focused experience for the practicing hospitalist seeking to update his or her skills.[4] The UCSF Hospitalist Mini‐College (UHMC) embraced the principles for creation of effective CME by conducting needs assessment from community hospitalists and constructing a program that provides focused, interactive, small‐group, intensive experiences and then evaluating the experience to improve subsequent iterations of the Mini‐College. The UHMC immerses participants in a relatively intense experience that includes close interaction with prominent faculty, hands‐on bedside experiences, practical skills, and attendance at sessions (resident report, morbidity and mortality conferences) that are part of every resident trainee's experience. Participants would be linked to their previous learning activities. As the authors point out, there may be a powerful stimulus to learning when practicing physicians return to the milieu of training environments. This observation deserves further investigation.

The report does not provide evidence that participation in the Mini‐College improved patient outcomes or physician performance in practice; these outcome measures remain elusive and an aspirational goal in medical education research. However, experienced clinician educators have come to recognize and adopt effective interventions that simply make sense in the same fashion that it makes sense to use a parachute when jumping out of an airplane in flight.[5] The UHMC makes sense. The medical education literature is replete with articles describing educational innovations and their 1‐ to 2‐year outcomes, leaving the reader wondering about sustainability. It is reassuring that Sehgal et al. report 5 years of experience with the UHMC, and that the program has consistently had a waiting list of hospitalists who want to participate despite the expense. Although it requires patience on the part of educational innovators, this report helps set a standard for reporting enduring innovation in the education arena.

The article provides a description that is sufficiently detailed for other academic medical centers to replicate the intervention or to effectively adapt the principles of the intervention for the needs of their local hospitalist community. The authors should be congratulated for sharing the details of their program and for sharing powerful comments by participants. For hospitalist medical educators interested in sharing details of effective and sustained innovations, publication of this article emphasizes the Journal of Hospital Medicine's interest in disseminating these important projects.

In summary, the report on the UHMC model challenges all of us in academic hospital medicine to think creatively about how to provide effective, engaging, and exciting learning opportunities beyond the years of medical school and residency training.

Hospitalists, and physicians in general, recognize the need for continuing medical education (CME) to update their knowledge and skills to provide the best possible care for patients. Interactive and personalized learning activities provide the most effective approaches for maintaining or improving physician competency.[1, 2] Despite guidelines that recommend a shift of CME from the traditional large lecture format to case‐based and highly interactive learning techniques,[3] this has been challenging to achieve in practice.

In this issue of the Journal of Hospital Medicine, Sehgal and collaborators at the University of California, San Francisco (UCSF) report innovative and highly appealing CME activity that provides a short, focused experience for the practicing hospitalist seeking to update his or her skills.[4] The UCSF Hospitalist Mini‐College (UHMC) embraced the principles for creation of effective CME by conducting needs assessment from community hospitalists and constructing a program that provides focused, interactive, small‐group, intensive experiences and then evaluating the experience to improve subsequent iterations of the Mini‐College. The UHMC immerses participants in a relatively intense experience that includes close interaction with prominent faculty, hands‐on bedside experiences, practical skills, and attendance at sessions (resident report, morbidity and mortality conferences) that are part of every resident trainee's experience. Participants would be linked to their previous learning activities. As the authors point out, there may be a powerful stimulus to learning when practicing physicians return to the milieu of training environments. This observation deserves further investigation.

The report does not provide evidence that participation in the Mini‐College improved patient outcomes or physician performance in practice; these outcome measures remain elusive and an aspirational goal in medical education research. However, experienced clinician educators have come to recognize and adopt effective interventions that simply make sense in the same fashion that it makes sense to use a parachute when jumping out of an airplane in flight.[5] The UHMC makes sense. The medical education literature is replete with articles describing educational innovations and their 1‐ to 2‐year outcomes, leaving the reader wondering about sustainability. It is reassuring that Sehgal et al. report 5 years of experience with the UHMC, and that the program has consistently had a waiting list of hospitalists who want to participate despite the expense. Although it requires patience on the part of educational innovators, this report helps set a standard for reporting enduring innovation in the education arena.

The article provides a description that is sufficiently detailed for other academic medical centers to replicate the intervention or to effectively adapt the principles of the intervention for the needs of their local hospitalist community. The authors should be congratulated for sharing the details of their program and for sharing powerful comments by participants. For hospitalist medical educators interested in sharing details of effective and sustained innovations, publication of this article emphasizes the Journal of Hospital Medicine's interest in disseminating these important projects.

In summary, the report on the UHMC model challenges all of us in academic hospital medicine to think creatively about how to provide effective, engaging, and exciting learning opportunities beyond the years of medical school and residency training.

References
  1. Bloom BS. Effects of continuing medical education on improving physician clinical care and patient health: a review of systematic reviews. Int J Technol Assess Health Care. 2005;21:380385.
  2. Dorman T, Miller BM. Continuing medical education: the link between physician learning and health care outcomes. Acad Med. 2011;86:1339.
  3. Davis N, Davis D, Bloch R. Continuing medical education: AMEE Education Guide No. 35. Med Teach. 2008;30:652666.
  4. Sehgal NL, Wachter RM, Vidyarthi AR. Bringing continuing medical education to the bedside: The University of California, San Francisco hospitalist mini‐college. J HospMed. 2014;9:129134.
  5. Smith GC, Pell JP. Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials. BMJ. 2003;327:14591461.
References
  1. Bloom BS. Effects of continuing medical education on improving physician clinical care and patient health: a review of systematic reviews. Int J Technol Assess Health Care. 2005;21:380385.
  2. Dorman T, Miller BM. Continuing medical education: the link between physician learning and health care outcomes. Acad Med. 2011;86:1339.
  3. Davis N, Davis D, Bloch R. Continuing medical education: AMEE Education Guide No. 35. Med Teach. 2008;30:652666.
  4. Sehgal NL, Wachter RM, Vidyarthi AR. Bringing continuing medical education to the bedside: The University of California, San Francisco hospitalist mini‐college. J HospMed. 2014;9:129134.
  5. Smith GC, Pell JP. Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials. BMJ. 2003;327:14591461.
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Journal of Hospital Medicine - 9(2)
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Journal of Hospital Medicine - 9(2)
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Returning hospitalists to their formative training environment for CME: The UCSF Hospitalist Mini‐College
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© 2013 Society of Hospital Medicine
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Address for correspondence and reprint requests: Daniel Hunt, MD, Inpatient Clinician Educator Service, Department of Medicine, Massachusetts General Hospital, 50 Staniford Street, Suite 503B, Boston, MA 02114; Telephone: 617‐643‐0581; Fax: 617‐643‐0660; E‐mail: [email protected]
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Perioral dermatitis and diet

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Perioral dermatitis and diet

Could it be the carbs?

In my practice, I have observed consistent improvements in recalcitrant perioral dermatitis when patients switch to low-carbohydrate diets. Several of my patients with perioral dermatitis that responded poorly to oral doxycycline, topical metronidazole, and topical tacrolimus – or recurred upon cessation of therapy – have proven to have gluten sensitivity or intolerance. Their skin condition improves when they go on a gluten-free diet. But I have also seen considerable improvements after patients undertake low-carbohydrate, high-protein diets, even if those patients have no diagnosed gluten sensitivity. These improvements have occurred with minimal oral and topical treatments, and these patients have not experienced recurrences.

There have been no well-controlled studies, or even case reports to my knowledge, linking carbohydrate or gluten intake to perioral dermatitis. Could the improvement be serendipitous, or is there some basis for carbohydrates contributing to inflammatory status in the oral and gastrointestinal mucosa?

Alcohol, spicy foods, and chocolate have been linked to exacerbation of erythemogenic and papulopustular rosacea. However, the precipitating ingredients in these foods have not been identified. Could the common link simply be an abundance of carbohydrates?

More studies are needed to better define the role of diet in perioral dermatitis. In the meantime, I am seeing good results with low-carb/carb-free diets and will continue to suggest them to prevent recurrences in my patients with perioral dermatitis.

Dr. Talakoub is in private practice in McLean, Va.

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Could it be the carbs?

In my practice, I have observed consistent improvements in recalcitrant perioral dermatitis when patients switch to low-carbohydrate diets. Several of my patients with perioral dermatitis that responded poorly to oral doxycycline, topical metronidazole, and topical tacrolimus – or recurred upon cessation of therapy – have proven to have gluten sensitivity or intolerance. Their skin condition improves when they go on a gluten-free diet. But I have also seen considerable improvements after patients undertake low-carbohydrate, high-protein diets, even if those patients have no diagnosed gluten sensitivity. These improvements have occurred with minimal oral and topical treatments, and these patients have not experienced recurrences.

