Community‐associated methicillin‐resistant Staphylococcus aureus (MRSA) infection is an evolving disease that is changing medical practice. MRSA has become the most frequent cause of skin and soft‐tissue infections presenting to most emergency departments in the United States.1 In comparison with methicillin‐sensitive S. aureus, community‐associated MRSA is more likely to present as soft‐tissue abscesses or necrotizing pneumonia.2 In 2005 alone, 94,360 invasive MRSA infections were estimated to have occurred in the United States, most of which were associated with MRSA bacteremia.3 In the hospital, MRSA infections are associated with greater lengths of stay, higher mortality, and increased costs.3

We report a patient with persistent MRSA bacteremia due to a prostatic abscess. Prostatitis or prostatic abscess with MRSA has rarely been reported. Resolution of the bacteremia was achieved only after drainage of the abscess. This case highlights the importance of recognizing this clinical condition and draining any MRSA‐associated abscesses. In addition, the abscess‐forming characteristics of MRSA may suggest that the incidence of prostatic abscess due to this microbe is on the rise.

CASE REPORT

A 40‐year‐old human immunodeficiency viruspositive man presented with a 10‐day history of intermittent fever, urinary hesitancy, weak urinary stream, and intermittent abdominal pain relieved following urination. He denied dysuria, hematuria, chest pain, dyspnea, nausea, weight loss, diarrhea, or decreased functional status. His last CD4 count was 528/L on highly active antiretroviral therapy 1 year prior to presentation; however, he had run out of medications several months prior to presentation. His medical history was also significant for incision and drainage of skin abscesses with unknown microbiology several months prior to presentation. He currently used tobacco but denied illicit drug use. He was sexually abstinent for over a year prior to presentation but had a history of having unprotected sex with men.

On physical examination, his vital signs were as follows: temperature, 37.8C; blood pressure, 133/84 mm Hg; heart rate, 107 beats/minute; respiration rate, 16 breaths/minute; and oxygen saturation, 100% on room air. He was under no distress. His heart sound was tachycardic and regular with no murmur noted. Lung sounds were clear. Abdominal examination revealed no tenderness or organomegaly. His prostate was boggy, minimally tender, and slightly enlarged. The rest of his physical examination was normal. The white blood cell count was 7.5 10⁹/L with 79% neutrophils. The serum chemistry was normal. The prostate‐specific antigen level was 2.9 ng/mL. A repeat CD4 count was 140/L. Urinalysis revealed large leukocyte esterase, no nitrites, and 60 white blood cells per high‐power field. He was diagnosed with prostatitis and discharged on levofloxacin.

The subsequent day, he returned to the emergency department with an inability to void. A Foley catheter was placed with resolution of his symptoms. Later that day, blood cultures from his initial admission grew MRSA in 2 out of 4 bottles, and he was admitted to the hospital. A review of the prior urine culture showed no growth. Computed tomography (CT) of the abdomen and pelvis showed an enlarged prostate with multiple noncommunicating peripherally enhancing hypodensities consistent with prostatic abscesses (arrows in Figure 1). These abscesses were associated with periprostatic fat stranding, edematous seminal vesicles, diffuse urinary bladder wall thickening, and mild inguinal adenopathy. Therapy with intravenous vancomycin was initiated.

Figure 1

Over the next 6 days, the patient continued to have intermittent fevers. Blood cultures continued to grow MRSA. Gentamicin was added for possible synergy on hospital day 3 without improvement. A transesophageal echocardiogram was normal. On hospital day 6, repeat CT showed no change in the size of the prostatic abscesses but an increased capsular bulge along the right mid gland. The urology service was consulted. They performed bedside transperineal drainage of the largest abscess with transrectal ultrasound guidance. No indwelling drain was placed. A culture of the purulent drainage grew MRSA. Three days after the surgical drainage, the patient was afebrile, urinary symptoms had resolved, and serial blood cultures remained negative. He was discharged on hospital day 13 to complete a 4‐week course of intravenous vancomycin. The patient missed an appointment for follow‐up imaging.

DISCUSSION

We report a case of community‐associated MRSA bacteremia secondary to a prostatic abscess, as confirmed by cultures from serum and of the abscess. S. aureus bacteremia often stems from infections of the respiratory tract, skin, and soft tissues, endocarditis, or infections of indwelling devices.4S. aureus can then create embolic foci, including in the prostate, which can serve as sources of persistent bacteremia. However, new evidence suggests community‐associated MRSA might be sexually transmitted among men who have sex with men.5 An MRSA prostatic abscess could then potentially be related to an ascending urinary tract infection or translocation from the gastrointestinal tract.

The vast majority of prostatitis cases prostatic abscesses are caused by Escherichia coli and other gram‐negative bacilli.6 Staphylococcus species are less common, and MRSA isolates have been described as a rare etiologic agent. Only four other case reports describing MRSA bacteremia associated with prostatitis or prostatic abscesses have been published.710 Both our patient and the three other case reports in the literature with prostatic abscesses and MRSA bacteremia required drainage of the abscess as well as antibiotics for resolution. The other reported cases involved drainage by transurethral resection of the prostate,79 whereas our case used transperineal drainage of the prostatic abscess via transrectal ultrasound guidance. In addition to intravenous antibiotics, drainage appears to be a key therapeutic measure for resolution of MRSA prostatic abscesses.

With the increasing incidence of community‐associated and healthcare‐associated MRSA infections, the incidence of prostatitis or prostatic abscesses secondary to MRSA may be increasing. MRSA seems to have a specific predilection for abscess formation in skin and soft‐tissue infections and pneumonia.2 Clinicians must be alert to a potentially higher frequency of MRSA as a cause of prostatic abscesses and prostatitis.

In the evaluation of a patient with persistent MRSA bacteremia, the potential for the prostate as a source of infection should be considered. Urinary symptoms may be subtle. Clinicians should have a low threshold for imaging studies such as CT to evaluate for a possible source of MRSA bacteremia. If a prostatic abscess is found, prompt surgical drainage or debridement is necessary for cure.

Community‐associated methicillin‐resistant Staphylococcus aureus (MRSA) infection is an evolving disease that is changing medical practice. MRSA has become the most frequent cause of skin and soft‐tissue infections presenting to most emergency departments in the United States.1 In comparison with methicillin‐sensitive S. aureus, community‐associated MRSA is more likely to present as soft‐tissue abscesses or necrotizing pneumonia.2 In 2005 alone, 94,360 invasive MRSA infections were estimated to have occurred in the United States, most of which were associated with MRSA bacteremia.3 In the hospital, MRSA infections are associated with greater lengths of stay, higher mortality, and increased costs.3

We report a patient with persistent MRSA bacteremia due to a prostatic abscess. Prostatitis or prostatic abscess with MRSA has rarely been reported. Resolution of the bacteremia was achieved only after drainage of the abscess. This case highlights the importance of recognizing this clinical condition and draining any MRSA‐associated abscesses. In addition, the abscess‐forming characteristics of MRSA may suggest that the incidence of prostatic abscess due to this microbe is on the rise.

CASE REPORT

A 40‐year‐old human immunodeficiency viruspositive man presented with a 10‐day history of intermittent fever, urinary hesitancy, weak urinary stream, and intermittent abdominal pain relieved following urination. He denied dysuria, hematuria, chest pain, dyspnea, nausea, weight loss, diarrhea, or decreased functional status. His last CD4 count was 528/L on highly active antiretroviral therapy 1 year prior to presentation; however, he had run out of medications several months prior to presentation. His medical history was also significant for incision and drainage of skin abscesses with unknown microbiology several months prior to presentation. He currently used tobacco but denied illicit drug use. He was sexually abstinent for over a year prior to presentation but had a history of having unprotected sex with men.

On physical examination, his vital signs were as follows: temperature, 37.8C; blood pressure, 133/84 mm Hg; heart rate, 107 beats/minute; respiration rate, 16 breaths/minute; and oxygen saturation, 100% on room air. He was under no distress. His heart sound was tachycardic and regular with no murmur noted. Lung sounds were clear. Abdominal examination revealed no tenderness or organomegaly. His prostate was boggy, minimally tender, and slightly enlarged. The rest of his physical examination was normal. The white blood cell count was 7.5 10⁹/L with 79% neutrophils. The serum chemistry was normal. The prostate‐specific antigen level was 2.9 ng/mL. A repeat CD4 count was 140/L. Urinalysis revealed large leukocyte esterase, no nitrites, and 60 white blood cells per high‐power field. He was diagnosed with prostatitis and discharged on levofloxacin.

The subsequent day, he returned to the emergency department with an inability to void. A Foley catheter was placed with resolution of his symptoms. Later that day, blood cultures from his initial admission grew MRSA in 2 out of 4 bottles, and he was admitted to the hospital. A review of the prior urine culture showed no growth. Computed tomography (CT) of the abdomen and pelvis showed an enlarged prostate with multiple noncommunicating peripherally enhancing hypodensities consistent with prostatic abscesses (arrows in Figure 1). These abscesses were associated with periprostatic fat stranding, edematous seminal vesicles, diffuse urinary bladder wall thickening, and mild inguinal adenopathy. Therapy with intravenous vancomycin was initiated.

Figure 1

Over the next 6 days, the patient continued to have intermittent fevers. Blood cultures continued to grow MRSA. Gentamicin was added for possible synergy on hospital day 3 without improvement. A transesophageal echocardiogram was normal. On hospital day 6, repeat CT showed no change in the size of the prostatic abscesses but an increased capsular bulge along the right mid gland. The urology service was consulted. They performed bedside transperineal drainage of the largest abscess with transrectal ultrasound guidance. No indwelling drain was placed. A culture of the purulent drainage grew MRSA. Three days after the surgical drainage, the patient was afebrile, urinary symptoms had resolved, and serial blood cultures remained negative. He was discharged on hospital day 13 to complete a 4‐week course of intravenous vancomycin. The patient missed an appointment for follow‐up imaging.

DISCUSSION

We report a case of community‐associated MRSA bacteremia secondary to a prostatic abscess, as confirmed by cultures from serum and of the abscess. S. aureus bacteremia often stems from infections of the respiratory tract, skin, and soft tissues, endocarditis, or infections of indwelling devices.4S. aureus can then create embolic foci, including in the prostate, which can serve as sources of persistent bacteremia. However, new evidence suggests community‐associated MRSA might be sexually transmitted among men who have sex with men.5 An MRSA prostatic abscess could then potentially be related to an ascending urinary tract infection or translocation from the gastrointestinal tract.

The vast majority of prostatitis cases prostatic abscesses are caused by Escherichia coli and other gram‐negative bacilli.6 Staphylococcus species are less common, and MRSA isolates have been described as a rare etiologic agent. Only four other case reports describing MRSA bacteremia associated with prostatitis or prostatic abscesses have been published.710 Both our patient and the three other case reports in the literature with prostatic abscesses and MRSA bacteremia required drainage of the abscess as well as antibiotics for resolution. The other reported cases involved drainage by transurethral resection of the prostate,79 whereas our case used transperineal drainage of the prostatic abscess via transrectal ultrasound guidance. In addition to intravenous antibiotics, drainage appears to be a key therapeutic measure for resolution of MRSA prostatic abscesses.

With the increasing incidence of community‐associated and healthcare‐associated MRSA infections, the incidence of prostatitis or prostatic abscesses secondary to MRSA may be increasing. MRSA seems to have a specific predilection for abscess formation in skin and soft‐tissue infections and pneumonia.2 Clinicians must be alert to a potentially higher frequency of MRSA as a cause of prostatic abscesses and prostatitis.

In the evaluation of a patient with persistent MRSA bacteremia, the potential for the prostate as a source of infection should be considered. Urinary symptoms may be subtle. Clinicians should have a low threshold for imaging studies such as CT to evaluate for a possible source of MRSA bacteremia. If a prostatic abscess is found, prompt surgical drainage or debridement is necessary for cure.

Community‐associated methicillin‐resistant Staphylococcus aureus (MRSA) infection is an evolving disease that is changing medical practice. MRSA has become the most frequent cause of skin and soft‐tissue infections presenting to most emergency departments in the United States.1 In comparison with methicillin‐sensitive S. aureus, community‐associated MRSA is more likely to present as soft‐tissue abscesses or necrotizing pneumonia.2 In 2005 alone, 94,360 invasive MRSA infections were estimated to have occurred in the United States, most of which were associated with MRSA bacteremia.3 In the hospital, MRSA infections are associated with greater lengths of stay, higher mortality, and increased costs.3

We report a patient with persistent MRSA bacteremia due to a prostatic abscess. Prostatitis or prostatic abscess with MRSA has rarely been reported. Resolution of the bacteremia was achieved only after drainage of the abscess. This case highlights the importance of recognizing this clinical condition and draining any MRSA‐associated abscesses. In addition, the abscess‐forming characteristics of MRSA may suggest that the incidence of prostatic abscess due to this microbe is on the rise.

CASE REPORT

A 40‐year‐old human immunodeficiency viruspositive man presented with a 10‐day history of intermittent fever, urinary hesitancy, weak urinary stream, and intermittent abdominal pain relieved following urination. He denied dysuria, hematuria, chest pain, dyspnea, nausea, weight loss, diarrhea, or decreased functional status. His last CD4 count was 528/L on highly active antiretroviral therapy 1 year prior to presentation; however, he had run out of medications several months prior to presentation. His medical history was also significant for incision and drainage of skin abscesses with unknown microbiology several months prior to presentation. He currently used tobacco but denied illicit drug use. He was sexually abstinent for over a year prior to presentation but had a history of having unprotected sex with men.