There have been no well-controlled studies, or even case reports to my knowledge, linking carbohydrate or gluten intake to perioral dermatitis. Could the improvement be serendipitous, or is there some basis for carbohydrates contributing to inflammatory status in the oral and gastrointestinal mucosa?

Alcohol, spicy foods, and chocolate have been linked to exacerbation of erythemogenic and papulopustular rosacea. However, the precipitating ingredients in these foods have not been identified. Could the common link simply be an abundance of carbohydrates?

More studies are needed to better define the role of diet in perioral dermatitis. In the meantime, I am seeing good results with low-carb/carb-free diets and will continue to suggest them to prevent recurrences in my patients with perioral dermatitis.

Dr. Talakoub is in private practice in McLean, Va.

Could it be the carbs?

In my practice, I have observed consistent improvements in recalcitrant perioral dermatitis when patients switch to low-carbohydrate diets. Several of my patients with perioral dermatitis that responded poorly to oral doxycycline, topical metronidazole, and topical tacrolimus – or recurred upon cessation of therapy – have proven to have gluten sensitivity or intolerance. Their skin condition improves when they go on a gluten-free diet. But I have also seen considerable improvements after patients undertake low-carbohydrate, high-protein diets, even if those patients have no diagnosed gluten sensitivity. These improvements have occurred with minimal oral and topical treatments, and these patients have not experienced recurrences.

There have been no well-controlled studies, or even case reports to my knowledge, linking carbohydrate or gluten intake to perioral dermatitis. Could the improvement be serendipitous, or is there some basis for carbohydrates contributing to inflammatory status in the oral and gastrointestinal mucosa?

Alcohol, spicy foods, and chocolate have been linked to exacerbation of erythemogenic and papulopustular rosacea. However, the precipitating ingredients in these foods have not been identified. Could the common link simply be an abundance of carbohydrates?

More studies are needed to better define the role of diet in perioral dermatitis. In the meantime, I am seeing good results with low-carb/carb-free diets and will continue to suggest them to prevent recurrences in my patients with perioral dermatitis.

Dr. Talakoub is in private practice in McLean, Va.

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First-in-man bioengineered graft proves enduring for vascular access

Tissue-engineered graft fills a medical need
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First-in-man bioengineered graft proves enduring for vascular access

DALLAS – An investigational tissue-engineered vascular graft has enduring potential for vascular access for hemodialysis in patients with end-stage renal disease, based on early clinical results.

Moreover, other potential uses are on the horizon. The big picture involves subsequent extrapolation of this technology from the large-diameter, high-flow bioengineered vessels required for hemodialysis to the creation of small-diameter, low-flow vessels for coronary artery and peripheral arterial graft surgery, Dr. Jeffrey H. Lawson explained at the American Heart Association scientific sessions.

Dr. Jeffrey H. Lawson

"Our goal is to make a tissue-engineered conduit that could be used widely throughout the body," said Dr. Lawson, professor of surgery and of pathology at Duke University Medical Center, Durham, N.C.

He presented the results from the first-in-man, ongoing phase I clinical experience with the Humacyte graft, which to date has been implanted to provide vascular access for hemodialysis in 28 patients, with 6-month patency as the primary study endpoint. This was a challenging study population, with an average of 4.1 previous access procedure failures per patient. The presentation at the AHA was the first public disclosure of the results of a project Dr. Lawson has been working on for more than 15 years. His surgical colleagues from Poland, who have done the implantations in patients with end-stage renal disease, were in attendance.

The overall 6-month patency was 100%, with no infections, no sign of an immune response, and no aneurysms or other indication of structural degeneration, he said.

Of the 28 patients, 20 had no further interventions, yielding a primary unassisted 6-month patency rate of 71%. Eight patients collectively underwent 10 interventions to maintain patency: eight had thrombectomies for graft- or surgically related thrombosis and two had venous anastomoses. Flow rates have remained suitable for dialysis in all patients, and the grafts are being used for dialysis three times per week. Dr. Lawson described the grafts as easy to cannulate via standard techniques.

He characterized these initial results as "quite remarkable" compared with the outcomes in two large studies of the current benchmark technologies, which are synthetic grafts made of PTFE (polytetrafluoroethyline). In those studies, the primary patency rate at 6 months was less than 50%, with a secondary patency rate of 77% and a 10% infection rate. In other studies, 30%-40% of PTFE grafts are abandoned within 12 months due to loss of patency.

The process of creating the bioengineered grafts begins with harvesting human aortic vascular smooth muscle cells, seeding them on a biodegradable matrix, then culturing them under pulsatile conditions. When the biodegradable matrix melts away, what remains is a tube comprised of vascular smooth muscle cells and extracellular matrix. This is then decellularized, yielding a tube of extracellular matrix that can be shipped off the shelf and around the world.

In primate models, the implanted bioengineered graft has been shown to repopulate with the host’s own vascular smooth muscle cells lined intimally by endothelium.

"Where we implanted an acellular structure, it appears to now be a living tissue, suggesting [the graft] has become their tissue, not ours," Dr. Lawson said.

To date, none of the bioengineered grafts implanted in patients has been explanted, so it’s unknown whether the favorable histologic changes seen in primates’ grafts also occur in humans. Larger clinical trials with longer follow-up are planned in order to assess the bioengineered graft’s durability.

Dr. Lawson’s study is funded by a Department of Defense research grant and by Humacyte. He serves as a consultant to the company.

[email protected]

Body

This work is exciting. The early patency, thrombosis, and infection rates are encouraging.

The unmet clinical need for better ways to provide vascular access for hemodialysis is huge. There are 450,000 U.S. patients with end-stage renal disease on long-term hemodialysis. In this population, hemodialysis access morbidity costs more than $1 billion per year. Although the preferred means of vascular access is an arteriovenous fistula, many hemodialysis patients don’t have suitable veins. And 60% of fistulas become unusable within 6 months.


Dr. Sanjay Misra

We’ve got a conundrum where PTFE grafts have their problems and fistulas have their own problems. We don’t have a good clinical armamentarium.

Synthetic grafts most often lose patency because of venous outflow tract stenosis due to intimal hyperplasia. Balloon angioplasty of the stenotic anastomosis has been the conventional treatment to restore patency, but a landmark randomized trial carried out several years ago (N. Engl. J. Med. 2010;362:494-503) showed the patency rate was a mere 23%, significantly worse than the 51% patency rate with a PTFE-covered stent graft – and even that 51% patency rate, is abysmal.

Dr. Sanjay Misra is professor of radiology at the Mayo Clinic in Rochester, Minn. He was the invited discussant of the paper at the meeting and declared having no relevant financial disclosures.

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Body

This work is exciting. The early patency, thrombosis, and infection rates are encouraging.

The unmet clinical need for better ways to provide vascular access for hemodialysis is huge. There are 450,000 U.S. patients with end-stage renal disease on long-term hemodialysis. In this population, hemodialysis access morbidity costs more than $1 billion per year. Although the preferred means of vascular access is an arteriovenous fistula, many hemodialysis patients don’t have suitable veins. And 60% of fistulas become unusable within 6 months.


Dr. Sanjay Misra

We’ve got a conundrum where PTFE grafts have their problems and fistulas have their own problems. We don’t have a good clinical armamentarium.

Synthetic grafts most often lose patency because of venous outflow tract stenosis due to intimal hyperplasia. Balloon angioplasty of the stenotic anastomosis has been the conventional treatment to restore patency, but a landmark randomized trial carried out several years ago (N. Engl. J. Med. 2010;362:494-503) showed the patency rate was a mere 23%, significantly worse than the 51% patency rate with a PTFE-covered stent graft – and even that 51% patency rate, is abysmal.

Dr. Sanjay Misra is professor of radiology at the Mayo Clinic in Rochester, Minn. He was the invited discussant of the paper at the meeting and declared having no relevant financial disclosures.

Body

This work is exciting. The early patency, thrombosis, and infection rates are encouraging.

The unmet clinical need for better ways to provide vascular access for hemodialysis is huge. There are 450,000 U.S. patients with end-stage renal disease on long-term hemodialysis. In this population, hemodialysis access morbidity costs more than $1 billion per year. Although the preferred means of vascular access is an arteriovenous fistula, many hemodialysis patients don’t have suitable veins. And 60% of fistulas become unusable within 6 months.


Dr. Sanjay Misra

We’ve got a conundrum where PTFE grafts have their problems and fistulas have their own problems. We don’t have a good clinical armamentarium.

Synthetic grafts most often lose patency because of venous outflow tract stenosis due to intimal hyperplasia. Balloon angioplasty of the stenotic anastomosis has been the conventional treatment to restore patency, but a landmark randomized trial carried out several years ago (N. Engl. J. Med. 2010;362:494-503) showed the patency rate was a mere 23%, significantly worse than the 51% patency rate with a PTFE-covered stent graft – and even that 51% patency rate, is abysmal.

Dr. Sanjay Misra is professor of radiology at the Mayo Clinic in Rochester, Minn. He was the invited discussant of the paper at the meeting and declared having no relevant financial disclosures.

Title
Tissue-engineered graft fills a medical need
Tissue-engineered graft fills a medical need

DALLAS – An investigational tissue-engineered vascular graft has enduring potential for vascular access for hemodialysis in patients with end-stage renal disease, based on early clinical results.

Moreover, other potential uses are on the horizon. The big picture involves subsequent extrapolation of this technology from the large-diameter, high-flow bioengineered vessels required for hemodialysis to the creation of small-diameter, low-flow vessels for coronary artery and peripheral arterial graft surgery, Dr. Jeffrey H. Lawson explained at the American Heart Association scientific sessions.

Dr. Jeffrey H. Lawson

"Our goal is to make a tissue-engineered conduit that could be used widely throughout the body," said Dr. Lawson, professor of surgery and of pathology at Duke University Medical Center, Durham, N.C.

He presented the results from the first-in-man, ongoing phase I clinical experience with the Humacyte graft, which to date has been implanted to provide vascular access for hemodialysis in 28 patients, with 6-month patency as the primary study endpoint. This was a challenging study population, with an average of 4.1 previous access procedure failures per patient. The presentation at the AHA was the first public disclosure of the results of a project Dr. Lawson has been working on for more than 15 years. His surgical colleagues from Poland, who have done the implantations in patients with end-stage renal disease, were in attendance.

The overall 6-month patency was 100%, with no infections, no sign of an immune response, and no aneurysms or other indication of structural degeneration, he said.

Of the 28 patients, 20 had no further interventions, yielding a primary unassisted 6-month patency rate of 71%. Eight patients collectively underwent 10 interventions to maintain patency: eight had thrombectomies for graft- or surgically related thrombosis and two had venous anastomoses. Flow rates have remained suitable for dialysis in all patients, and the grafts are being used for dialysis three times per week. Dr. Lawson described the grafts as easy to cannulate via standard techniques.

He characterized these initial results as "quite remarkable" compared with the outcomes in two large studies of the current benchmark technologies, which are synthetic grafts made of PTFE (polytetrafluoroethyline). In those studies, the primary patency rate at 6 months was less than 50%, with a secondary patency rate of 77% and a 10% infection rate. In other studies, 30%-40% of PTFE grafts are abandoned within 12 months due to loss of patency.

The process of creating the bioengineered grafts begins with harvesting human aortic vascular smooth muscle cells, seeding them on a biodegradable matrix, then culturing them under pulsatile conditions. When the biodegradable matrix melts away, what remains is a tube comprised of vascular smooth muscle cells and extracellular matrix. This is then decellularized, yielding a tube of extracellular matrix that can be shipped off the shelf and around the world.

In primate models, the implanted bioengineered graft has been shown to repopulate with the host’s own vascular smooth muscle cells lined intimally by endothelium.

"Where we implanted an acellular structure, it appears to now be a living tissue, suggesting [the graft] has become their tissue, not ours," Dr. Lawson said.

To date, none of the bioengineered grafts implanted in patients has been explanted, so it’s unknown whether the favorable histologic changes seen in primates’ grafts also occur in humans. Larger clinical trials with longer follow-up are planned in order to assess the bioengineered graft’s durability.

Dr. Lawson’s study is funded by a Department of Defense research grant and by Humacyte. He serves as a consultant to the company.

[email protected]

DALLAS – An investigational tissue-engineered vascular graft has enduring potential for vascular access for hemodialysis in patients with end-stage renal disease, based on early clinical results.

Moreover, other potential uses are on the horizon. The big picture involves subsequent extrapolation of this technology from the large-diameter, high-flow bioengineered vessels required for hemodialysis to the creation of small-diameter, low-flow vessels for coronary artery and peripheral arterial graft surgery, Dr. Jeffrey H. Lawson explained at the American Heart Association scientific sessions.

Dr. Jeffrey H. Lawson

"Our goal is to make a tissue-engineered conduit that could be used widely throughout the body," said Dr. Lawson, professor of surgery and of pathology at Duke University Medical Center, Durham, N.C.

He presented the results from the first-in-man, ongoing phase I clinical experience with the Humacyte graft, which to date has been implanted to provide vascular access for hemodialysis in 28 patients, with 6-month patency as the primary study endpoint. This was a challenging study population, with an average of 4.1 previous access procedure failures per patient. The presentation at the AHA was the first public disclosure of the results of a project Dr. Lawson has been working on for more than 15 years. His surgical colleagues from Poland, who have done the implantations in patients with end-stage renal disease, were in attendance.

The overall 6-month patency was 100%, with no infections, no sign of an immune response, and no aneurysms or other indication of structural degeneration, he said.

Of the 28 patients, 20 had no further interventions, yielding a primary unassisted 6-month patency rate of 71%. Eight patients collectively underwent 10 interventions to maintain patency: eight had thrombectomies for graft- or surgically related thrombosis and two had venous anastomoses. Flow rates have remained suitable for dialysis in all patients, and the grafts are being used for dialysis three times per week. Dr. Lawson described the grafts as easy to cannulate via standard techniques.

He characterized these initial results as "quite remarkable" compared with the outcomes in two large studies of the current benchmark technologies, which are synthetic grafts made of PTFE (polytetrafluoroethyline). In those studies, the primary patency rate at 6 months was less than 50%, with a secondary patency rate of 77% and a 10% infection rate. In other studies, 30%-40% of PTFE grafts are abandoned within 12 months due to loss of patency.

The process of creating the bioengineered grafts begins with harvesting human aortic vascular smooth muscle cells, seeding them on a biodegradable matrix, then culturing them under pulsatile conditions. When the biodegradable matrix melts away, what remains is a tube comprised of vascular smooth muscle cells and extracellular matrix. This is then decellularized, yielding a tube of extracellular matrix that can be shipped off the shelf and around the world.

In primate models, the implanted bioengineered graft has been shown to repopulate with the host’s own vascular smooth muscle cells lined intimally by endothelium.

"Where we implanted an acellular structure, it appears to now be a living tissue, suggesting [the graft] has become their tissue, not ours," Dr. Lawson said.

To date, none of the bioengineered grafts implanted in patients has been explanted, so it’s unknown whether the favorable histologic changes seen in primates’ grafts also occur in humans. Larger clinical trials with longer follow-up are planned in order to assess the bioengineered graft’s durability.

Dr. Lawson’s study is funded by a Department of Defense research grant and by Humacyte. He serves as a consultant to the company.

[email protected]

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Major finding: The 6-month enduring patency rate of an investigational tissue-engineered vascular graft for hemodialysis access was 100%, markedly better than rates achievable with synthetic PTFE grafts, the current benchmark technology.

Data source: An initial report from an ongoing prospective first-in-man study in which, to date, 28 patients with end-stage renal disease have been implanted with a novel tissue-engineered vascular graft for use as a hemodialysis access.

Disclosures: The study was funded by the Department of Defense and Humacyte. The presenter is a consultant to the company.

Is Spreading Pain Due to Injury?

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Is Spreading Pain Due to Injury?

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The radiograph shows a right apical mass. This clinical and radiographic presentation is strongly suggestive of a Pancoast tumor. Such lung masses (typically non–small cell carcinomas) can cause brachial plexus compression when they progress, which results in thoracic outlet obstruction and symptoms similar to those seen in this patient. 

The patient was admitted by a hospitalist service, and further imaging did confirm the presence of a lung mass, as well as extension to the chest wall and cervicothoracic portion of the spinal canal. CT-guided biopsy of the mass is pending.

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The radiograph shows a right apical mass. This clinical and radiographic presentation is strongly suggestive of a Pancoast tumor. Such lung masses (typically non–small cell carcinomas) can cause brachial plexus compression when they progress, which results in thoracic outlet obstruction and symptoms similar to those seen in this patient. 

The patient was admitted by a hospitalist service, and further imaging did confirm the presence of a lung mass, as well as extension to the chest wall and cervicothoracic portion of the spinal canal. CT-guided biopsy of the mass is pending.

Answer

The radiograph shows a right apical mass. This clinical and radiographic presentation is strongly suggestive of a Pancoast tumor. Such lung masses (typically non–small cell carcinomas) can cause brachial plexus compression when they progress, which results in thoracic outlet obstruction and symptoms similar to those seen in this patient. 

The patient was admitted by a hospitalist service, and further imaging did confirm the presence of a lung mass, as well as extension to the chest wall and cervicothoracic portion of the spinal canal. CT-guided biopsy of the mass is pending.