On physical examination, his vital signs were as follows: temperature, 37.8C; blood pressure, 133/84 mm Hg; heart rate, 107 beats/minute; respiration rate, 16 breaths/minute; and oxygen saturation, 100% on room air. He was under no distress. His heart sound was tachycardic and regular with no murmur noted. Lung sounds were clear. Abdominal examination revealed no tenderness or organomegaly. His prostate was boggy, minimally tender, and slightly enlarged. The rest of his physical examination was normal. The white blood cell count was 7.5 10⁹/L with 79% neutrophils. The serum chemistry was normal. The prostate‐specific antigen level was 2.9 ng/mL. A repeat CD4 count was 140/L. Urinalysis revealed large leukocyte esterase, no nitrites, and 60 white blood cells per high‐power field. He was diagnosed with prostatitis and discharged on levofloxacin.

The subsequent day, he returned to the emergency department with an inability to void. A Foley catheter was placed with resolution of his symptoms. Later that day, blood cultures from his initial admission grew MRSA in 2 out of 4 bottles, and he was admitted to the hospital. A review of the prior urine culture showed no growth. Computed tomography (CT) of the abdomen and pelvis showed an enlarged prostate with multiple noncommunicating peripherally enhancing hypodensities consistent with prostatic abscesses (arrows in Figure 1). These abscesses were associated with periprostatic fat stranding, edematous seminal vesicles, diffuse urinary bladder wall thickening, and mild inguinal adenopathy. Therapy with intravenous vancomycin was initiated.

Figure 1

Over the next 6 days, the patient continued to have intermittent fevers. Blood cultures continued to grow MRSA. Gentamicin was added for possible synergy on hospital day 3 without improvement. A transesophageal echocardiogram was normal. On hospital day 6, repeat CT showed no change in the size of the prostatic abscesses but an increased capsular bulge along the right mid gland. The urology service was consulted. They performed bedside transperineal drainage of the largest abscess with transrectal ultrasound guidance. No indwelling drain was placed. A culture of the purulent drainage grew MRSA. Three days after the surgical drainage, the patient was afebrile, urinary symptoms had resolved, and serial blood cultures remained negative. He was discharged on hospital day 13 to complete a 4‐week course of intravenous vancomycin. The patient missed an appointment for follow‐up imaging.

DISCUSSION

We report a case of community‐associated MRSA bacteremia secondary to a prostatic abscess, as confirmed by cultures from serum and of the abscess. S. aureus bacteremia often stems from infections of the respiratory tract, skin, and soft tissues, endocarditis, or infections of indwelling devices.4S. aureus can then create embolic foci, including in the prostate, which can serve as sources of persistent bacteremia. However, new evidence suggests community‐associated MRSA might be sexually transmitted among men who have sex with men.5 An MRSA prostatic abscess could then potentially be related to an ascending urinary tract infection or translocation from the gastrointestinal tract.

The vast majority of prostatitis cases prostatic abscesses are caused by Escherichia coli and other gram‐negative bacilli.6 Staphylococcus species are less common, and MRSA isolates have been described as a rare etiologic agent. Only four other case reports describing MRSA bacteremia associated with prostatitis or prostatic abscesses have been published.710 Both our patient and the three other case reports in the literature with prostatic abscesses and MRSA bacteremia required drainage of the abscess as well as antibiotics for resolution. The other reported cases involved drainage by transurethral resection of the prostate,79 whereas our case used transperineal drainage of the prostatic abscess via transrectal ultrasound guidance. In addition to intravenous antibiotics, drainage appears to be a key therapeutic measure for resolution of MRSA prostatic abscesses.

With the increasing incidence of community‐associated and healthcare‐associated MRSA infections, the incidence of prostatitis or prostatic abscesses secondary to MRSA may be increasing. MRSA seems to have a specific predilection for abscess formation in skin and soft‐tissue infections and pneumonia.2 Clinicians must be alert to a potentially higher frequency of MRSA as a cause of prostatic abscesses and prostatitis.

In the evaluation of a patient with persistent MRSA bacteremia, the potential for the prostate as a source of infection should be considered. Urinary symptoms may be subtle. Clinicians should have a low threshold for imaging studies such as CT to evaluate for a possible source of MRSA bacteremia. If a prostatic abscess is found, prompt surgical drainage or debridement is necessary for cure.

A 38‐year‐old woman with juvenile dermatomyositis (JDM) and calcinosis universalis presented with 3 days of drainage from a lesion on her right elbow. An examination of the elbow revealed diffuse and firm subcutaneous nodules with overlying erythema. X‐rays illustrated soft‐tissue calcifications in the forearm and elbow without evidence of osteomyelitis (Figure 1). Wound cultures grew Staphylococcus aureus, and the patient was started on intravenous antibiotics for abscess treatment.

Figure 1

Calcinosis universalis is soft‐tissue calcification presenting as a complication of JDM. It is often detected in childhood in 30% to 70% of patients. It is hypothesized that calcinosis is due to chronic tissue inflammation, as seen in JDM, leading to muscle damage, releasing calcium, and inducing mineralization. Calcinosis universalis often presents as calcified nodules and plaques in areas of repeated trauma, such as joints, extremities, and buttocks (Figures 13). Calcification is localized in subcutaneous tissue, fascial planes, tendons, or intramuscular areas. It can cause debilitating secondary complications such as skin ulcerations expressing calcified material, superimposed infections of skin lesions, joint contractures with severe arthralgias, and muscle atrophy. Calcinosis has been correlated with severity of JDM with presence of cardiac involvement and use of more than one immunosuppression medication.1 It has also been associated with the degree of vasculopathy and delay in initiation of therapy for controlling inflammation in JDM.2

Soft‐tissue calcification can be classified into 5 categories:

• 1

  Dystrophic calcification occurs in injured tissues with normal calcium, phosphorus, and parathyroid hormone levels, as seen in this patient. Calcified nodules or plaques occur in the extremities and buttocks. This is most often seen in JDM, scleroderma, and systemic lupus erythematosus.

• 2

  Metastatic calcification affects normal tissues with abnormal levels of calcium and phosphorus. It is seen in large joints as well as arteries and visceral organs. It is associated with hyperparathyroidism, hypervitaminosis D, and malignancies.

• 3

  Calciphylaxis with abnormal calcium and phosphorus metabolism causes small‐vessel calcification in patients with chronic renal failure.

• 4

  Tumoral calcification is a familial condition with normal calcium levels but elevated phosphorus levels. Large subcutaneous calcifications are seen near high‐pressure areas and joints.

• 5

  Idiopathic calcification is seen in healthy children and young adults with normal calcium metabolism and appears as multiple subcutaneous calcifications.2

Figure 2

Figure 3

Although multiple therapeutic options have been tried for the management or prevention of calcinosis, there is currently no accepted standard of treatment. In patients with calcinosis, warfarin, probenecid, colchicine, bisphosphonates, minocycline, diltiazem, aluminum hydroxide, corticosteroids, and salicylate have been attempted with variable results. Other therapeutic options include carbon dioxide laser treatments and surgical excision of large plaques. Decreasing muscle inflammation with aggressive treatment of JDM may improve outcomes and decrease the incidence of calcification.3 Unfortunately, once calcinosis has occurred, it is highly refractory to medical therapy.

Calcinosis universalis can lead to severe functional impairment. It can be distinguished from other types of calcinosis by diffuse involvement of muscle and fascia in connective tissue disease with normal calcium and phosphorus levels. New management modalities such as cyclosporine, intravenous immunoglobulin, and tumor necrosis factor alpha inhibitors are currently being evaluated.

A 38‐year‐old woman with juvenile dermatomyositis (JDM) and calcinosis universalis presented with 3 days of drainage from a lesion on her right elbow. An examination of the elbow revealed diffuse and firm subcutaneous nodules with overlying erythema. X‐rays illustrated soft‐tissue calcifications in the forearm and elbow without evidence of osteomyelitis (Figure 1). Wound cultures grew Staphylococcus aureus, and the patient was started on intravenous antibiotics for abscess treatment.

Figure 1

Calcinosis universalis is soft‐tissue calcification presenting as a complication of JDM. It is often detected in childhood in 30% to 70% of patients. It is hypothesized that calcinosis is due to chronic tissue inflammation, as seen in JDM, leading to muscle damage, releasing calcium, and inducing mineralization. Calcinosis universalis often presents as calcified nodules and plaques in areas of repeated trauma, such as joints, extremities, and buttocks (Figures 13). Calcification is localized in subcutaneous tissue, fascial planes, tendons, or intramuscular areas. It can cause debilitating secondary complications such as skin ulcerations expressing calcified material, superimposed infections of skin lesions, joint contractures with severe arthralgias, and muscle atrophy. Calcinosis has been correlated with severity of JDM with presence of cardiac involvement and use of more than one immunosuppression medication.1 It has also been associated with the degree of vasculopathy and delay in initiation of therapy for controlling inflammation in JDM.2

Soft‐tissue calcification can be classified into 5 categories:

• 1

  Dystrophic calcification occurs in injured tissues with normal calcium, phosphorus, and parathyroid hormone levels, as seen in this patient. Calcified nodules or plaques occur in the extremities and buttocks. This is most often seen in JDM, scleroderma, and systemic lupus erythematosus.

• 2

  Metastatic calcification affects normal tissues with abnormal levels of calcium and phosphorus. It is seen in large joints as well as arteries and visceral organs. It is associated with hyperparathyroidism, hypervitaminosis D, and malignancies.

• 3

  Calciphylaxis with abnormal calcium and phosphorus metabolism causes small‐vessel calcification in patients with chronic renal failure.

• 4

  Tumoral calcification is a familial condition with normal calcium levels but elevated phosphorus levels. Large subcutaneous calcifications are seen near high‐pressure areas and joints.

• 5

  Idiopathic calcification is seen in healthy children and young adults with normal calcium metabolism and appears as multiple subcutaneous calcifications.2

Figure 2

Figure 3

Although multiple therapeutic options have been tried for the management or prevention of calcinosis, there is currently no accepted standard of treatment. In patients with calcinosis, warfarin, probenecid, colchicine, bisphosphonates, minocycline, diltiazem, aluminum hydroxide, corticosteroids, and salicylate have been attempted with variable results. Other therapeutic options include carbon dioxide laser treatments and surgical excision of large plaques. Decreasing muscle inflammation with aggressive treatment of JDM may improve outcomes and decrease the incidence of calcification.3 Unfortunately, once calcinosis has occurred, it is highly refractory to medical therapy.

Calcinosis universalis can lead to severe functional impairment. It can be distinguished from other types of calcinosis by diffuse involvement of muscle and fascia in connective tissue disease with normal calcium and phosphorus levels. New management modalities such as cyclosporine, intravenous immunoglobulin, and tumor necrosis factor alpha inhibitors are currently being evaluated.

A 38‐year‐old woman with juvenile dermatomyositis (JDM) and calcinosis universalis presented with 3 days of drainage from a lesion on her right elbow. An examination of the elbow revealed diffuse and firm subcutaneous nodules with overlying erythema. X‐rays illustrated soft‐tissue calcifications in the forearm and elbow without evidence of osteomyelitis (Figure 1). Wound cultures grew Staphylococcus aureus, and the patient was started on intravenous antibiotics for abscess treatment.

Figure 1

Calcinosis universalis is soft‐tissue calcification presenting as a complication of JDM. It is often detected in childhood in 30% to 70% of patients. It is hypothesized that calcinosis is due to chronic tissue inflammation, as seen in JDM, leading to muscle damage, releasing calcium, and inducing mineralization. Calcinosis universalis often presents as calcified nodules and plaques in areas of repeated trauma, such as joints, extremities, and buttocks (Figures 13). Calcification is localized in subcutaneous tissue, fascial planes, tendons, or intramuscular areas. It can cause debilitating secondary complications such as skin ulcerations expressing calcified material, superimposed infections of skin lesions, joint contractures with severe arthralgias, and muscle atrophy. Calcinosis has been correlated with severity of JDM with presence of cardiac involvement and use of more than one immunosuppression medication.1 It has also been associated with the degree of vasculopathy and delay in initiation of therapy for controlling inflammation in JDM.2

Soft‐tissue calcification can be classified into 5 categories:

• 1

  Dystrophic calcification occurs in injured tissues with normal calcium, phosphorus, and parathyroid hormone levels, as seen in this patient. Calcified nodules or plaques occur in the extremities and buttocks. This is most often seen in JDM, scleroderma, and systemic lupus erythematosus.

• 2

  Metastatic calcification affects normal tissues with abnormal levels of calcium and phosphorus. It is seen in large joints as well as arteries and visceral organs. It is associated with hyperparathyroidism, hypervitaminosis D, and malignancies.

• 3

  Calciphylaxis with abnormal calcium and phosphorus metabolism causes small‐vessel calcification in patients with chronic renal failure.

• 4

  Tumoral calcification is a familial condition with normal calcium levels but elevated phosphorus levels. Large subcutaneous calcifications are seen near high‐pressure areas and joints.

• 5

  Idiopathic calcification is seen in healthy children and young adults with normal calcium metabolism and appears as multiple subcutaneous calcifications.2

Figure 2

Figure 3

Although multiple therapeutic options have been tried for the management or prevention of calcinosis, there is currently no accepted standard of treatment. In patients with calcinosis, warfarin, probenecid, colchicine, bisphosphonates, minocycline, diltiazem, aluminum hydroxide, corticosteroids, and salicylate have been attempted with variable results. Other therapeutic options include carbon dioxide laser treatments and surgical excision of large plaques. Decreasing muscle inflammation with aggressive treatment of JDM may improve outcomes and decrease the incidence of calcification.3 Unfortunately, once calcinosis has occurred, it is highly refractory to medical therapy.