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A 53-year-old woman presents with complaints of right-side chest wall, neck, and shoulder pain. Her symptoms started two months ago, when she says she injured herself while doing yard work. She initially self-treated but subsequently went to various emergency departments and walk-in clinics on several occasions; no definitive diagnosis was established. Recently, she has noticed increasing weakness in her right arm and hand as well. Medical history is significant for hypertension. Family history is remarkable for non-Hodgkin’s lymphoma (mother). Social history reveals that the patient is a smoker, with a pack-a-day habit for at least 40 years. On physical exam, you note normal vital signs. The patient has good range of motion in her extremities; however, the strength in her right upper extremity is significantly diminished. Her deltoid, biceps, triceps, and hand grip are all about 2/5. She also notes a paresthesia along her right anterior chest wall, although sensation is intact. Chest radiograph is ordered (shown). What is your impression?
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Man, 45, With Greasy Rash and Deformed Nails

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Man, 45, With Greasy Rash and Deformed Nails

A 45-year-old man presented to the dermatology office complaining of a pruritic rash on his neck, chest, abdomen, and upper back. The rash had been present since the patient was 20, intermittently flaring and causing severe pruritus. For the past two weeks, it had become increasingly bothersome.

The patient described the rash as “greasy” brown plaques diffusely scattered on his body. The rash on his neck was the most bothersome, and the patient felt an uncontrollable need to scratch that area.

Since it first developed 25 years ago, he had used OTC hydro­cortisone cream as needed to treat the rash. Although effective for past flares, the cream provided only minimal relief during the current episode.

The patient’s medical history included brittle nails with a worsening of nail quality in recent years. The family history revealed that the patient’s father and sister were affected by the same type of rash, which developed in adolescence for each of them, as well as brittle nails.

On physical examination, the skin was warm and moist to the touch. Flat, slightly elevated, greasy brown papules were scattered on the chest, abdomen, and ­upper back, with mild surrounding erythema (see Figure 1). Excoriated lesions were noted on the anterior surface of the neck, with pinpoint bleeding resulting from constant irritation. The patient’s fingernails were deformed, with longitudinal ridges and v-shaped notching of the free margin. The remainder of the physical exam was unremarkable, and review of systems was negative.

This patient’s symptoms could result from a variety of causes. Seborrheic dermatitis is a common skin condition that presents with brown plaques similar to those on the patient’s trunk. Another possible diagnosis is Grover’s disease, a rare disorder also known as transient acantholytic dermatosis, in which keratotic plaques appear on the torso and are thought to occur from trauma to sun-damaged skin. An additional consideration is Hailey-Hailey disease, a rare genetic disorder also known as benign familial pemphigus, which is characterized by red-brown plaques located predominantly on flexure surfaces.1 Skin biopsy should be performed for a definitive diagnosis.

Given the family history of a similar rash occurring in first-degree relatives and the distinct physical exam findings, the most likely diagnosis for this patient is keratosis follicularis, also known as Darier disease (DD) or Darier-White disease.

DISCUSSION

Named after Ferdinand-Jean Darier, who discovered this rare genodermatosis, DD is a rare genetic skin disorder caused by mutations of the ATP2A2 gene, located on the long arm of chromosome 12 at position 24,11.1,2 The mutation disrupts the encoding of the enzyme sarco/endoplasmic reticulum calcium-ATPase 2 (SERCA2). This enzyme is important in the transport of calcium ions across the cell membrane, and insufficient amounts lead to a defect in intracellular calcium signaling.2,3

This genetic mutation is inherited as an autosomal dominant trait with complete penetrance. DD affects men and women equally, with progressive skin signs of interfamilial and intrafamilial variability.4 Skin manifestations occur from late childhood to early adulthood and are typical during adolescence.4 Acute flare-ups can be triggered by heat, perspiration, sunlight, ultraviolet B exposure, stress, or certain medications (in particular, lithium).2 DD is not contagious.2

CLINICAL PRESENTATION

The characteristics of DD include yellow or brown, rough, firm papules that are frequently crusted. The papules often appear in seborrheic areas of the body, such as the chest, back, ears, nasolabial fold, forehead, scalp, and groin.4 The severity of expression varies from mild, with few lesions, to severe, in which the entire body is covered with disfiguring, macerated plaques emitting a strong odor. On biopsy, the histopathologic findings are typical of dyskeratosis and acantholysis.4

Fingernails (and occasionally toenails) display broad, white or red, somewhat translucent, longitudinal bands accompanied by v-shaped notching1,4,5 (see Figure 2). Such nail changes are diagnostic and occur in 92% to 95% of patients with DD.6 They may, in fact, occur in the absence of cutaneous disease. All nails may be affected, but usually only two to three are involved.6

 

Although uncommon in DD, white, umbilicated, or cobblestone plaques may be found on intraoral mucous membranes (ie, tongue, buccal mucosa, palate, epiglottis, pharyngeal wall, and esophagus); due to confluence, papules may mimic leukoplakia.7 Lesions may also appear on the vulva or rectum.1,5 In severe cases, the salivary glands can become blocked, and the gums can hypertrophy.5

Since epidermal and brain tissue both derive from ectoderm, pathologic processes that affect one organ system may also affect the other.8 Indeed, among patients with DD, neuropsychiatric problems—including epilepsy, learning difficulties, and schizoaffective disorder—are commonly reported.1 To confirm an association between DD and ATP2A2 mutations, Jacobsen and colleagues performed an analysis of 19 unrelated DD patients with neuropsychiatric phenotypes. They discovered evidence to support the gene’s pleiotropic effects in the brain and hypothesized that mutations in the enzyme SERCA2 correlate with these phenotypes, most specifically for mood disorders.9

 

 

TREATMENT AND MANAGEMENT

Although no cure is currently available for DD, both short- and long-term treatment options are available; the choice should be based on the severity of an individual patient’s signs and symptoms. For mild cases, topical therapy, such as general emollients, corticosteroid ointments, and high sun protection factor sunscreen, is sufficient.1

For moderate cases, topical retinoids, including tretinoin cream, adapalene gel or cream, and tazarotene gel, may be necessary.4 Keratolytics, including salicylic acid in propylene glycol gel, may be used to regulate hyperkeratosis.4 Celecoxib, a COX-2 inhibitor, is another option that may restore the down regulation of SERCA2. This can prevent progression of the disease.10

 Long-term management includes use of oral retinoid therapy (eg, acitretin), which might reduce the frequency of inflammatory flares.1 Systemic adverse effects from long-term use of oral retinoids are cause for concern, however. Close monitoring along with patient education can limit the occurrence of complications.11

If DD is uncontrolled with medication, dermabrasion and erbium:YAG laser ablation have been used to successfully treat chronic cases.12 Although these treatment options may remove existing lesions, it is important to inform patients that the disease has not been cured, that remission is difficult to attain, and that lesions may recur.

Because viral, bacterial, and fungal superinfections are common and may exacerbate the disease, be sure to check for signs of infection while examining the patient.4 Patients should be advised to avoid hot environments, and if that is not possible, to dress in cool cotton clothing to allow for proper ventilation and avoid the build-up of perspiration. Excessive perspiration along with poor hygiene can contribute to the formation of infections as well as trigger a flare-up. If an infection develops, patients should consult a health care provider.

Keeping the skin well moisturized can alleviate the constant pruritus that many patients experience. Daily sunscreen use is essential to avoid skin irritation caused by the sun, which can trigger an acute flare-up. Patients should be advised to avoid the long-term use of corticosteroid ointment. They should also contact their health care provider before using OTC treatments such as Burow’s solution.

CONCLUSION

A thorough history and physical exam are crucial in the diagnosis of DD. In this particular case, inquiry into family history was the key to proper diagnosis. That information, paired with a thorough physical exam, led to the correct diagnosis of this rare genetic skin disorder. A skin biopsy provided definitive confirmation.

This patient had a mild-to-moderate manifestation of DD. He was prescribed retinoid therapy, and routine follow-up visits were recommended to monitor the efficacy of medical therapy and to screen for secondary infections or neuropsychiatric disorders.

This case illustrates the importance of taking a full history and performing an in-depth physical exam when a patient presents with an unfamiliar complaint. Being thorough reduces the risk of missing a crucial element that can guide the diagnostic process.

REFERENCES

1. Creamer D, Barker J, Kerdel FA. Papular and papulosquamous dermatoses. In: Acute Adult Dermatology: Diagnosis and Management (A Colour Handbook). London, UK: Manson Publishing Ltd; 2011:48.

2. Kelly EB. Darier disease (DAR). In: Encyclopedia of Human Genetics and Disease. Santa Barbara, CA: ABC-CLIO; 2013:186-187.

3. Klausegger A, Laimer M, Bauer JW. Darier disease. [In German.] Haut­arzt. 2013;64:22-25.

4. Ringpfeil F. Dermatologic disorders. In: NORD Guide to Rare Disorders. Philadelphia, PA: Lippincott Williams & Wilkins; 2003:101.