Calcinosis universalis can lead to severe functional impairment. It can be distinguished from other types of calcinosis by diffuse involvement of muscle and fascia in connective tissue disease with normal calcium and phosphorus levels. New management modalities such as cyclosporine, intravenous immunoglobulin, and tumor necrosis factor alpha inhibitors are currently being evaluated.

Hyperglycemia and insulin resistance are common occurrences in critically ill patients, even those without a past medical history of diabetes.1, 2 This hyperglycemic state is associated with adverse outcomes, including severe infections, polyneuropathy, multiple‐organ failure, and death.3 Several studies have shown benefit in keeping patients' blood glucose (BG) tightly controlled.37 In a randomized controlled study, strict BG control (80‐110 mg/dL) with an insulin drip significantly reduced morbidity and mortality in critically ill patients.3 A recent meta‐analysis concluded that avoiding BG levels >150 mg/dL appeared to be crucial to reducing mortality in a mixed medical and surgical intensive care unit (ICU) population.7

The Diabetes Mellitus Insulin‐Glucose Infusion in Acute Myocardial Infarction study addressed the issue of tight glycemic control both acutely and chronically in 620 diabetic patients postmyocardial infarction. Patients were randomized to tight glycemic control (126‐180 mg/dL) followed by a transition to maintenance insulin or to standard care. This intervention demonstrated a sustained mortality reduction of 7.5% at 1 year.8 In contrast, the CREATE‐ECLA study showed a neutral mortality benefit of a short‐term (24‐hour) insulin infusion in postmyocardial infarction patients.9 These data demonstrate the need for clinicians to consider insulin requirements throughout the hospital stay and after discharge. To date, there are no published studies evaluating glycemic control following discontinuation of an intensive insulin protocol (IIP). Therefore, the current study was conducted to compare BG control during the use of an IIP and for the 5 days following intensive insulin therapy.

METHODS

RESULTS

A total of 171 patients received the IIP during the study period. Ninety‐seven patients did not meet inclusion criteria because they received the IIP for less than 24 hours. Of the 74 patients meeting inclusion criteria, 9 were excluded (5 had insufficient glucose data, 3 were cared for by an endocrinologist, and 1 died while receiving the IIP). Thus, 65 patients were included in the study.

Table 1 lists the baseline demographics for all patients and those with and without a history of diabetes mellitus (DM). The majority of the patients (n = 49) underwent a surgical procedure, with the most common procedure being coronary artery bypass graft (n = 38). Patients undergoing coronary artery bypass graft had the IIP included in their standard postoperative order set. The majority of patients were considered stable during the 12 hours prior to discontinuation of the IIP, including 23 patients with a history of DM. Of the 65 patients who were included in the study, 25 (38.5%) received a scheduled insulin order following discontinuation of the IIP, whereas 38 (58.5%) received some form of sliding‐scale insulin (SSI). Additionally, 2 (3%) patients did not receive any form of insulin order after stopping the IIP. Of those receiving scheduled insulin, 15 (60%) received neutral protamine Hagedorn, 5 (20%) received glargine, 5 (20%) received 70/30, and 1 (4%) received regular insulin. Of those receiving SSI only, the prescribed frequency was as follows: every 4 hours for 17 (45%), before meals and at bedtime for 15 (39%), every 6 hours for 5 (13%), and every 2 hours for 1 (3%).

A total of 562 glucose measurements were collected during the last 12 hours on the IIP, whereas 201 were collected during the first 12 hours immediately following the IIP. Patients demonstrated a significant increase in BG (mean standard deviation) during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP (168 50 mg/dL versus 123 26 mg/dL, P < 0.001). This corresponded to a significant decrease in the median (interquartile range) insulin administered during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP [8 (0‐18) units versus 40 (22‐65) units, P < 0.001; Figure 1]. A total of 1914 BG measurements were collected during the follow‐up period. Figure 2 shows mean BG values for all patients on the IIP compared to mean BG values for each day of the follow‐up period. There was a significant increase in mean BG measurements when the IIP was compared to each day of the follow‐up period, but there was no difference between days of the follow‐up period. Table 2 shows the proportion of patients experiencing at least 1 episode of hyperglycemia (BG > 150 mg/dL), significant hyperglycemia (BG > 200 mg/dL), severe hyperglycemia (BG > 300 mg/dL), or hypoglycemia (BG < 60 mg/dL) while receiving the IIP and during the follow‐up period. When comparing the IIP to the follow‐up period, we found a significant increase in the proportion of patients with at least 1 BG > 150 mg/dL. This was also true for patients with a BG of > 200 mg/dL.

Figure 1

Figure 2

The only independent predictor of a greater than 30% change in mean BG was the requirement for more than 20 units of insulin (>1.7 units/hour) during the last 12 hours on the IIP. The odds of a greater than 30% change was 4.62 times higher (95% confidence interval: 1.1718.17) in patients requiring more than 20 units during the last 12 hours on IIP after adjustments for stability on the protocol and past medical history of diabetes. Stability on the protocol was not identified as an independent predictor, with an adjusted odds ratio of 2.40 (95% confidence interval: 0.797.32).

DISCUSSION

This is the first study to describe glycemic control following the transition from an IIP to subcutaneous insulin. We observed that during the 5 days following discontinuation of an IIP, patients had significantly elevated mean BG values. These data are highlighted by the fact that patients received significantly less insulin during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP. Additionally, a larger than expected proportion of patients exhibited at least 1 episode of hyperglycemia during the follow‐up period. We also found that an increased insulin requirement of >1.7 units/hour during the last 12 hours of the IIP was an independent risk factor for a greater than 30% increase in mean BG on day 1 of the follow‐up period.

Increasing evidence demonstrates that the development of hyperglycemia in the hospital setting is a marker of poor clinical outcome and mortality. In fact, hyperglycemia has been associated with prolonged hospital stay, infection, disability after discharge, and death in patients on general surgical and medical wards.1012 This makes the increase in mean BG found in our study following discontinuation of the IIP a concern.

SSI with subcutaneous short‐acting insulin has been used for inpatients as the standard of care for many years. However, evidence supporting the effectiveness of SSI alone is lacking, and it is not recommended by the American Diabetes Association.13 Queale et al.14 showed that SSI regimens when used alone were associated with suboptimal glycemic control and a 3‐fold higher risk of hyperglycemic episodes.1 Two retrospective studies have also demonstrated that SSI is less effective and widely variable in comparison with proactive preventative therapy.15, 16 In the current study, 58.5% of patients received SSI alone during the follow‐up period. As indicated in Figure 1, there was a significant increase in mean BG during this time interval. The choice of an inappropriate insulin regimen might be a contributing factor to poor glycemic control.

Because only 38.5% of patients were transitioned to scheduled insulin in our study, one possible strategy to help improve glycemic control would be to transition patients to a scheduled insulin regimen. Umpierrez et al.12 conducted a prospective, multicenter randomized trial to compare the efficacy and safety of a basal‐bolus insulin regimen with that of SSI in hospitalized type 2 diabetics. These authors found that patients treated with insulin glargine and glulisine had greater improvement in glycemic control than those treated with SSI (P < 0.01).12 Interestingly, the basal‐bolus method provides a maintenance insulin regimen that is aggressively titrated upward as well as an adjustable SSI based on insulin sensitivity. Patients in the current study may have benefited from a similar approach as many did not have their scheduled insulin adjusted despite persistent hyperglycemia.

With the increasing evidence for tight glycemic control in the ICU, a standardized transition from an intensive insulin infusion to a subcutaneous basal‐bolus regimen or other scheduled regimen is needed. To date, the current study is the first to describe this transition. Based on these data, recommendations for transitioning patients off an IIP provided by Furnary and Braithwaite17 should be considered by clinicians. In fact, one of their proposed predictors for unsuccessful transition was an insulin requirement of 2 units/hour. Indeed, the only independent risk factor for poor glycemic control identified in the current study was a requirement of >20 units (>1.7 units/hour) during the last 12 hours of the IIP. Further research is required to verify the other predictors suggested by Furnary and Braithwaite. They recommended using a standardized conversion protocol to transition patients off an IIP.

More recently, Kitabchi et al.18 recommended that a BG target of less than 180 mg/dL be maintained for the hospitalized patient.18 Although our study showed a mean BG less than 180 mg/dL during the follow‐up period, the variability in these values raises concerns for individual patients.

The current study is limited by its size and retrospective nature. As with all retrospective studies, the inability to control the implementation and discontinuation of the IIP may confound the results. However, this study demonstrates a real world experience with an IIP and illustrates the difficulties with transitioning patients to a subcutaneous regimen. BG values and administered insulin were collected only for the last 12 hours on the IIP. This duration is considered appropriate as this time period is used clinically at MUH, and previous recommendations for transitioning patients suggest using a time period of 6 to 8 hours to guide the transition insulin regimen.17 In addition, data regarding the severity of illness and new onset of infections were not collected for patients in the study. Both could affect glucose control. All patients had to be in an ICU to receive the IIP, but their location during the follow‐up period varied. Although these data were not available, control of BG is a problem that should be addressed whether the patient is in the ICU or not. Another possible limitation of the study was the identification of patients with or without a past medical history of DM. The inability to identify new‐onset or previously undiagnosed DM may have affected analyses based on this variable.

CONCLUSIONS

This study demonstrated a significant increase in mean BG following discontinuation of an IIP; this corresponded to a significant decrease in the amount of insulin administered. This increase was sustained for a period of at least 5 days. Additionally, an independent risk factor for poor glycemic control immediately following discontinuation of an IIP was an insulin requirement of >1.7 units/hour during the previous 12 hours. Further study into transitioning off an IIP is warranted.

Hyperglycemia and insulin resistance are common occurrences in critically ill patients, even those without a past medical history of diabetes.1, 2 This hyperglycemic state is associated with adverse outcomes, including severe infections, polyneuropathy, multiple‐organ failure, and death.3 Several studies have shown benefit in keeping patients' blood glucose (BG) tightly controlled.37 In a randomized controlled study, strict BG control (80‐110 mg/dL) with an insulin drip significantly reduced morbidity and mortality in critically ill patients.3 A recent meta‐analysis concluded that avoiding BG levels >150 mg/dL appeared to be crucial to reducing mortality in a mixed medical and surgical intensive care unit (ICU) population.7

The Diabetes Mellitus Insulin‐Glucose Infusion in Acute Myocardial Infarction study addressed the issue of tight glycemic control both acutely and chronically in 620 diabetic patients postmyocardial infarction. Patients were randomized to tight glycemic control (126‐180 mg/dL) followed by a transition to maintenance insulin or to standard care. This intervention demonstrated a sustained mortality reduction of 7.5% at 1 year.8 In contrast, the CREATE‐ECLA study showed a neutral mortality benefit of a short‐term (24‐hour) insulin infusion in postmyocardial infarction patients.9 These data demonstrate the need for clinicians to consider insulin requirements throughout the hospital stay and after discharge. To date, there are no published studies evaluating glycemic control following discontinuation of an intensive insulin protocol (IIP). Therefore, the current study was conducted to compare BG control during the use of an IIP and for the 5 days following intensive insulin therapy.

METHODS

RESULTS

A total of 171 patients received the IIP during the study period. Ninety‐seven patients did not meet inclusion criteria because they received the IIP for less than 24 hours. Of the 74 patients meeting inclusion criteria, 9 were excluded (5 had insufficient glucose data, 3 were cared for by an endocrinologist, and 1 died while receiving the IIP). Thus, 65 patients were included in the study.

Table 1 lists the baseline demographics for all patients and those with and without a history of diabetes mellitus (DM). The majority of the patients (n = 49) underwent a surgical procedure, with the most common procedure being coronary artery bypass graft (n = 38). Patients undergoing coronary artery bypass graft had the IIP included in their standard postoperative order set. The majority of patients were considered stable during the 12 hours prior to discontinuation of the IIP, including 23 patients with a history of DM. Of the 65 patients who were included in the study, 25 (38.5%) received a scheduled insulin order following discontinuation of the IIP, whereas 38 (58.5%) received some form of sliding‐scale insulin (SSI). Additionally, 2 (3%) patients did not receive any form of insulin order after stopping the IIP. Of those receiving scheduled insulin, 15 (60%) received neutral protamine Hagedorn, 5 (20%) received glargine, 5 (20%) received 70/30, and 1 (4%) received regular insulin. Of those receiving SSI only, the prescribed frequency was as follows: every 4 hours for 17 (45%), before meals and at bedtime for 15 (39%), every 6 hours for 5 (13%), and every 2 hours for 1 (3%).

A total of 562 glucose measurements were collected during the last 12 hours on the IIP, whereas 201 were collected during the first 12 hours immediately following the IIP. Patients demonstrated a significant increase in BG (mean standard deviation) during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP (168 50 mg/dL versus 123 26 mg/dL, P < 0.001). This corresponded to a significant decrease in the median (interquartile range) insulin administered during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP [8 (0‐18) units versus 40 (22‐65) units, P < 0.001; Figure 1]. A total of 1914 BG measurements were collected during the follow‐up period. Figure 2 shows mean BG values for all patients on the IIP compared to mean BG values for each day of the follow‐up period. There was a significant increase in mean BG measurements when the IIP was compared to each day of the follow‐up period, but there was no difference between days of the follow‐up period. Table 2 shows the proportion of patients experiencing at least 1 episode of hyperglycemia (BG > 150 mg/dL), significant hyperglycemia (BG > 200 mg/dL), severe hyperglycemia (BG > 300 mg/dL), or hypoglycemia (BG < 60 mg/dL) while receiving the IIP and during the follow‐up period. When comparing the IIP to the follow‐up period, we found a significant increase in the proportion of patients with at least 1 BG > 150 mg/dL. This was also true for patients with a BG of > 200 mg/dL.

Figure 1

Figure 2

The only independent predictor of a greater than 30% change in mean BG was the requirement for more than 20 units of insulin (>1.7 units/hour) during the last 12 hours on the IIP. The odds of a greater than 30% change was 4.62 times higher (95% confidence interval: 1.1718.17) in patients requiring more than 20 units during the last 12 hours on IIP after adjustments for stability on the protocol and past medical history of diabetes. Stability on the protocol was not identified as an independent predictor, with an adjusted odds ratio of 2.40 (95% confidence interval: 0.797.32).

DISCUSSION

This is the first study to describe glycemic control following the transition from an IIP to subcutaneous insulin. We observed that during the 5 days following discontinuation of an IIP, patients had significantly elevated mean BG values. These data are highlighted by the fact that patients received significantly less insulin during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP. Additionally, a larger than expected proportion of patients exhibited at least 1 episode of hyperglycemia during the follow‐up period. We also found that an increased insulin requirement of >1.7 units/hour during the last 12 hours of the IIP was an independent risk factor for a greater than 30% increase in mean BG on day 1 of the follow‐up period.

Increasing evidence demonstrates that the development of hyperglycemia in the hospital setting is a marker of poor clinical outcome and mortality. In fact, hyperglycemia has been associated with prolonged hospital stay, infection, disability after discharge, and death in patients on general surgical and medical wards.1012 This makes the increase in mean BG found in our study following discontinuation of the IIP a concern.

SSI with subcutaneous short‐acting insulin has been used for inpatients as the standard of care for many years. However, evidence supporting the effectiveness of SSI alone is lacking, and it is not recommended by the American Diabetes Association.13 Queale et al.14 showed that SSI regimens when used alone were associated with suboptimal glycemic control and a 3‐fold higher risk of hyperglycemic episodes.1 Two retrospective studies have also demonstrated that SSI is less effective and widely variable in comparison with proactive preventative therapy.15, 16 In the current study, 58.5% of patients received SSI alone during the follow‐up period. As indicated in Figure 1, there was a significant increase in mean BG during this time interval. The choice of an inappropriate insulin regimen might be a contributing factor to poor glycemic control.

Because only 38.5% of patients were transitioned to scheduled insulin in our study, one possible strategy to help improve glycemic control would be to transition patients to a scheduled insulin regimen. Umpierrez et al.12 conducted a prospective, multicenter randomized trial to compare the efficacy and safety of a basal‐bolus insulin regimen with that of SSI in hospitalized type 2 diabetics. These authors found that patients treated with insulin glargine and glulisine had greater improvement in glycemic control than those treated with SSI (P < 0.01).12 Interestingly, the basal‐bolus method provides a maintenance insulin regimen that is aggressively titrated upward as well as an adjustable SSI based on insulin sensitivity. Patients in the current study may have benefited from a similar approach as many did not have their scheduled insulin adjusted despite persistent hyperglycemia.

With the increasing evidence for tight glycemic control in the ICU, a standardized transition from an intensive insulin infusion to a subcutaneous basal‐bolus regimen or other scheduled regimen is needed. To date, the current study is the first to describe this transition. Based on these data, recommendations for transitioning patients off an IIP provided by Furnary and Braithwaite17 should be considered by clinicians. In fact, one of their proposed predictors for unsuccessful transition was an insulin requirement of 2 units/hour. Indeed, the only independent risk factor for poor glycemic control identified in the current study was a requirement of >20 units (>1.7 units/hour) during the last 12 hours of the IIP. Further research is required to verify the other predictors suggested by Furnary and Braithwaite. They recommended using a standardized conversion protocol to transition patients off an IIP.

More recently, Kitabchi et al.18 recommended that a BG target of less than 180 mg/dL be maintained for the hospitalized patient.18 Although our study showed a mean BG less than 180 mg/dL during the follow‐up period, the variability in these values raises concerns for individual patients.

The current study is limited by its size and retrospective nature. As with all retrospective studies, the inability to control the implementation and discontinuation of the IIP may confound the results. However, this study demonstrates a real world experience with an IIP and illustrates the difficulties with transitioning patients to a subcutaneous regimen. BG values and administered insulin were collected only for the last 12 hours on the IIP. This duration is considered appropriate as this time period is used clinically at MUH, and previous recommendations for transitioning patients suggest using a time period of 6 to 8 hours to guide the transition insulin regimen.17 In addition, data regarding the severity of illness and new onset of infections were not collected for patients in the study. Both could affect glucose control. All patients had to be in an ICU to receive the IIP, but their location during the follow‐up period varied. Although these data were not available, control of BG is a problem that should be addressed whether the patient is in the ICU or not. Another possible limitation of the study was the identification of patients with or without a past medical history of DM. The inability to identify new‐onset or previously undiagnosed DM may have affected analyses based on this variable.

CONCLUSIONS

This study demonstrated a significant increase in mean BG following discontinuation of an IIP; this corresponded to a significant decrease in the amount of insulin administered. This increase was sustained for a period of at least 5 days. Additionally, an independent risk factor for poor glycemic control immediately following discontinuation of an IIP was an insulin requirement of >1.7 units/hour during the previous 12 hours. Further study into transitioning off an IIP is warranted.

Hyperglycemia and insulin resistance are common occurrences in critically ill patients, even those without a past medical history of diabetes.1, 2 This hyperglycemic state is associated with adverse outcomes, including severe infections, polyneuropathy, multiple‐organ failure, and death.3 Several studies have shown benefit in keeping patients' blood glucose (BG) tightly controlled.37 In a randomized controlled study, strict BG control (80‐110 mg/dL) with an insulin drip significantly reduced morbidity and mortality in critically ill patients.3 A recent meta‐analysis concluded that avoiding BG levels >150 mg/dL appeared to be crucial to reducing mortality in a mixed medical and surgical intensive care unit (ICU) population.7

The Diabetes Mellitus Insulin‐Glucose Infusion in Acute Myocardial Infarction study addressed the issue of tight glycemic control both acutely and chronically in 620 diabetic patients postmyocardial infarction. Patients were randomized to tight glycemic control (126‐180 mg/dL) followed by a transition to maintenance insulin or to standard care. This intervention demonstrated a sustained mortality reduction of 7.5% at 1 year.8 In contrast, the CREATE‐ECLA study showed a neutral mortality benefit of a short‐term (24‐hour) insulin infusion in postmyocardial infarction patients.9 These data demonstrate the need for clinicians to consider insulin requirements throughout the hospital stay and after discharge. To date, there are no published studies evaluating glycemic control following discontinuation of an intensive insulin protocol (IIP). Therefore, the current study was conducted to compare BG control during the use of an IIP and for the 5 days following intensive insulin therapy.

METHODS

RESULTS

A total of 171 patients received the IIP during the study period. Ninety‐seven patients did not meet inclusion criteria because they received the IIP for less than 24 hours. Of the 74 patients meeting inclusion criteria, 9 were excluded (5 had insufficient glucose data, 3 were cared for by an endocrinologist, and 1 died while receiving the IIP). Thus, 65 patients were included in the study.

Table 1 lists the baseline demographics for all patients and those with and without a history of diabetes mellitus (DM). The majority of the patients (n = 49) underwent a surgical procedure, with the most common procedure being coronary artery bypass graft (n = 38). Patients undergoing coronary artery bypass graft had the IIP included in their standard postoperative order set. The majority of patients were considered stable during the 12 hours prior to discontinuation of the IIP, including 23 patients with a history of DM. Of the 65 patients who were included in the study, 25 (38.5%) received a scheduled insulin order following discontinuation of the IIP, whereas 38 (58.5%) received some form of sliding‐scale insulin (SSI). Additionally, 2 (3%) patients did not receive any form of insulin order after stopping the IIP. Of those receiving scheduled insulin, 15 (60%) received neutral protamine Hagedorn, 5 (20%) received glargine, 5 (20%) received 70/30, and 1 (4%) received regular insulin. Of those receiving SSI only, the prescribed frequency was as follows: every 4 hours for 17 (45%), before meals and at bedtime for 15 (39%), every 6 hours for 5 (13%), and every 2 hours for 1 (3%).

A total of 562 glucose measurements were collected during the last 12 hours on the IIP, whereas 201 were collected during the first 12 hours immediately following the IIP. Patients demonstrated a significant increase in BG (mean standard deviation) during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP (168 50 mg/dL versus 123 26 mg/dL, P < 0.001). This corresponded to a significant decrease in the median (interquartile range) insulin administered during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP [8 (0‐18) units versus 40 (22‐65) units, P < 0.001; Figure 1]. A total of 1914 BG measurements were collected during the follow‐up period. Figure 2 shows mean BG values for all patients on the IIP compared to mean BG values for each day of the follow‐up period. There was a significant increase in mean BG measurements when the IIP was compared to each day of the follow‐up period, but there was no difference between days of the follow‐up period. Table 2 shows the proportion of patients experiencing at least 1 episode of hyperglycemia (BG > 150 mg/dL), significant hyperglycemia (BG > 200 mg/dL), severe hyperglycemia (BG > 300 mg/dL), or hypoglycemia (BG < 60 mg/dL) while receiving the IIP and during the follow‐up period. When comparing the IIP to the follow‐up period, we found a significant increase in the proportion of patients with at least 1 BG > 150 mg/dL. This was also true for patients with a BG of > 200 mg/dL.

Figure 1

Figure 2

The only independent predictor of a greater than 30% change in mean BG was the requirement for more than 20 units of insulin (>1.7 units/hour) during the last 12 hours on the IIP. The odds of a greater than 30% change was 4.62 times higher (95% confidence interval: 1.1718.17) in patients requiring more than 20 units during the last 12 hours on IIP after adjustments for stability on the protocol and past medical history of diabetes. Stability on the protocol was not identified as an independent predictor, with an adjusted odds ratio of 2.40 (95% confidence interval: 0.797.32).

DISCUSSION

This is the first study to describe glycemic control following the transition from an IIP to subcutaneous insulin. We observed that during the 5 days following discontinuation of an IIP, patients had significantly elevated mean BG values. These data are highlighted by the fact that patients received significantly less insulin during the first 12 hours of the follow‐up period versus the last 12 hours of the IIP. Additionally, a larger than expected proportion of patients exhibited at least 1 episode of hyperglycemia during the follow‐up period. We also found that an increased insulin requirement of >1.7 units/hour during the last 12 hours of the IIP was an independent risk factor for a greater than 30% increase in mean BG on day 1 of the follow‐up period.

Increasing evidence demonstrates that the development of hyperglycemia in the hospital setting is a marker of poor clinical outcome and mortality. In fact, hyperglycemia has been associated with prolonged hospital stay, infection, disability after discharge, and death in patients on general surgical and medical wards.1012 This makes the increase in mean BG found in our study following discontinuation of the IIP a concern.

SSI with subcutaneous short‐acting insulin has been used for inpatients as the standard of care for many years. However, evidence supporting the effectiveness of SSI alone is lacking, and it is not recommended by the American Diabetes Association.13 Queale et al.14 showed that SSI regimens when used alone were associated with suboptimal glycemic control and a 3‐fold higher risk of hyperglycemic episodes.1 Two retrospective studies have also demonstrated that SSI is less effective and widely variable in comparison with proactive preventative therapy.15, 16 In the current study, 58.5% of patients received SSI alone during the follow‐up period. As indicated in Figure 1, there was a significant increase in mean BG during this time interval. The choice of an inappropriate insulin regimen might be a contributing factor to poor glycemic control.

Because only 38.5% of patients were transitioned to scheduled insulin in our study, one possible strategy to help improve glycemic control would be to transition patients to a scheduled insulin regimen. Umpierrez et al.12 conducted a prospective, multicenter randomized trial to compare the efficacy and safety of a basal‐bolus insulin regimen with that of SSI in hospitalized type 2 diabetics. These authors found that patients treated with insulin glargine and glulisine had greater improvement in glycemic control than those treated with SSI (P < 0.01).12 Interestingly, the basal‐bolus method provides a maintenance insulin regimen that is aggressively titrated upward as well as an adjustable SSI based on insulin sensitivity. Patients in the current study may have benefited from a similar approach as many did not have their scheduled insulin adjusted despite persistent hyperglycemia.

With the increasing evidence for tight glycemic control in the ICU, a standardized transition from an intensive insulin infusion to a subcutaneous basal‐bolus regimen or other scheduled regimen is needed. To date, the current study is the first to describe this transition. Based on these data, recommendations for transitioning patients off an IIP provided by Furnary and Braithwaite17 should be considered by clinicians. In fact, one of their proposed predictors for unsuccessful transition was an insulin requirement of 2 units/hour. Indeed, the only independent risk factor for poor glycemic control identified in the current study was a requirement of >20 units (>1.7 units/hour) during the last 12 hours of the IIP. Further research is required to verify the other predictors suggested by Furnary and Braithwaite. They recommended using a standardized conversion protocol to transition patients off an IIP.

More recently, Kitabchi et al.18 recommended that a BG target of less than 180 mg/dL be maintained for the hospitalized patient.18 Although our study showed a mean BG less than 180 mg/dL during the follow‐up period, the variability in these values raises concerns for individual patients.