5. Disorders of keratinization. In: Ostler HB, Maibach HI, Hoke AW, Schwab IR, eds. Diseases of the Eye and Skin: A Color Atlas. Philadelphia, PA: Lippincott Williams & Wilkins; 2004:23-34.

6. Baran R, de Berker D, Holzberg M, Thomas L, eds. Baran & Dawber’s Diseases of the Nails and their Management. 4th ed. West Sussex, UK: John Wiley & Sons, Ltd; 2012:295-296.

7. Thiagarajan MK, Narasimhan M, Sankarasubramanian A. Darier disease with oral and esophageal involvement: a case report. Indian J Dent Res. 2011;22:843-846.

8. Medansky RS, Woloshin AA. Darier’s disease: an evaluation of its neuropsychiatric component. Arch Dermatol. 1961;84:482-484.

9. Jacobsen NJ, Lyons I, Hoogendoorn B, et al. ATP2A2 mutations in Darier’s disease and their relationship to neuropsychiatric phenotypes. Hum Mol Genet. 1999;8:1631-1636.

10. Kamijo M, Nishiyama C, Takagi A, et al. Cyclooxygenase-2 inhibition restores ultraviolet B-induced downregulation of ATP2A2/SERCA2 in keratinocytes: possible therapeutic approach of cyclooxygenase-2 inhibition for treatment of Darier disease. Br J Dermatol. 2012;166: 1017-1022.

11. Brecher AR, Orlow SJ. Oral retinoid therapy for dermatologic conditions in children and adolescents. J Am Acad Dermatol. 2003;49:171-182.

12. Beier C, Kaufmann R. Efficacy of erbium:YAG laser ablation in Darier disease and Hailey-Hailey disease. Arch Dermatol. 1999;35:423-427.

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A 45-year-old man presented to the dermatology office complaining of a pruritic rash on his neck, chest, abdomen, and upper back. The rash had been present since the patient was 20, intermittently flaring and causing severe pruritus. For the past two weeks, it had become increasingly bothersome.

The patient described the rash as “greasy” brown plaques diffusely scattered on his body. The rash on his neck was the most bothersome, and the patient felt an uncontrollable need to scratch that area.

Since it first developed 25 years ago, he had used OTC hydro­cortisone cream as needed to treat the rash. Although effective for past flares, the cream provided only minimal relief during the current episode.

The patient’s medical history included brittle nails with a worsening of nail quality in recent years. The family history revealed that the patient’s father and sister were affected by the same type of rash, which developed in adolescence for each of them, as well as brittle nails.

On physical examination, the skin was warm and moist to the touch. Flat, slightly elevated, greasy brown papules were scattered on the chest, abdomen, and ­upper back, with mild surrounding erythema (see Figure 1). Excoriated lesions were noted on the anterior surface of the neck, with pinpoint bleeding resulting from constant irritation. The patient’s fingernails were deformed, with longitudinal ridges and v-shaped notching of the free margin. The remainder of the physical exam was unremarkable, and review of systems was negative.

This patient’s symptoms could result from a variety of causes. Seborrheic dermatitis is a common skin condition that presents with brown plaques similar to those on the patient’s trunk. Another possible diagnosis is Grover’s disease, a rare disorder also known as transient acantholytic dermatosis, in which keratotic plaques appear on the torso and are thought to occur from trauma to sun-damaged skin. An additional consideration is Hailey-Hailey disease, a rare genetic disorder also known as benign familial pemphigus, which is characterized by red-brown plaques located predominantly on flexure surfaces.1 Skin biopsy should be performed for a definitive diagnosis.

Given the family history of a similar rash occurring in first-degree relatives and the distinct physical exam findings, the most likely diagnosis for this patient is keratosis follicularis, also known as Darier disease (DD) or Darier-White disease.

DISCUSSION

Named after Ferdinand-Jean Darier, who discovered this rare genodermatosis, DD is a rare genetic skin disorder caused by mutations of the ATP2A2 gene, located on the long arm of chromosome 12 at position 24,11.1,2 The mutation disrupts the encoding of the enzyme sarco/endoplasmic reticulum calcium-ATPase 2 (SERCA2). This enzyme is important in the transport of calcium ions across the cell membrane, and insufficient amounts lead to a defect in intracellular calcium signaling.2,3

This genetic mutation is inherited as an autosomal dominant trait with complete penetrance. DD affects men and women equally, with progressive skin signs of interfamilial and intrafamilial variability.4 Skin manifestations occur from late childhood to early adulthood and are typical during adolescence.4 Acute flare-ups can be triggered by heat, perspiration, sunlight, ultraviolet B exposure, stress, or certain medications (in particular, lithium).2 DD is not contagious.2

CLINICAL PRESENTATION

The characteristics of DD include yellow or brown, rough, firm papules that are frequently crusted. The papules often appear in seborrheic areas of the body, such as the chest, back, ears, nasolabial fold, forehead, scalp, and groin.4 The severity of expression varies from mild, with few lesions, to severe, in which the entire body is covered with disfiguring, macerated plaques emitting a strong odor. On biopsy, the histopathologic findings are typical of dyskeratosis and acantholysis.4

Fingernails (and occasionally toenails) display broad, white or red, somewhat translucent, longitudinal bands accompanied by v-shaped notching1,4,5 (see Figure 2). Such nail changes are diagnostic and occur in 92% to 95% of patients with DD.6 They may, in fact, occur in the absence of cutaneous disease. All nails may be affected, but usually only two to three are involved.6

 

Although uncommon in DD, white, umbilicated, or cobblestone plaques may be found on intraoral mucous membranes (ie, tongue, buccal mucosa, palate, epiglottis, pharyngeal wall, and esophagus); due to confluence, papules may mimic leukoplakia.7 Lesions may also appear on the vulva or rectum.1,5 In severe cases, the salivary glands can become blocked, and the gums can hypertrophy.5

Since epidermal and brain tissue both derive from ectoderm, pathologic processes that affect one organ system may also affect the other.8 Indeed, among patients with DD, neuropsychiatric problems—including epilepsy, learning difficulties, and schizoaffective disorder—are commonly reported.1 To confirm an association between DD and ATP2A2 mutations, Jacobsen and colleagues performed an analysis of 19 unrelated DD patients with neuropsychiatric phenotypes. They discovered evidence to support the gene’s pleiotropic effects in the brain and hypothesized that mutations in the enzyme SERCA2 correlate with these phenotypes, most specifically for mood disorders.9

 

 

TREATMENT AND MANAGEMENT

Although no cure is currently available for DD, both short- and long-term treatment options are available; the choice should be based on the severity of an individual patient’s signs and symptoms. For mild cases, topical therapy, such as general emollients, corticosteroid ointments, and high sun protection factor sunscreen, is sufficient.1

For moderate cases, topical retinoids, including tretinoin cream, adapalene gel or cream, and tazarotene gel, may be necessary.4 Keratolytics, including salicylic acid in propylene glycol gel, may be used to regulate hyperkeratosis.4 Celecoxib, a COX-2 inhibitor, is another option that may restore the down regulation of SERCA2. This can prevent progression of the disease.10

 Long-term management includes use of oral retinoid therapy (eg, acitretin), which might reduce the frequency of inflammatory flares.1 Systemic adverse effects from long-term use of oral retinoids are cause for concern, however. Close monitoring along with patient education can limit the occurrence of complications.11

If DD is uncontrolled with medication, dermabrasion and erbium:YAG laser ablation have been used to successfully treat chronic cases.12 Although these treatment options may remove existing lesions, it is important to inform patients that the disease has not been cured, that remission is difficult to attain, and that lesions may recur.

Because viral, bacterial, and fungal superinfections are common and may exacerbate the disease, be sure to check for signs of infection while examining the patient.4 Patients should be advised to avoid hot environments, and if that is not possible, to dress in cool cotton clothing to allow for proper ventilation and avoid the build-up of perspiration. Excessive perspiration along with poor hygiene can contribute to the formation of infections as well as trigger a flare-up. If an infection develops, patients should consult a health care provider.

Keeping the skin well moisturized can alleviate the constant pruritus that many patients experience. Daily sunscreen use is essential to avoid skin irritation caused by the sun, which can trigger an acute flare-up. Patients should be advised to avoid the long-term use of corticosteroid ointment. They should also contact their health care provider before using OTC treatments such as Burow’s solution.

CONCLUSION

A thorough history and physical exam are crucial in the diagnosis of DD. In this particular case, inquiry into family history was the key to proper diagnosis. That information, paired with a thorough physical exam, led to the correct diagnosis of this rare genetic skin disorder. A skin biopsy provided definitive confirmation.