The current study is limited by its size and retrospective nature. As with all retrospective studies, the inability to control the implementation and discontinuation of the IIP may confound the results. However, this study demonstrates a real world experience with an IIP and illustrates the difficulties with transitioning patients to a subcutaneous regimen. BG values and administered insulin were collected only for the last 12 hours on the IIP. This duration is considered appropriate as this time period is used clinically at MUH, and previous recommendations for transitioning patients suggest using a time period of 6 to 8 hours to guide the transition insulin regimen.17 In addition, data regarding the severity of illness and new onset of infections were not collected for patients in the study. Both could affect glucose control. All patients had to be in an ICU to receive the IIP, but their location during the follow‐up period varied. Although these data were not available, control of BG is a problem that should be addressed whether the patient is in the ICU or not. Another possible limitation of the study was the identification of patients with or without a past medical history of DM. The inability to identify new‐onset or previously undiagnosed DM may have affected analyses based on this variable.

CONCLUSIONS

This study demonstrated a significant increase in mean BG following discontinuation of an IIP; this corresponded to a significant decrease in the amount of insulin administered. This increase was sustained for a period of at least 5 days. Additionally, an independent risk factor for poor glycemic control immediately following discontinuation of an IIP was an insulin requirement of >1.7 units/hour during the previous 12 hours. Further study into transitioning off an IIP is warranted.

Eight days prior to admission to our hospital, a 50‐year‐old morbidly obese patient presented to his primary care clinic, complaining of weakness, dizziness, and symptoms consistent with paroxysmal nocturnal dyspnea. He had a history of diabetes mellitus type 2, hypertension, chronic renal insufficiency with baseline creatinine in the range of 2.0 mg/dL, and atrial fibrillation on warfarin (10 mg/day). He was given diuretics and sent home. Two days later, the patient presented to a rural emergency department, complaining of leg pain and swelling. He was given cephalexin for cellulitis and discharged home. The evening prior to admission to our hospital, the patient developed sharp left‐sided chest pain, orthopnea, and worsening dyspnea. He again presented to the rural emergency department and was found to have a blood pressure of 60/40 mm Hg. He was admitted and given boluses of intravenous fluids and a dose of ceftriaxone. Laboratory studies at that time demonstrated the following: sodium, 130 mEq/L; potassium, 6.5 mEq/L; CO₂, 21 mEq/L; blood urea nitrogen (BUN), 105 mg/dL; creatinine, 5.5 mg/dL; alkaline phosphatase, 330 IU/L; aspartate aminotransferase (AST), 507 IU/L; and alanine aminotransferase (ALT), 145 IU/L. The following morning, he was oliguric, and his liver transaminases had increased to an AST level of 1862 IU/L and an ALT level of 1055 IU/L. At this point, he was transferred to our hospital for hemodialysis with a diagnosis of acute oliguric renal failure.

On admission to our hospital, the patient was afebrile, had a blood pressure of 112/80 mm Hg, and was hypoxic with an O₂ saturation of 93% on 4 L of oxygen by nasal cannula. His weight was 201 kg. He was alert and cooperative. Heart sounds were distant but had a regular rate and rhythm without murmurs, rubs, or gallops. No jugular venous pulsations were appreciated. He had decreased lung sounds throughout both lung fields. His abdomen was morbidly obese and nontender. Extremities demonstrated chronic venous stasis changes with multiple superficial ulcers and bilateral pitting edema.

In light of the elevated liver function tests reported by the referring hospital, these studies were repeated on arrival, revealing an AST level of 4780 IU/L and an ALT level of 1876 IU/L. Other initial laboratory studies demonstrated a BUN level of 116 mg/dL, a creatinine level of 6 mg/dL, a potassium level of 7.2 mEq/L, negative cardiac enzymes, and an international normalized ratio greater than 9.0. A urinalysis could not be performed because the patient was anuric. An electrocardiogram demonstrated a normal sinus rhythm with a right bundle branch block and nonspecific ST segment and T wave changes. There was no prior electrocardiogram available for comparison. Blood acetaminophen level and infectious hepatitis panels were negative.

Within 1 hour of admission, the patient became hypotensive, with his systolic blood pressure decreasing into the 70s. Over the next 24 hours, the patient was treated with intravenous fluids and pressors (neosynephrine) but remained hypotensive, with his systolic blood pressure in the range of 64 to 80 mm Hg.

At 14 hours after admission, liver function tests were repeated and revealed further elevation of his transaminases (AST, 5135 IU/L; ALT, 2468 IU/L). The diagnosis of shock liver was entertained. A portable chest X‐ray (CXR) demonstrated an enlarged cardiac silhouette suggestive of cardiomegaly or pericardial effusion. No prior CXR was available for comparison. An echocardiogram showed probable effusion but was not diagnostic secondary to his body habitus and poor windows. A computed tomography (CT) scan confirmed a large pericardial effusion. This finding, in combination with diminished heart sounds and hypotension, presented a clinical picture consistent with cardiac tamponade. The patient underwent a subxiphoid pericardial window, and 1.5 L of bloody effusion was removed. Intraoperatively, his systolic blood pressure immediately improved from 95 to 135 mm Hg. Urine output increased from 0 to 80 mL/hour in the first hour. Five days later, his creatinine returned to his baseline of 1.9 mg/dL, and other laboratory values had decreased: AST, 306 IU/L; ALT, 520 IU/L; alkaline phosphatase, 122 IU/L; and BUN, 86 mg/dL.

DISCUSSION

Acute renal failure (ARF) is a common condition, with an incidence of 1% on admission to the hospital; 70% of these cases are due to prerenal causes.1 Among patients already in the hospital, prerenal azotemia is responsible for 21% to 39% of cases of ARF.2, 3 Prerenal ARF is most commonly caused by hypotension, which may be cardiogenic, hypovolemic, septic, or due to vasodilatation. Adrenal insufficiency and other etiologies should also be considered. In our patient, chronic renal failure and superimposed hypotension contributed to acute oliguric renal failure. In searching for the etiology of his hypotension, we concentrated on cardiogenic causes in view of his enlarged cardiac silhouette.

In considering the cardiogenic causes of hypotension, we did not initially focus on tamponade. Although oliguria with renal failure is recognized as a complication of cardiac tamponade, relatively little has been written about ARF as the presenting problem in tamponade. The literature is limited to a few case reports, such as those described by Queffeulou et al.4 and Saklayen et al.5 In our patient, the diagnosis of tamponade was made more difficult by the patient's large size, which made the interpretation of physical findings such as heart sounds more difficult and compromised the quality of essential imaging studies.

His rising transaminases suggested shock liver and eventually provided the key to the patient's diagnosis. In light of his worsening liver function tests, chest pain, shortness of breath, and cardiomegaly on CXR, we focused on a cardiac etiology. An echocardiogram, which often can be used to identify pericardial effusion and hence tamponade, was nondiagnostic because of the patient's obesity. Despite the concerns regarding the weight limits of the examination table, the diagnosis was finally established with a CT scan.

In our patient, no definite cause for his bloody pericardial effusion was found. Cardiac enzymes were negative, and this helped rule out ischemia. Nothing indicative of a neoplasm was seen on the CT of his chest. Blood cultures were negative. Viral studies were not performed, and the effusion was not sent for special studies. He may have had an underlying pericarditis secondary to his chronic kidney disease or a viral syndrome that, combined with his anticoagulation treatment, resulted in a bloody effusion.

In addition to illustrating the difficulties in properly diagnosing acutely ill morbidly obese patients, this report also demonstrates that in patients with shock liver and ARF, pericardial tamponade may be the culprit. If preliminary studies including CXR and echocardiogram are equivocal and sufficient suspicion remains, then a CT is warranted.

Eight days prior to admission to our hospital, a 50‐year‐old morbidly obese patient presented to his primary care clinic, complaining of weakness, dizziness, and symptoms consistent with paroxysmal nocturnal dyspnea. He had a history of diabetes mellitus type 2, hypertension, chronic renal insufficiency with baseline creatinine in the range of 2.0 mg/dL, and atrial fibrillation on warfarin (10 mg/day). He was given diuretics and sent home. Two days later, the patient presented to a rural emergency department, complaining of leg pain and swelling. He was given cephalexin for cellulitis and discharged home. The evening prior to admission to our hospital, the patient developed sharp left‐sided chest pain, orthopnea, and worsening dyspnea. He again presented to the rural emergency department and was found to have a blood pressure of 60/40 mm Hg. He was admitted and given boluses of intravenous fluids and a dose of ceftriaxone. Laboratory studies at that time demonstrated the following: sodium, 130 mEq/L; potassium, 6.5 mEq/L; CO₂, 21 mEq/L; blood urea nitrogen (BUN), 105 mg/dL; creatinine, 5.5 mg/dL; alkaline phosphatase, 330 IU/L; aspartate aminotransferase (AST), 507 IU/L; and alanine aminotransferase (ALT), 145 IU/L. The following morning, he was oliguric, and his liver transaminases had increased to an AST level of 1862 IU/L and an ALT level of 1055 IU/L. At this point, he was transferred to our hospital for hemodialysis with a diagnosis of acute oliguric renal failure.

On admission to our hospital, the patient was afebrile, had a blood pressure of 112/80 mm Hg, and was hypoxic with an O₂ saturation of 93% on 4 L of oxygen by nasal cannula. His weight was 201 kg. He was alert and cooperative. Heart sounds were distant but had a regular rate and rhythm without murmurs, rubs, or gallops. No jugular venous pulsations were appreciated. He had decreased lung sounds throughout both lung fields. His abdomen was morbidly obese and nontender. Extremities demonstrated chronic venous stasis changes with multiple superficial ulcers and bilateral pitting edema.

In light of the elevated liver function tests reported by the referring hospital, these studies were repeated on arrival, revealing an AST level of 4780 IU/L and an ALT level of 1876 IU/L. Other initial laboratory studies demonstrated a BUN level of 116 mg/dL, a creatinine level of 6 mg/dL, a potassium level of 7.2 mEq/L, negative cardiac enzymes, and an international normalized ratio greater than 9.0. A urinalysis could not be performed because the patient was anuric. An electrocardiogram demonstrated a normal sinus rhythm with a right bundle branch block and nonspecific ST segment and T wave changes. There was no prior electrocardiogram available for comparison. Blood acetaminophen level and infectious hepatitis panels were negative.

Within 1 hour of admission, the patient became hypotensive, with his systolic blood pressure decreasing into the 70s. Over the next 24 hours, the patient was treated with intravenous fluids and pressors (neosynephrine) but remained hypotensive, with his systolic blood pressure in the range of 64 to 80 mm Hg.

At 14 hours after admission, liver function tests were repeated and revealed further elevation of his transaminases (AST, 5135 IU/L; ALT, 2468 IU/L). The diagnosis of shock liver was entertained. A portable chest X‐ray (CXR) demonstrated an enlarged cardiac silhouette suggestive of cardiomegaly or pericardial effusion. No prior CXR was available for comparison. An echocardiogram showed probable effusion but was not diagnostic secondary to his body habitus and poor windows. A computed tomography (CT) scan confirmed a large pericardial effusion. This finding, in combination with diminished heart sounds and hypotension, presented a clinical picture consistent with cardiac tamponade. The patient underwent a subxiphoid pericardial window, and 1.5 L of bloody effusion was removed. Intraoperatively, his systolic blood pressure immediately improved from 95 to 135 mm Hg. Urine output increased from 0 to 80 mL/hour in the first hour. Five days later, his creatinine returned to his baseline of 1.9 mg/dL, and other laboratory values had decreased: AST, 306 IU/L; ALT, 520 IU/L; alkaline phosphatase, 122 IU/L; and BUN, 86 mg/dL.

DISCUSSION

Acute renal failure (ARF) is a common condition, with an incidence of 1% on admission to the hospital; 70% of these cases are due to prerenal causes.1 Among patients already in the hospital, prerenal azotemia is responsible for 21% to 39% of cases of ARF.2, 3 Prerenal ARF is most commonly caused by hypotension, which may be cardiogenic, hypovolemic, septic, or due to vasodilatation. Adrenal insufficiency and other etiologies should also be considered. In our patient, chronic renal failure and superimposed hypotension contributed to acute oliguric renal failure. In searching for the etiology of his hypotension, we concentrated on cardiogenic causes in view of his enlarged cardiac silhouette.

In considering the cardiogenic causes of hypotension, we did not initially focus on tamponade. Although oliguria with renal failure is recognized as a complication of cardiac tamponade, relatively little has been written about ARF as the presenting problem in tamponade. The literature is limited to a few case reports, such as those described by Queffeulou et al.4 and Saklayen et al.5 In our patient, the diagnosis of tamponade was made more difficult by the patient's large size, which made the interpretation of physical findings such as heart sounds more difficult and compromised the quality of essential imaging studies.

His rising transaminases suggested shock liver and eventually provided the key to the patient's diagnosis. In light of his worsening liver function tests, chest pain, shortness of breath, and cardiomegaly on CXR, we focused on a cardiac etiology. An echocardiogram, which often can be used to identify pericardial effusion and hence tamponade, was nondiagnostic because of the patient's obesity. Despite the concerns regarding the weight limits of the examination table, the diagnosis was finally established with a CT scan.

In our patient, no definite cause for his bloody pericardial effusion was found. Cardiac enzymes were negative, and this helped rule out ischemia. Nothing indicative of a neoplasm was seen on the CT of his chest. Blood cultures were negative. Viral studies were not performed, and the effusion was not sent for special studies. He may have had an underlying pericarditis secondary to his chronic kidney disease or a viral syndrome that, combined with his anticoagulation treatment, resulted in a bloody effusion.

In addition to illustrating the difficulties in properly diagnosing acutely ill morbidly obese patients, this report also demonstrates that in patients with shock liver and ARF, pericardial tamponade may be the culprit. If preliminary studies including CXR and echocardiogram are equivocal and sufficient suspicion remains, then a CT is warranted.

Eight days prior to admission to our hospital, a 50‐year‐old morbidly obese patient presented to his primary care clinic, complaining of weakness, dizziness, and symptoms consistent with paroxysmal nocturnal dyspnea. He had a history of diabetes mellitus type 2, hypertension, chronic renal insufficiency with baseline creatinine in the range of 2.0 mg/dL, and atrial fibrillation on warfarin (10 mg/day). He was given diuretics and sent home. Two days later, the patient presented to a rural emergency department, complaining of leg pain and swelling. He was given cephalexin for cellulitis and discharged home. The evening prior to admission to our hospital, the patient developed sharp left‐sided chest pain, orthopnea, and worsening dyspnea. He again presented to the rural emergency department and was found to have a blood pressure of 60/40 mm Hg. He was admitted and given boluses of intravenous fluids and a dose of ceftriaxone. Laboratory studies at that time demonstrated the following: sodium, 130 mEq/L; potassium, 6.5 mEq/L; CO₂, 21 mEq/L; blood urea nitrogen (BUN), 105 mg/dL; creatinine, 5.5 mg/dL; alkaline phosphatase, 330 IU/L; aspartate aminotransferase (AST), 507 IU/L; and alanine aminotransferase (ALT), 145 IU/L. The following morning, he was oliguric, and his liver transaminases had increased to an AST level of 1862 IU/L and an ALT level of 1055 IU/L. At this point, he was transferred to our hospital for hemodialysis with a diagnosis of acute oliguric renal failure.

On admission to our hospital, the patient was afebrile, had a blood pressure of 112/80 mm Hg, and was hypoxic with an O₂ saturation of 93% on 4 L of oxygen by nasal cannula. His weight was 201 kg. He was alert and cooperative. Heart sounds were distant but had a regular rate and rhythm without murmurs, rubs, or gallops. No jugular venous pulsations were appreciated. He had decreased lung sounds throughout both lung fields. His abdomen was morbidly obese and nontender. Extremities demonstrated chronic venous stasis changes with multiple superficial ulcers and bilateral pitting edema.

In light of the elevated liver function tests reported by the referring hospital, these studies were repeated on arrival, revealing an AST level of 4780 IU/L and an ALT level of 1876 IU/L. Other initial laboratory studies demonstrated a BUN level of 116 mg/dL, a creatinine level of 6 mg/dL, a potassium level of 7.2 mEq/L, negative cardiac enzymes, and an international normalized ratio greater than 9.0. A urinalysis could not be performed because the patient was anuric. An electrocardiogram demonstrated a normal sinus rhythm with a right bundle branch block and nonspecific ST segment and T wave changes. There was no prior electrocardiogram available for comparison. Blood acetaminophen level and infectious hepatitis panels were negative.

Within 1 hour of admission, the patient became hypotensive, with his systolic blood pressure decreasing into the 70s. Over the next 24 hours, the patient was treated with intravenous fluids and pressors (neosynephrine) but remained hypotensive, with his systolic blood pressure in the range of 64 to 80 mm Hg.

At 14 hours after admission, liver function tests were repeated and revealed further elevation of his transaminases (AST, 5135 IU/L; ALT, 2468 IU/L). The diagnosis of shock liver was entertained. A portable chest X‐ray (CXR) demonstrated an enlarged cardiac silhouette suggestive of cardiomegaly or pericardial effusion. No prior CXR was available for comparison. An echocardiogram showed probable effusion but was not diagnostic secondary to his body habitus and poor windows. A computed tomography (CT) scan confirmed a large pericardial effusion. This finding, in combination with diminished heart sounds and hypotension, presented a clinical picture consistent with cardiac tamponade. The patient underwent a subxiphoid pericardial window, and 1.5 L of bloody effusion was removed. Intraoperatively, his systolic blood pressure immediately improved from 95 to 135 mm Hg. Urine output increased from 0 to 80 mL/hour in the first hour. Five days later, his creatinine returned to his baseline of 1.9 mg/dL, and other laboratory values had decreased: AST, 306 IU/L; ALT, 520 IU/L; alkaline phosphatase, 122 IU/L; and BUN, 86 mg/dL.

DISCUSSION

Acute renal failure (ARF) is a common condition, with an incidence of 1% on admission to the hospital; 70% of these cases are due to prerenal causes.1 Among patients already in the hospital, prerenal azotemia is responsible for 21% to 39% of cases of ARF.2, 3 Prerenal ARF is most commonly caused by hypotension, which may be cardiogenic, hypovolemic, septic, or due to vasodilatation. Adrenal insufficiency and other etiologies should also be considered. In our patient, chronic renal failure and superimposed hypotension contributed to acute oliguric renal failure. In searching for the etiology of his hypotension, we concentrated on cardiogenic causes in view of his enlarged cardiac silhouette.

In considering the cardiogenic causes of hypotension, we did not initially focus on tamponade. Although oliguria with renal failure is recognized as a complication of cardiac tamponade, relatively little has been written about ARF as the presenting problem in tamponade. The literature is limited to a few case reports, such as those described by Queffeulou et al.4 and Saklayen et al.5 In our patient, the diagnosis of tamponade was made more difficult by the patient's large size, which made the interpretation of physical findings such as heart sounds more difficult and compromised the quality of essential imaging studies.

His rising transaminases suggested shock liver and eventually provided the key to the patient's diagnosis. In light of his worsening liver function tests, chest pain, shortness of breath, and cardiomegaly on CXR, we focused on a cardiac etiology. An echocardiogram, which often can be used to identify pericardial effusion and hence tamponade, was nondiagnostic because of the patient's obesity. Despite the concerns regarding the weight limits of the examination table, the diagnosis was finally established with a CT scan.

In our patient, no definite cause for his bloody pericardial effusion was found. Cardiac enzymes were negative, and this helped rule out ischemia. Nothing indicative of a neoplasm was seen on the CT of his chest. Blood cultures were negative. Viral studies were not performed, and the effusion was not sent for special studies. He may have had an underlying pericarditis secondary to his chronic kidney disease or a viral syndrome that, combined with his anticoagulation treatment, resulted in a bloody effusion.

In addition to illustrating the difficulties in properly diagnosing acutely ill morbidly obese patients, this report also demonstrates that in patients with shock liver and ARF, pericardial tamponade may be the culprit. If preliminary studies including CXR and echocardiogram are equivocal and sufficient suspicion remains, then a CT is warranted.

Diabetes mellitus and/or inpatient hyperglycemia are common comorbid conditions in hospitalized patients. Recent surveys show that over 90% of hospitalized diabetic patients experience hyperglycemia (>200 mg/dL), and in nearly 1 in 5 of these patients hyperglycemia persists for 3 days or more.1 Hyperglycemia among inpatients without a previous history of diabetes mellitus is also very common.2 Observational studies have shown that hyperglycemia in hospitalized patients is associated with adverse outcomes including infectious complications, increased length of stay, and increased mortality.27 Recent randomized controlled trials have demonstrated that aggressive treatment of inpatient hyperglycemia improves outcomes in surgical and medical intensive care units.8, 9

Based on the available data, the American Diabetes Association (ADA) now advocates good metabolic control, defined as preprandial glucose levels of 90 to 130 mg/dL and peak postprandial glucose levels <180 mg/dL in hospitalized nonintensive care unit (ICU) patients.10 To reach these targets, the ADA and American College of Endocrinology (ACE) suggest that multidisciplinary teams develop and implement hyperglycemia management guidelines and protocols.11 Protocols should promote the use of continuous intravenous insulin infusions or scheduled basal‐bolus subcutaneous insulin regimens. Subcutaneous insulin protocols should include target glucose levels, basal, nutritional, and supplemental insulin, and daily dose adjustments.6 A recent randomized controlled trial of non‐ICU inpatients demonstrated that such a basal‐bolus insulin regimen results in improved glucose control compared with a sliding scale only regimen.12

To date, few published studies have investigated the best ways to implement such management protocols; those that have are often resource‐intensive, for example involving daily involvement of nurse practitioners or diabetologists.13, 14 It is therefore not known how best to implement an inpatient diabetes management program that is effective, efficient, and self‐perpetuating. At Brigham and Women's Hospital (BWH), we have been refining a subcutaneous insulin protocol, focused provider education, and more recently a computerized order set to overcome barriers related to fear of hypoglycemia, delays in insulin prescribing, and unfamiliarity with inpatient glucose management.15 The aims of this current trial were to evaluate the effects of these interventions on a geographically localized general medical service previously naive to these interventions to evaluate their effects on glycemic control, patient safety, and processes of care. We hypothesized that these interventions would improve glycemic control and increase use of basal‐bolus insulin orders without increasing the rate of hypoglycemia.

METHODS

RESULTS

We prospectively identified 248 potential patients for the study. We subsequently excluded 79 patients for the following reasons: no glucose readings beyond hospital day 1 while on PACE service (34 patients); never admitted to PACE service (15 patients); no diabetes or inpatient hyperglycemia (9 patients, mostly patients prescribed an insulin sliding scale prophylactically to avoid steroid‐induced hyperglycemia); type 1 diabetes (13 patients); TPN, DKA, or HHS (5 patients); and palliative care (3 patients). The remaining 169 patients included 63 from the preintervention period(out of 489 total admissions to the PACE service; 13%) and 106 patients in the postintervention period (out of 565 admissions; 19%). These patients had 2447 glucose readings, or an average of 3.6 glucose readings per monitored patient‐day in the preintervention period and 3.3 glucose readings per patient‐day in the postintervention period. Even including the 34 patients who were excluded for lack of glucose readings, glucose data were still available for 717 out of a potential 775 patient‐days (93%). Characteristics for all included patients are shown in Table 2. The mean admission glucose was 197 mg/dL, mean A1C was 8.4%, 54% of the patients were prescribed insulin prior to admission, and 7% had no prior diagnosis of diabetes. There were no significant differences in baseline characteristics between the 2 patient groups except for Charlson score, which was higher in the preintervention group (87% versus 74% with score 2 or higher; Table 2). The top diagnosis‐related groups for the entire cohort included: heart failure and shock (12 patients); kidney and urinary tract infections (12 patients); esophagitis, gastroenteritis, and miscellaneous digestive disorders (11 patients); chronic obstructive pulmonary disease (10 patients); renal failure (10 patients); simple pneumonia and pleurisy (7 patients); disorders of the pancreas except malignancy (6 patients); chest pain (5 patients); and cellulitis (5 patients).

With respect to insulin ordering practices, there was no significant difference in the use of basal insulin in hyperglycemic patients between the preintervention period and postintervention period (81% versus 91%; P = 0.17), nor in the dose of basal insulin prescribed (results not shown), but there was an increase in the use of scheduled nutritional insulin for those patients with hyperglycemia receiving nutrition: 40% versus 75%, P < 0.001 (Table 3). The percent of patients receiving supplemental (sliding scale) insulin by itself (ie, without ever receiving basal or nutritional insulin) was lower during the postintervention period (29% versus 8%, P < 0.001). Nonsignificant differences were seen in the rates of prescribing an appropriate dose and type of nutritional insulin. Notably, there was no difference at all in the proportion of patient‐days in which insulin adjustments were made when 2 or more episodes of hyperglycemia or hypoglycemia were present during the previous day (56% of patient‐days in both groups; P = 0.90).

The primary outcome, the mean percent of glucose readings between 60 and 180 mg/dL per patient, was 59.1% in the preintervention period and 64.7% in the postintervention (P = 0.13 in unadjusted analysis; Table 3). When adjusted for A1C, admission glucose, and insulin use prior to admission, the adjusted absolute difference in the percent of glucose readings within range was 9.7% (95% confidence interval [CI], 0.6%‐18.8%; P = 0.04; Table 3). Regarding other measures of glucose control, the patient‐day weighted mean glucose was 174.7 mg/dL in the preintervention period and 164.6 mg/dL postintervention (P = 0.02), and there was no significant difference in the percent of patient‐days with any hypoglycemia (glucose <60 mg/dL) or severe hypoglycemia (glucose <40 mg/dL; Table 3). There were also no significant differences in the mean number of hypoglycemic events per patient‐day (6.8 versus 6.6 per 100 patient‐days; relative risk, 0.95; 95% CI, 0.541.67; P = 0.87) or severe hypoglycemic events per patient‐day (1.0 versus 1.4 per 100 patient‐days; relative risk, 1.38; 95% CI, 0.355.53; P = 0.65).

We also compared hospital length of stay in hours between the study groups (Table 3). Length of stay (LOS) was shorter in the postintervention arm in unadjusted analyses (112 versus 86 hours; P < 0.001), and this difference persisted when adjusted for patient insurance, race, gender, and Charlson comorbidity score (25% shorter; 95% CI, 6%‐44%). A comparison of LOS among nonstudy patients on the PACE service during these 2 time periods revealed no difference (105 versus 101 hours). When the length of stay analysis was limited to study patients with a known diagnosis of diabetes, the adjusted effect size was a 31% relative decrease in length of stay.