This patient had a mild-to-moderate manifestation of DD. He was prescribed retinoid therapy, and routine follow-up visits were recommended to monitor the efficacy of medical therapy and to screen for secondary infections or neuropsychiatric disorders.

This case illustrates the importance of taking a full history and performing an in-depth physical exam when a patient presents with an unfamiliar complaint. Being thorough reduces the risk of missing a crucial element that can guide the diagnostic process.

REFERENCES

1. Creamer D, Barker J, Kerdel FA. Papular and papulosquamous dermatoses. In: Acute Adult Dermatology: Diagnosis and Management (A Colour Handbook). London, UK: Manson Publishing Ltd; 2011:48.

2. Kelly EB. Darier disease (DAR). In: Encyclopedia of Human Genetics and Disease. Santa Barbara, CA: ABC-CLIO; 2013:186-187.

3. Klausegger A, Laimer M, Bauer JW. Darier disease. [In German.] Haut­arzt. 2013;64:22-25.

4. Ringpfeil F. Dermatologic disorders. In: NORD Guide to Rare Disorders. Philadelphia, PA: Lippincott Williams & Wilkins; 2003:101.

5. Disorders of keratinization. In: Ostler HB, Maibach HI, Hoke AW, Schwab IR, eds. Diseases of the Eye and Skin: A Color Atlas. Philadelphia, PA: Lippincott Williams & Wilkins; 2004:23-34.

6. Baran R, de Berker D, Holzberg M, Thomas L, eds. Baran & Dawber’s Diseases of the Nails and their Management. 4th ed. West Sussex, UK: John Wiley & Sons, Ltd; 2012:295-296.

7. Thiagarajan MK, Narasimhan M, Sankarasubramanian A. Darier disease with oral and esophageal involvement: a case report. Indian J Dent Res. 2011;22:843-846.

8. Medansky RS, Woloshin AA. Darier’s disease: an evaluation of its neuropsychiatric component. Arch Dermatol. 1961;84:482-484.

9. Jacobsen NJ, Lyons I, Hoogendoorn B, et al. ATP2A2 mutations in Darier’s disease and their relationship to neuropsychiatric phenotypes. Hum Mol Genet. 1999;8:1631-1636.

10. Kamijo M, Nishiyama C, Takagi A, et al. Cyclooxygenase-2 inhibition restores ultraviolet B-induced downregulation of ATP2A2/SERCA2 in keratinocytes: possible therapeutic approach of cyclooxygenase-2 inhibition for treatment of Darier disease. Br J Dermatol. 2012;166: 1017-1022.

11. Brecher AR, Orlow SJ. Oral retinoid therapy for dermatologic conditions in children and adolescents. J Am Acad Dermatol. 2003;49:171-182.

12. Beier C, Kaufmann R. Efficacy of erbium:YAG laser ablation in Darier disease and Hailey-Hailey disease. Arch Dermatol. 1999;35:423-427.

A 45-year-old man presented to the dermatology office complaining of a pruritic rash on his neck, chest, abdomen, and upper back. The rash had been present since the patient was 20, intermittently flaring and causing severe pruritus. For the past two weeks, it had become increasingly bothersome.

The patient described the rash as “greasy” brown plaques diffusely scattered on his body. The rash on his neck was the most bothersome, and the patient felt an uncontrollable need to scratch that area.

Since it first developed 25 years ago, he had used OTC hydro­cortisone cream as needed to treat the rash. Although effective for past flares, the cream provided only minimal relief during the current episode.

The patient’s medical history included brittle nails with a worsening of nail quality in recent years. The family history revealed that the patient’s father and sister were affected by the same type of rash, which developed in adolescence for each of them, as well as brittle nails.

On physical examination, the skin was warm and moist to the touch. Flat, slightly elevated, greasy brown papules were scattered on the chest, abdomen, and ­upper back, with mild surrounding erythema (see Figure 1). Excoriated lesions were noted on the anterior surface of the neck, with pinpoint bleeding resulting from constant irritation. The patient’s fingernails were deformed, with longitudinal ridges and v-shaped notching of the free margin. The remainder of the physical exam was unremarkable, and review of systems was negative.

This patient’s symptoms could result from a variety of causes. Seborrheic dermatitis is a common skin condition that presents with brown plaques similar to those on the patient’s trunk. Another possible diagnosis is Grover’s disease, a rare disorder also known as transient acantholytic dermatosis, in which keratotic plaques appear on the torso and are thought to occur from trauma to sun-damaged skin. An additional consideration is Hailey-Hailey disease, a rare genetic disorder also known as benign familial pemphigus, which is characterized by red-brown plaques located predominantly on flexure surfaces.1 Skin biopsy should be performed for a definitive diagnosis.

Given the family history of a similar rash occurring in first-degree relatives and the distinct physical exam findings, the most likely diagnosis for this patient is keratosis follicularis, also known as Darier disease (DD) or Darier-White disease.

DISCUSSION

Named after Ferdinand-Jean Darier, who discovered this rare genodermatosis, DD is a rare genetic skin disorder caused by mutations of the ATP2A2 gene, located on the long arm of chromosome 12 at position 24,11.1,2 The mutation disrupts the encoding of the enzyme sarco/endoplasmic reticulum calcium-ATPase 2 (SERCA2). This enzyme is important in the transport of calcium ions across the cell membrane, and insufficient amounts lead to a defect in intracellular calcium signaling.2,3

This genetic mutation is inherited as an autosomal dominant trait with complete penetrance. DD affects men and women equally, with progressive skin signs of interfamilial and intrafamilial variability.4 Skin manifestations occur from late childhood to early adulthood and are typical during adolescence.4 Acute flare-ups can be triggered by heat, perspiration, sunlight, ultraviolet B exposure, stress, or certain medications (in particular, lithium).2 DD is not contagious.2

CLINICAL PRESENTATION

The characteristics of DD include yellow or brown, rough, firm papules that are frequently crusted. The papules often appear in seborrheic areas of the body, such as the chest, back, ears, nasolabial fold, forehead, scalp, and groin.4 The severity of expression varies from mild, with few lesions, to severe, in which the entire body is covered with disfiguring, macerated plaques emitting a strong odor. On biopsy, the histopathologic findings are typical of dyskeratosis and acantholysis.4

Fingernails (and occasionally toenails) display broad, white or red, somewhat translucent, longitudinal bands accompanied by v-shaped notching1,4,5 (see Figure 2). Such nail changes are diagnostic and occur in 92% to 95% of patients with DD.6 They may, in fact, occur in the absence of cutaneous disease. All nails may be affected, but usually only two to three are involved.6

 

Although uncommon in DD, white, umbilicated, or cobblestone plaques may be found on intraoral mucous membranes (ie, tongue, buccal mucosa, palate, epiglottis, pharyngeal wall, and esophagus); due to confluence, papules may mimic leukoplakia.7 Lesions may also appear on the vulva or rectum.1,5 In severe cases, the salivary glands can become blocked, and the gums can hypertrophy.5

Since epidermal and brain tissue both derive from ectoderm, pathologic processes that affect one organ system may also affect the other.8 Indeed, among patients with DD, neuropsychiatric problems—including epilepsy, learning difficulties, and schizoaffective disorder—are commonly reported.1 To confirm an association between DD and ATP2A2 mutations, Jacobsen and colleagues performed an analysis of 19 unrelated DD patients with neuropsychiatric phenotypes. They discovered evidence to support the gene’s pleiotropic effects in the brain and hypothesized that mutations in the enzyme SERCA2 correlate with these phenotypes, most specifically for mood disorders.9

 

 

TREATMENT AND MANAGEMENT

Although no cure is currently available for DD, both short- and long-term treatment options are available; the choice should be based on the severity of an individual patient’s signs and symptoms. For mild cases, topical therapy, such as general emollients, corticosteroid ointments, and high sun protection factor sunscreen, is sufficient.1

For moderate cases, topical retinoids, including tretinoin cream, adapalene gel or cream, and tazarotene gel, may be necessary.4 Keratolytics, including salicylic acid in propylene glycol gel, may be used to regulate hyperkeratosis.4 Celecoxib, a COX-2 inhibitor, is another option that may restore the down regulation of SERCA2. This can prevent progression of the disease.10

 Long-term management includes use of oral retinoid therapy (eg, acitretin), which might reduce the frequency of inflammatory flares.1 Systemic adverse effects from long-term use of oral retinoids are cause for concern, however. Close monitoring along with patient education can limit the occurrence of complications.11

If DD is uncontrolled with medication, dermabrasion and erbium:YAG laser ablation have been used to successfully treat chronic cases.12 Although these treatment options may remove existing lesions, it is important to inform patients that the disease has not been cured, that remission is difficult to attain, and that lesions may recur.