Figure 1A shows the percent glucose readings within range per patient by hospital day. The greatest differences between groups can be seen on hospital days 2 and 3 (11% absolute differences on both days). Similarly, Figure 1B shows the mean glucose per patient by hospital day. Again, the biggest differences are seen on hospital days 2 and 3 (20 and 23 mg/dL difference between groups, respectively). In both cases, only the day 3 comparisons were significantly different between study groups.

Figure 1

DISCUSSION

In this before‐after study, we found that a multifaceted intervention consisting of a subcutaneous insulin protocol, focused education, and an order set built into the hospital's CPOE system was associated with a significantly higher percentage of glucose readings within range per patient in analyses adjusted for patient demographics and severity of diabetes. We also found a significant decrease in patient‐day weighted mean glucose, a marked increase in appropriate use of scheduled nutritional insulin, and a concomitant decrease in sliding scale insulin only regimens during the postintervention period. Moreover, we found a shorter length of stay during the postintervention period that persisted after adjustment for several clinical factors. Importantly, the interventions described in this study require very few resources to continue indefinitely: printing costs for the management protocol, 4 hours of education delivered per year, and routine upkeep of an electronic order set.

Because this was a before‐after study, we cannot exclude the possibility that these improvements in process and outcome were due to cointerventions and/or temporal trends. However, we know of no other interventions aimed at improving diabetes care in this self‐contained service of nurses, PAs, and hospitalists. Moreover, the process improvements, especially the increase in scheduled nutritional insulin, were rather marked, unlikely to be due to temporal trends alone, and likely capable of producing the corresponding improvements in glucose control. That glucose control stopped improving after hospital day 3 may be due to the fact that subsequent adjustment to insulin orders occurred infrequently and no more often than prior to the intervention. That we did not see greater improvements in glycemic control overall may also reflect the fact that 81% of study patients with inpatient hyperglycemia received basal insulin prior to the intervention.

The reduction in patient LOS was somewhat surprising given the relatively small sample size. However, the results are consistent with those of other studies linking hyperglycemia to LOS18, 19 and we found no evidence for a temporal trend toward lower LOS on the PACE service as a whole during the same time period. While a greater proportion of patients on the PACE service were in the study in the post‐intervention period compared with the preintervention period, we found no evidence that the difference in length of stay was due to increased surveillance for nondiabetics, especially because eligibility criteria depended on phlebotomy glucose values, which were uniformly tested in all inpatients. Also, effects on length of stay were actually stronger when limited to patients with known diabetes. Finally, we controlled for several predictors of length of stay, although we still cannot exclude the possibility of unmeasured confounding between groups.

Since ADA and ACE issued guidelines for inpatient management of diabetes and hyperglycemia, many institutions have developed subcutaneous insulin algorithms, educational curricula, and/or order sets to increase compliance with these guidelines and improve glycemic control. Some of these efforts have been studied and some have been successful in their efforts.13, 14, 2023 Unfortunately, most of these programs have not rigorously assessed their impact on process and outcomes, and the most effective studies published to date have involved interventions much more intensive than those described here. For example, Rush University's intervention was associated with a 50 mg/dL decrease in mean blood glucose but involved an endocrinologist rounding twice daily with house officers for 2 weeks at a time.13 At Northwestern University, a diabetes management service run by nurse practitioners was established, and the focus was on the conversion from intravenous to subcutaneous insulin regimens.14 The RABBIT 2 study that demonstrated the benefits of a basal‐bolus insulin regimen used daily rounding with an endocrinologist.12 More modestly, a program in Pitt County Memorial Hospital in Greenville, NC, relied mostly on diabetes nurse case managers, a strategy which reduced hospital‐wide mean glucose levels as well as LOS, although the greatest improvements in glycemic control were seen in the ICU.19 Our findings are much more consistent with those from University of California San Diego, as yet unpublished, which also used an algorithm, computerized order set, education, as well as continuous quality improvement methods to achieve its aims.22

Our study has several limitations, including being conducted on 1 general medicine service at 1 academic medical center. Moreover, this service, using a physician assistant/hospitalist model, a closed geographic unit, and fairly generous staffing ratio, is likely different from those in many settings and may limit the generalizability of our findings. However, this model allowed us to conduct the study in a laboratory relatively untouched by other cointerventions. Furthermore, the use of PAs in this way may become more common as both academic and community hospitals rely more on mid‐level providers. Our study had a relatively low percentage of patients without a known diagnosis of diabetes compared with other studies, again potentially but not necessarily limiting generalizability. This finding has been shown in other studies at our institution24 and may be due to the high rate of screening for diabetes in the community. Another limitation is that this was a nonrandomized, before‐after trial. However, all subjects were prospectively enrolled to improve comparability, and we performed rigorous adjustment for multiple potential confounding factors. Also, this study had limited statistical power to detect differences in hypoglycemia rates. The preintervention arm was smaller than planned due to fewer diabetic patients than expected on the service and a higher number of exclusions; we prolonged the postintervention period to achieve the desired sample size for that arm of the study.

Our study also has several strengths, including electronic capture of many processes of care and a methodology to operationalize them into measures of protocol adherence. Our metrics of glycemic control were rigorously designed and based on a national task force on inpatient glycemic control sponsored by the Society of Hospital Medicine, with representation from the ADA and AACE.25

Potential future improvements to this intervention include modifications to the daily adjustment algorithm to improve its usability and ability to improve glucose control. Another is the use of high‐reliability methods to improve order set use and daily insulin adjustment, including alerts within the CPOE system and nurse empowerment to contact medical teams if glucose levels are out of range (eg, if greater than 180 mg/dL, not just if greater than 350 or 400 mg/dL). Future research directions include multicenter, randomized controlled trials of these types of interventions and an analysis of more distal patient outcomes including total healthcare utilization, infection rates, end‐organ damage, and mortality.

In conclusion, we found a relationship between a relatively low‐cost quality improvement intervention and improved glycemic control in the non‐ICU general medical setting. Such a finding suggests the benefits of the algorithm itself to improve glucose control and of our implementation strategy. Other institutions may find this intervention a useful starting point for their own quality improvement efforts. Both the algorithm and implementation strategy are deserving of further improvements and future study.

Diabetes mellitus and/or inpatient hyperglycemia are common comorbid conditions in hospitalized patients. Recent surveys show that over 90% of hospitalized diabetic patients experience hyperglycemia (>200 mg/dL), and in nearly 1 in 5 of these patients hyperglycemia persists for 3 days or more.1 Hyperglycemia among inpatients without a previous history of diabetes mellitus is also very common.2 Observational studies have shown that hyperglycemia in hospitalized patients is associated with adverse outcomes including infectious complications, increased length of stay, and increased mortality.27 Recent randomized controlled trials have demonstrated that aggressive treatment of inpatient hyperglycemia improves outcomes in surgical and medical intensive care units.8, 9

Based on the available data, the American Diabetes Association (ADA) now advocates good metabolic control, defined as preprandial glucose levels of 90 to 130 mg/dL and peak postprandial glucose levels <180 mg/dL in hospitalized nonintensive care unit (ICU) patients.10 To reach these targets, the ADA and American College of Endocrinology (ACE) suggest that multidisciplinary teams develop and implement hyperglycemia management guidelines and protocols.11 Protocols should promote the use of continuous intravenous insulin infusions or scheduled basal‐bolus subcutaneous insulin regimens. Subcutaneous insulin protocols should include target glucose levels, basal, nutritional, and supplemental insulin, and daily dose adjustments.6 A recent randomized controlled trial of non‐ICU inpatients demonstrated that such a basal‐bolus insulin regimen results in improved glucose control compared with a sliding scale only regimen.12

To date, few published studies have investigated the best ways to implement such management protocols; those that have are often resource‐intensive, for example involving daily involvement of nurse practitioners or diabetologists.13, 14 It is therefore not known how best to implement an inpatient diabetes management program that is effective, efficient, and self‐perpetuating. At Brigham and Women's Hospital (BWH), we have been refining a subcutaneous insulin protocol, focused provider education, and more recently a computerized order set to overcome barriers related to fear of hypoglycemia, delays in insulin prescribing, and unfamiliarity with inpatient glucose management.15 The aims of this current trial were to evaluate the effects of these interventions on a geographically localized general medical service previously naive to these interventions to evaluate their effects on glycemic control, patient safety, and processes of care. We hypothesized that these interventions would improve glycemic control and increase use of basal‐bolus insulin orders without increasing the rate of hypoglycemia.

METHODS

RESULTS

We prospectively identified 248 potential patients for the study. We subsequently excluded 79 patients for the following reasons: no glucose readings beyond hospital day 1 while on PACE service (34 patients); never admitted to PACE service (15 patients); no diabetes or inpatient hyperglycemia (9 patients, mostly patients prescribed an insulin sliding scale prophylactically to avoid steroid‐induced hyperglycemia); type 1 diabetes (13 patients); TPN, DKA, or HHS (5 patients); and palliative care (3 patients). The remaining 169 patients included 63 from the preintervention period(out of 489 total admissions to the PACE service; 13%) and 106 patients in the postintervention period (out of 565 admissions; 19%). These patients had 2447 glucose readings, or an average of 3.6 glucose readings per monitored patient‐day in the preintervention period and 3.3 glucose readings per patient‐day in the postintervention period. Even including the 34 patients who were excluded for lack of glucose readings, glucose data were still available for 717 out of a potential 775 patient‐days (93%). Characteristics for all included patients are shown in Table 2. The mean admission glucose was 197 mg/dL, mean A1C was 8.4%, 54% of the patients were prescribed insulin prior to admission, and 7% had no prior diagnosis of diabetes. There were no significant differences in baseline characteristics between the 2 patient groups except for Charlson score, which was higher in the preintervention group (87% versus 74% with score 2 or higher; Table 2). The top diagnosis‐related groups for the entire cohort included: heart failure and shock (12 patients); kidney and urinary tract infections (12 patients); esophagitis, gastroenteritis, and miscellaneous digestive disorders (11 patients); chronic obstructive pulmonary disease (10 patients); renal failure (10 patients); simple pneumonia and pleurisy (7 patients); disorders of the pancreas except malignancy (6 patients); chest pain (5 patients); and cellulitis (5 patients).

With respect to insulin ordering practices, there was no significant difference in the use of basal insulin in hyperglycemic patients between the preintervention period and postintervention period (81% versus 91%; P = 0.17), nor in the dose of basal insulin prescribed (results not shown), but there was an increase in the use of scheduled nutritional insulin for those patients with hyperglycemia receiving nutrition: 40% versus 75%, P < 0.001 (Table 3). The percent of patients receiving supplemental (sliding scale) insulin by itself (ie, without ever receiving basal or nutritional insulin) was lower during the postintervention period (29% versus 8%, P < 0.001). Nonsignificant differences were seen in the rates of prescribing an appropriate dose and type of nutritional insulin. Notably, there was no difference at all in the proportion of patient‐days in which insulin adjustments were made when 2 or more episodes of hyperglycemia or hypoglycemia were present during the previous day (56% of patient‐days in both groups; P = 0.90).

The primary outcome, the mean percent of glucose readings between 60 and 180 mg/dL per patient, was 59.1% in the preintervention period and 64.7% in the postintervention (P = 0.13 in unadjusted analysis; Table 3). When adjusted for A1C, admission glucose, and insulin use prior to admission, the adjusted absolute difference in the percent of glucose readings within range was 9.7% (95% confidence interval [CI], 0.6%‐18.8%; P = 0.04; Table 3). Regarding other measures of glucose control, the patient‐day weighted mean glucose was 174.7 mg/dL in the preintervention period and 164.6 mg/dL postintervention (P = 0.02), and there was no significant difference in the percent of patient‐days with any hypoglycemia (glucose <60 mg/dL) or severe hypoglycemia (glucose <40 mg/dL; Table 3). There were also no significant differences in the mean number of hypoglycemic events per patient‐day (6.8 versus 6.6 per 100 patient‐days; relative risk, 0.95; 95% CI, 0.541.67; P = 0.87) or severe hypoglycemic events per patient‐day (1.0 versus 1.4 per 100 patient‐days; relative risk, 1.38; 95% CI, 0.355.53; P = 0.65).

We also compared hospital length of stay in hours between the study groups (Table 3). Length of stay (LOS) was shorter in the postintervention arm in unadjusted analyses (112 versus 86 hours; P < 0.001), and this difference persisted when adjusted for patient insurance, race, gender, and Charlson comorbidity score (25% shorter; 95% CI, 6%‐44%). A comparison of LOS among nonstudy patients on the PACE service during these 2 time periods revealed no difference (105 versus 101 hours). When the length of stay analysis was limited to study patients with a known diagnosis of diabetes, the adjusted effect size was a 31% relative decrease in length of stay.

Figure 1A shows the percent glucose readings within range per patient by hospital day. The greatest differences between groups can be seen on hospital days 2 and 3 (11% absolute differences on both days). Similarly, Figure 1B shows the mean glucose per patient by hospital day. Again, the biggest differences are seen on hospital days 2 and 3 (20 and 23 mg/dL difference between groups, respectively). In both cases, only the day 3 comparisons were significantly different between study groups.

Figure 1

DISCUSSION

In this before‐after study, we found that a multifaceted intervention consisting of a subcutaneous insulin protocol, focused education, and an order set built into the hospital's CPOE system was associated with a significantly higher percentage of glucose readings within range per patient in analyses adjusted for patient demographics and severity of diabetes. We also found a significant decrease in patient‐day weighted mean glucose, a marked increase in appropriate use of scheduled nutritional insulin, and a concomitant decrease in sliding scale insulin only regimens during the postintervention period. Moreover, we found a shorter length of stay during the postintervention period that persisted after adjustment for several clinical factors. Importantly, the interventions described in this study require very few resources to continue indefinitely: printing costs for the management protocol, 4 hours of education delivered per year, and routine upkeep of an electronic order set.