Because viral, bacterial, and fungal superinfections are common and may exacerbate the disease, be sure to check for signs of infection while examining the patient.4 Patients should be advised to avoid hot environments, and if that is not possible, to dress in cool cotton clothing to allow for proper ventilation and avoid the build-up of perspiration. Excessive perspiration along with poor hygiene can contribute to the formation of infections as well as trigger a flare-up. If an infection develops, patients should consult a health care provider.

Keeping the skin well moisturized can alleviate the constant pruritus that many patients experience. Daily sunscreen use is essential to avoid skin irritation caused by the sun, which can trigger an acute flare-up. Patients should be advised to avoid the long-term use of corticosteroid ointment. They should also contact their health care provider before using OTC treatments such as Burow’s solution.

CONCLUSION

A thorough history and physical exam are crucial in the diagnosis of DD. In this particular case, inquiry into family history was the key to proper diagnosis. That information, paired with a thorough physical exam, led to the correct diagnosis of this rare genetic skin disorder. A skin biopsy provided definitive confirmation.

This patient had a mild-to-moderate manifestation of DD. He was prescribed retinoid therapy, and routine follow-up visits were recommended to monitor the efficacy of medical therapy and to screen for secondary infections or neuropsychiatric disorders.

This case illustrates the importance of taking a full history and performing an in-depth physical exam when a patient presents with an unfamiliar complaint. Being thorough reduces the risk of missing a crucial element that can guide the diagnostic process.

REFERENCES

1. Creamer D, Barker J, Kerdel FA. Papular and papulosquamous dermatoses. In: Acute Adult Dermatology: Diagnosis and Management (A Colour Handbook). London, UK: Manson Publishing Ltd; 2011:48.

2. Kelly EB. Darier disease (DAR). In: Encyclopedia of Human Genetics and Disease. Santa Barbara, CA: ABC-CLIO; 2013:186-187.

3. Klausegger A, Laimer M, Bauer JW. Darier disease. [In German.] Haut­arzt. 2013;64:22-25.

4. Ringpfeil F. Dermatologic disorders. In: NORD Guide to Rare Disorders. Philadelphia, PA: Lippincott Williams & Wilkins; 2003:101.

5. Disorders of keratinization. In: Ostler HB, Maibach HI, Hoke AW, Schwab IR, eds. Diseases of the Eye and Skin: A Color Atlas. Philadelphia, PA: Lippincott Williams & Wilkins; 2004:23-34.

6. Baran R, de Berker D, Holzberg M, Thomas L, eds. Baran & Dawber’s Diseases of the Nails and their Management. 4th ed. West Sussex, UK: John Wiley & Sons, Ltd; 2012:295-296.

7. Thiagarajan MK, Narasimhan M, Sankarasubramanian A. Darier disease with oral and esophageal involvement: a case report. Indian J Dent Res. 2011;22:843-846.

8. Medansky RS, Woloshin AA. Darier’s disease: an evaluation of its neuropsychiatric component. Arch Dermatol. 1961;84:482-484.

9. Jacobsen NJ, Lyons I, Hoogendoorn B, et al. ATP2A2 mutations in Darier’s disease and their relationship to neuropsychiatric phenotypes. Hum Mol Genet. 1999;8:1631-1636.

10. Kamijo M, Nishiyama C, Takagi A, et al. Cyclooxygenase-2 inhibition restores ultraviolet B-induced downregulation of ATP2A2/SERCA2 in keratinocytes: possible therapeutic approach of cyclooxygenase-2 inhibition for treatment of Darier disease. Br J Dermatol. 2012;166: 1017-1022.

11. Brecher AR, Orlow SJ. Oral retinoid therapy for dermatologic conditions in children and adolescents. J Am Acad Dermatol. 2003;49:171-182.

12. Beier C, Kaufmann R. Efficacy of erbium:YAG laser ablation in Darier disease and Hailey-Hailey disease. Arch Dermatol. 1999;35:423-427.

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Former Farmer Is Short of Breath

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The correct interpretation of this ECG includes normal sinus rhythm with left atrial enlargement and a left bundle branch block (LBBB). Normal sinus rhythm is evidenced by a P wave associated with each QRS complex with a consistent PR interval.

Left atrial enlargement is evidenced by a P-wave duration ≥ 120 ms in lead II, a notched P wave in the limb leads with a peak duration ≥ 4 ms, and a terminal P-wave negativity in lead V1 with a duration ≥ 4 ms and a depth ≥ 1 mm.

An LBBB is illustrated by the QRS duration ≥ 120 ms, a dominant S wave in lead V1, broad monophasic R waves in the lateral leads (including I, aVL, V5, and V6), and R-wave peak times of > 60 ms in leads V5 and V6.

Further work-up revealed elevated left end-diastolic filling pressures, volume overload, and pulmonary edema consistent with diastolic heart failure. Given the unclear etiology of the LBBB, cardiac catheterization was performed. It revealed no significant coronary artery disease.

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ANSWER

The correct interpretation of this ECG includes normal sinus rhythm with left atrial enlargement and a left bundle branch block (LBBB). Normal sinus rhythm is evidenced by a P wave associated with each QRS complex with a consistent PR interval.

Left atrial enlargement is evidenced by a P-wave duration ≥ 120 ms in lead II, a notched P wave in the limb leads with a peak duration ≥ 4 ms, and a terminal P-wave negativity in lead V1 with a duration ≥ 4 ms and a depth ≥ 1 mm.

An LBBB is illustrated by the QRS duration ≥ 120 ms, a dominant S wave in lead V1, broad monophasic R waves in the lateral leads (including I, aVL, V5, and V6), and R-wave peak times of > 60 ms in leads V5 and V6.

Further work-up revealed elevated left end-diastolic filling pressures, volume overload, and pulmonary edema consistent with diastolic heart failure. Given the unclear etiology of the LBBB, cardiac catheterization was performed. It revealed no significant coronary artery disease.

ANSWER

The correct interpretation of this ECG includes normal sinus rhythm with left atrial enlargement and a left bundle branch block (LBBB). Normal sinus rhythm is evidenced by a P wave associated with each QRS complex with a consistent PR interval.

Left atrial enlargement is evidenced by a P-wave duration ≥ 120 ms in lead II, a notched P wave in the limb leads with a peak duration ≥ 4 ms, and a terminal P-wave negativity in lead V1 with a duration ≥ 4 ms and a depth ≥ 1 mm.

An LBBB is illustrated by the QRS duration ≥ 120 ms, a dominant S wave in lead V1, broad monophasic R waves in the lateral leads (including I, aVL, V5, and V6), and R-wave peak times of > 60 ms in leads V5 and V6.

Further work-up revealed elevated left end-diastolic filling pressures, volume overload, and pulmonary edema consistent with diastolic heart failure. Given the unclear etiology of the LBBB, cardiac catheterization was performed. It revealed no significant coronary artery disease.

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A 67-year-old man has a history of chronic dyspnea. He is a retired farmer who says he “never had time” to seek medical help for anything other than cuts or broken bones. In the past two months, he’s noticed that his dyspnea has progressively worsened. When questioned, he admits that his legs began swelling around that time as well. Two days ago, he awoke from sleep unable to catch his breath. This morning, while walking to his mailbox, he became profoundly short of breath. He sat down by the side of the road and called 911. When the ambulance arrived, he felt much better but agreed to be taken to the emergency department, since his wife is away and he’s home alone. When questioned by the paramedics, he denied having chest pain, palpitations, productive or nonproductive cough, polyuria, polydipsia, nausea, or vomiting. Medical history is positive for hypertension, gastroesophageal reflux disease (GERD), and hypertension. He has had several fractures in his right ankle and left femur, which are well healed. Surgical history is remarkable for a cholecystectomy and multiple laceration repairs on his arms and hands (also well healed). His current medications include one aspirin per day and “a handful” of calcium carbonate tablets. Although he was prescribed “several heart pills” for hypertension, he hasn’t taken them or refilled the prescriptions for at least five years. He is allergic to penicillin and sulfa. He denies recreational or homeopathic drug use. He has never smoked, and he drinks one or two shots of bourbon on weekends. Family history includes a father who died in a farming accident and a mother who died of cervical cancer at age 85. He has seven siblings, all of whom are alive and well. The review of systems is remarkable only for GERD. Physical exam reveals a well-developed, obese male with a height of 6 ft 4 in and a weight of 278 lb. Vital signs include a blood pressure of 184/98 mm Hg; pulse, 90 beats/min; and respiratory rate, 20 breaths/min-1. He is afebrile. The HEENT exam is remarkable for atrophic glossitis. The neck shows no evidence of thyromegaly, and there are no carotid bruits or jugular venous distention. The chest is remarkable for diffuse wheezing and crackles in all lung bases. The cardiac exam reveals a regular rate of 90 beats/min, with no evidence of murmurs, rubs, or gallops. The abdomen is obese. There is no evidence of ascites or masses. Evidence of 2+ pitting edema to the midcalf is present bilaterally. The neurologic exam is grossly intact, and the psychiatric exam reveals the patient to be alert and oriented, with a bright affect. The working diagnosis in the emergency department is acute or chronic heart failure. A chest x-ray reveals moderate-to-severe pulmonary edema, cardiomegaly, and small bilateral effusions. Pertinent laboratory data include a serum glucose of 200 mg/dL and a B-type natriuretic peptide level of 590 pg/mL. All other lab values are within normal limits. An ECG reveals the following: a ventricular rate of 93 beats/min; PR interval, 168 ms; QRS duration, 156 ms; QT/QTc interval, 430/534 ms; P axis, 52°; R axis, 9°; and T axis, 171°. What is your interpretation of this ECG?
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Hair Loss at a Very Young Age

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ANSWER

The correct answer is trichotillomania (choice “c”). See Discussion for more information.

Alopecia mucinosa (choice “a”) is a rare cause of focal hair loss that can occur in children. However, it usually presents with papules or plaques, unlike the smooth skin surface seen here.

Alopecia areata (choice “b”), common in children, typically entails complete hair loss in a given area—or, as hair regrows, with hairs of equal length. The uneven hairs seen in trichotillomania help a great deal in distinguishing it from alopecia areata.

Traction alopecia (choice “d”) is focal hair loss caused by chronic tension related to hairstyling. Most common in African-American women, and typically affecting the frontal periphery of the scalp, it is an unlikely explanation for hair loss in a 10-year-old boy.

DISCUSSION

Trichotillomania (TT) means, literally, “hair-pulling madness.” But in reality, there’s little actual plucking of hairs in this common condition. Instead, patients habitually manipulate hair by twirling and tugging, which weakens the shafts and follicles and renders them more susceptible to everyday wear and tear. In some cases, individual hairs speed through their growth phases and others break off in mid-shaft. All of this contributes to the classic “uneven” look of TT.

Patients with TT tend to be in the 4-to-17 age range, and most have issues with unresolved anxiety that manifest in part with manipulation of the hair. Officially considered an impulse control disorder, TT in most cases belongs to the psychiatrist’s domain.

In this case, it was enormously helpful to have corroboration from the patient and his mother regarding his role in creating and perpetuating the problem. Had that not been the case—or in the event of other doubts as to the correct diagnosis—biopsy could have been performed to rule out most of the other items in the differential, particularly alopecia areata.

Interestingly enough, studies have shown that the more sharply defined the area of hair loss, the more likely the patient is to admit his/her role in its creation. However, as is often the case with scientific research, contradictory findings have also been made.

TREATMENT

Treatment of TT is problematic, since no medications have proven to be completely helpful. Psychiatrists use a combination of medication, cognitive behavioral therapy, and other behavior modifications that are designed to overcome the habitual component of the problem. Most cases of TT resolve on their own, but in severe cases that persist for years, permanent hair loss can result.

In this case, there was enough insight and motivation on the part of the patient and his family to stop the offending behavior and allow the hair to regrow.

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ANSWER

The correct answer is trichotillomania (choice “c”). See Discussion for more information.

Alopecia mucinosa (choice “a”) is a rare cause of focal hair loss that can occur in children. However, it usually presents with papules or plaques, unlike the smooth skin surface seen here.

Alopecia areata (choice “b”), common in children, typically entails complete hair loss in a given area—or, as hair regrows, with hairs of equal length. The uneven hairs seen in trichotillomania help a great deal in distinguishing it from alopecia areata.

Traction alopecia (choice “d”) is focal hair loss caused by chronic tension related to hairstyling. Most common in African-American women, and typically affecting the frontal periphery of the scalp, it is an unlikely explanation for hair loss in a 10-year-old boy.

DISCUSSION

Trichotillomania (TT) means, literally, “hair-pulling madness.” But in reality, there’s little actual plucking of hairs in this common condition. Instead, patients habitually manipulate hair by twirling and tugging, which weakens the shafts and follicles and renders them more susceptible to everyday wear and tear. In some cases, individual hairs speed through their growth phases and others break off in mid-shaft. All of this contributes to the classic “uneven” look of TT.

Patients with TT tend to be in the 4-to-17 age range, and most have issues with unresolved anxiety that manifest in part with manipulation of the hair. Officially considered an impulse control disorder, TT in most cases belongs to the psychiatrist’s domain.

In this case, it was enormously helpful to have corroboration from the patient and his mother regarding his role in creating and perpetuating the problem. Had that not been the case—or in the event of other doubts as to the correct diagnosis—biopsy could have been performed to rule out most of the other items in the differential, particularly alopecia areata.

Interestingly enough, studies have shown that the more sharply defined the area of hair loss, the more likely the patient is to admit his/her role in its creation. However, as is often the case with scientific research, contradictory findings have also been made.

TREATMENT

Treatment of TT is problematic, since no medications have proven to be completely helpful. Psychiatrists use a combination of medication, cognitive behavioral therapy, and other behavior modifications that are designed to overcome the habitual component of the problem. Most cases of TT resolve on their own, but in severe cases that persist for years, permanent hair loss can result.

In this case, there was enough insight and motivation on the part of the patient and his family to stop the offending behavior and allow the hair to regrow.

ANSWER

The correct answer is trichotillomania (choice “c”). See Discussion for more information.

Alopecia mucinosa (choice “a”) is a rare cause of focal hair loss that can occur in children. However, it usually presents with papules or plaques, unlike the smooth skin surface seen here.

Alopecia areata (choice “b”), common in children, typically entails complete hair loss in a given area—or, as hair regrows, with hairs of equal length. The uneven hairs seen in trichotillomania help a great deal in distinguishing it from alopecia areata.

Traction alopecia (choice “d”) is focal hair loss caused by chronic tension related to hairstyling. Most common in African-American women, and typically affecting the frontal periphery of the scalp, it is an unlikely explanation for hair loss in a 10-year-old boy.

DISCUSSION

Trichotillomania (TT) means, literally, “hair-pulling madness.” But in reality, there’s little actual plucking of hairs in this common condition. Instead, patients habitually manipulate hair by twirling and tugging, which weakens the shafts and follicles and renders them more susceptible to everyday wear and tear. In some cases, individual hairs speed through their growth phases and others break off in mid-shaft. All of this contributes to the classic “uneven” look of TT.

Patients with TT tend to be in the 4-to-17 age range, and most have issues with unresolved anxiety that manifest in part with manipulation of the hair. Officially considered an impulse control disorder, TT in most cases belongs to the psychiatrist’s domain.

In this case, it was enormously helpful to have corroboration from the patient and his mother regarding his role in creating and perpetuating the problem. Had that not been the case—or in the event of other doubts as to the correct diagnosis—biopsy could have been performed to rule out most of the other items in the differential, particularly alopecia areata.

Interestingly enough, studies have shown that the more sharply defined the area of hair loss, the more likely the patient is to admit his/her role in its creation. However, as is often the case with scientific research, contradictory findings have also been made.

TREATMENT

Treatment of TT is problematic, since no medications have proven to be completely helpful. Psychiatrists use a combination of medication, cognitive behavioral therapy, and other behavior modifications that are designed to overcome the habitual component of the problem. Most cases of TT resolve on their own, but in severe cases that persist for years, permanent hair loss can result.

In this case, there was enough insight and motivation on the part of the patient and his family to stop the offending behavior and allow the hair to regrow.

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A 10-year-old boy is referred to dermatology with a four-month history of hair loss. The affected area of the vertex is now large enough to alarm his mother, who accompanies him to his appointment. The child’s primary care provider had diagnosed alopecia areata and prescribed triamcinolone 0.1% solution. But after a month of twice-daily application, even more hair has been lost. There is no family history of alopecia areata or other autoimmune disease. The child is otherwise healthy, although he is being treated by a psychiatrist for attention deficit disorder and chronic anxiety (with two medications whose names are unknown). The patient denies any symptoms associated with his hair loss, and his mother denies any skin changes in the affected area. However, she emphasizes that she has seen her son manipulating the area with his hand on several occasions, despite her attempts to make him stop. When pressed, the patient finally admits that throughout the day he twirls and tugs on his hair—although he denies actually pulling out any. On inspection, an 11 x 8–cm oval area of distinct and sharply demarcated hair loss is noted in the vertex scalp. Hairs of different lengths are noted in the central portion of the site; some have obviously been broken off, while others are longer, with thin, tapering ends. There is no disruption (eg, scaling, redness, edema) in the surface of the scalp, but the whole area is darker (brown) than the surrounding, uninvolved scalp. No other areas of hair loss are noted in the scalp or face. No nodes are palpable in the neck.

 

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