Because this was a before‐after study, we cannot exclude the possibility that these improvements in process and outcome were due to cointerventions and/or temporal trends. However, we know of no other interventions aimed at improving diabetes care in this self‐contained service of nurses, PAs, and hospitalists. Moreover, the process improvements, especially the increase in scheduled nutritional insulin, were rather marked, unlikely to be due to temporal trends alone, and likely capable of producing the corresponding improvements in glucose control. That glucose control stopped improving after hospital day 3 may be due to the fact that subsequent adjustment to insulin orders occurred infrequently and no more often than prior to the intervention. That we did not see greater improvements in glycemic control overall may also reflect the fact that 81% of study patients with inpatient hyperglycemia received basal insulin prior to the intervention.

The reduction in patient LOS was somewhat surprising given the relatively small sample size. However, the results are consistent with those of other studies linking hyperglycemia to LOS18, 19 and we found no evidence for a temporal trend toward lower LOS on the PACE service as a whole during the same time period. While a greater proportion of patients on the PACE service were in the study in the post‐intervention period compared with the preintervention period, we found no evidence that the difference in length of stay was due to increased surveillance for nondiabetics, especially because eligibility criteria depended on phlebotomy glucose values, which were uniformly tested in all inpatients. Also, effects on length of stay were actually stronger when limited to patients with known diabetes. Finally, we controlled for several predictors of length of stay, although we still cannot exclude the possibility of unmeasured confounding between groups.

Since ADA and ACE issued guidelines for inpatient management of diabetes and hyperglycemia, many institutions have developed subcutaneous insulin algorithms, educational curricula, and/or order sets to increase compliance with these guidelines and improve glycemic control. Some of these efforts have been studied and some have been successful in their efforts.13, 14, 2023 Unfortunately, most of these programs have not rigorously assessed their impact on process and outcomes, and the most effective studies published to date have involved interventions much more intensive than those described here. For example, Rush University's intervention was associated with a 50 mg/dL decrease in mean blood glucose but involved an endocrinologist rounding twice daily with house officers for 2 weeks at a time.13 At Northwestern University, a diabetes management service run by nurse practitioners was established, and the focus was on the conversion from intravenous to subcutaneous insulin regimens.14 The RABBIT 2 study that demonstrated the benefits of a basal‐bolus insulin regimen used daily rounding with an endocrinologist.12 More modestly, a program in Pitt County Memorial Hospital in Greenville, NC, relied mostly on diabetes nurse case managers, a strategy which reduced hospital‐wide mean glucose levels as well as LOS, although the greatest improvements in glycemic control were seen in the ICU.19 Our findings are much more consistent with those from University of California San Diego, as yet unpublished, which also used an algorithm, computerized order set, education, as well as continuous quality improvement methods to achieve its aims.22

Our study has several limitations, including being conducted on 1 general medicine service at 1 academic medical center. Moreover, this service, using a physician assistant/hospitalist model, a closed geographic unit, and fairly generous staffing ratio, is likely different from those in many settings and may limit the generalizability of our findings. However, this model allowed us to conduct the study in a laboratory relatively untouched by other cointerventions. Furthermore, the use of PAs in this way may become more common as both academic and community hospitals rely more on mid‐level providers. Our study had a relatively low percentage of patients without a known diagnosis of diabetes compared with other studies, again potentially but not necessarily limiting generalizability. This finding has been shown in other studies at our institution24 and may be due to the high rate of screening for diabetes in the community. Another limitation is that this was a nonrandomized, before‐after trial. However, all subjects were prospectively enrolled to improve comparability, and we performed rigorous adjustment for multiple potential confounding factors. Also, this study had limited statistical power to detect differences in hypoglycemia rates. The preintervention arm was smaller than planned due to fewer diabetic patients than expected on the service and a higher number of exclusions; we prolonged the postintervention period to achieve the desired sample size for that arm of the study.

Our study also has several strengths, including electronic capture of many processes of care and a methodology to operationalize them into measures of protocol adherence. Our metrics of glycemic control were rigorously designed and based on a national task force on inpatient glycemic control sponsored by the Society of Hospital Medicine, with representation from the ADA and AACE.25

Potential future improvements to this intervention include modifications to the daily adjustment algorithm to improve its usability and ability to improve glucose control. Another is the use of high‐reliability methods to improve order set use and daily insulin adjustment, including alerts within the CPOE system and nurse empowerment to contact medical teams if glucose levels are out of range (eg, if greater than 180 mg/dL, not just if greater than 350 or 400 mg/dL). Future research directions include multicenter, randomized controlled trials of these types of interventions and an analysis of more distal patient outcomes including total healthcare utilization, infection rates, end‐organ damage, and mortality.

In conclusion, we found a relationship between a relatively low‐cost quality improvement intervention and improved glycemic control in the non‐ICU general medical setting. Such a finding suggests the benefits of the algorithm itself to improve glucose control and of our implementation strategy. Other institutions may find this intervention a useful starting point for their own quality improvement efforts. Both the algorithm and implementation strategy are deserving of further improvements and future study.

Diabetes mellitus and/or inpatient hyperglycemia are common comorbid conditions in hospitalized patients. Recent surveys show that over 90% of hospitalized diabetic patients experience hyperglycemia (>200 mg/dL), and in nearly 1 in 5 of these patients hyperglycemia persists for 3 days or more.1 Hyperglycemia among inpatients without a previous history of diabetes mellitus is also very common.2 Observational studies have shown that hyperglycemia in hospitalized patients is associated with adverse outcomes including infectious complications, increased length of stay, and increased mortality.27 Recent randomized controlled trials have demonstrated that aggressive treatment of inpatient hyperglycemia improves outcomes in surgical and medical intensive care units.8, 9

Based on the available data, the American Diabetes Association (ADA) now advocates good metabolic control, defined as preprandial glucose levels of 90 to 130 mg/dL and peak postprandial glucose levels <180 mg/dL in hospitalized nonintensive care unit (ICU) patients.10 To reach these targets, the ADA and American College of Endocrinology (ACE) suggest that multidisciplinary teams develop and implement hyperglycemia management guidelines and protocols.11 Protocols should promote the use of continuous intravenous insulin infusions or scheduled basal‐bolus subcutaneous insulin regimens. Subcutaneous insulin protocols should include target glucose levels, basal, nutritional, and supplemental insulin, and daily dose adjustments.6 A recent randomized controlled trial of non‐ICU inpatients demonstrated that such a basal‐bolus insulin regimen results in improved glucose control compared with a sliding scale only regimen.12

To date, few published studies have investigated the best ways to implement such management protocols; those that have are often resource‐intensive, for example involving daily involvement of nurse practitioners or diabetologists.13, 14 It is therefore not known how best to implement an inpatient diabetes management program that is effective, efficient, and self‐perpetuating. At Brigham and Women's Hospital (BWH), we have been refining a subcutaneous insulin protocol, focused provider education, and more recently a computerized order set to overcome barriers related to fear of hypoglycemia, delays in insulin prescribing, and unfamiliarity with inpatient glucose management.15 The aims of this current trial were to evaluate the effects of these interventions on a geographically localized general medical service previously naive to these interventions to evaluate their effects on glycemic control, patient safety, and processes of care. We hypothesized that these interventions would improve glycemic control and increase use of basal‐bolus insulin orders without increasing the rate of hypoglycemia.

METHODS

RESULTS

We prospectively identified 248 potential patients for the study. We subsequently excluded 79 patients for the following reasons: no glucose readings beyond hospital day 1 while on PACE service (34 patients); never admitted to PACE service (15 patients); no diabetes or inpatient hyperglycemia (9 patients, mostly patients prescribed an insulin sliding scale prophylactically to avoid steroid‐induced hyperglycemia); type 1 diabetes (13 patients); TPN, DKA, or HHS (5 patients); and palliative care (3 patients). The remaining 169 patients included 63 from the preintervention period(out of 489 total admissions to the PACE service; 13%) and 106 patients in the postintervention period (out of 565 admissions; 19%). These patients had 2447 glucose readings, or an average of 3.6 glucose readings per monitored patient‐day in the preintervention period and 3.3 glucose readings per patient‐day in the postintervention period. Even including the 34 patients who were excluded for lack of glucose readings, glucose data were still available for 717 out of a potential 775 patient‐days (93%). Characteristics for all included patients are shown in Table 2. The mean admission glucose was 197 mg/dL, mean A1C was 8.4%, 54% of the patients were prescribed insulin prior to admission, and 7% had no prior diagnosis of diabetes. There were no significant differences in baseline characteristics between the 2 patient groups except for Charlson score, which was higher in the preintervention group (87% versus 74% with score 2 or higher; Table 2). The top diagnosis‐related groups for the entire cohort included: heart failure and shock (12 patients); kidney and urinary tract infections (12 patients); esophagitis, gastroenteritis, and miscellaneous digestive disorders (11 patients); chronic obstructive pulmonary disease (10 patients); renal failure (10 patients); simple pneumonia and pleurisy (7 patients); disorders of the pancreas except malignancy (6 patients); chest pain (5 patients); and cellulitis (5 patients).

With respect to insulin ordering practices, there was no significant difference in the use of basal insulin in hyperglycemic patients between the preintervention period and postintervention period (81% versus 91%; P = 0.17), nor in the dose of basal insulin prescribed (results not shown), but there was an increase in the use of scheduled nutritional insulin for those patients with hyperglycemia receiving nutrition: 40% versus 75%, P < 0.001 (Table 3). The percent of patients receiving supplemental (sliding scale) insulin by itself (ie, without ever receiving basal or nutritional insulin) was lower during the postintervention period (29% versus 8%, P < 0.001). Nonsignificant differences were seen in the rates of prescribing an appropriate dose and type of nutritional insulin. Notably, there was no difference at all in the proportion of patient‐days in which insulin adjustments were made when 2 or more episodes of hyperglycemia or hypoglycemia were present during the previous day (56% of patient‐days in both groups; P = 0.90).

The primary outcome, the mean percent of glucose readings between 60 and 180 mg/dL per patient, was 59.1% in the preintervention period and 64.7% in the postintervention (P = 0.13 in unadjusted analysis; Table 3). When adjusted for A1C, admission glucose, and insulin use prior to admission, the adjusted absolute difference in the percent of glucose readings within range was 9.7% (95% confidence interval [CI], 0.6%‐18.8%; P = 0.04; Table 3). Regarding other measures of glucose control, the patient‐day weighted mean glucose was 174.7 mg/dL in the preintervention period and 164.6 mg/dL postintervention (P = 0.02), and there was no significant difference in the percent of patient‐days with any hypoglycemia (glucose <60 mg/dL) or severe hypoglycemia (glucose <40 mg/dL; Table 3). There were also no significant differences in the mean number of hypoglycemic events per patient‐day (6.8 versus 6.6 per 100 patient‐days; relative risk, 0.95; 95% CI, 0.541.67; P = 0.87) or severe hypoglycemic events per patient‐day (1.0 versus 1.4 per 100 patient‐days; relative risk, 1.38; 95% CI, 0.355.53; P = 0.65).

We also compared hospital length of stay in hours between the study groups (Table 3). Length of stay (LOS) was shorter in the postintervention arm in unadjusted analyses (112 versus 86 hours; P < 0.001), and this difference persisted when adjusted for patient insurance, race, gender, and Charlson comorbidity score (25% shorter; 95% CI, 6%‐44%). A comparison of LOS among nonstudy patients on the PACE service during these 2 time periods revealed no difference (105 versus 101 hours). When the length of stay analysis was limited to study patients with a known diagnosis of diabetes, the adjusted effect size was a 31% relative decrease in length of stay.

Figure 1A shows the percent glucose readings within range per patient by hospital day. The greatest differences between groups can be seen on hospital days 2 and 3 (11% absolute differences on both days). Similarly, Figure 1B shows the mean glucose per patient by hospital day. Again, the biggest differences are seen on hospital days 2 and 3 (20 and 23 mg/dL difference between groups, respectively). In both cases, only the day 3 comparisons were significantly different between study groups.

Figure 1

DISCUSSION

In this before‐after study, we found that a multifaceted intervention consisting of a subcutaneous insulin protocol, focused education, and an order set built into the hospital's CPOE system was associated with a significantly higher percentage of glucose readings within range per patient in analyses adjusted for patient demographics and severity of diabetes. We also found a significant decrease in patient‐day weighted mean glucose, a marked increase in appropriate use of scheduled nutritional insulin, and a concomitant decrease in sliding scale insulin only regimens during the postintervention period. Moreover, we found a shorter length of stay during the postintervention period that persisted after adjustment for several clinical factors. Importantly, the interventions described in this study require very few resources to continue indefinitely: printing costs for the management protocol, 4 hours of education delivered per year, and routine upkeep of an electronic order set.

Because this was a before‐after study, we cannot exclude the possibility that these improvements in process and outcome were due to cointerventions and/or temporal trends. However, we know of no other interventions aimed at improving diabetes care in this self‐contained service of nurses, PAs, and hospitalists. Moreover, the process improvements, especially the increase in scheduled nutritional insulin, were rather marked, unlikely to be due to temporal trends alone, and likely capable of producing the corresponding improvements in glucose control. That glucose control stopped improving after hospital day 3 may be due to the fact that subsequent adjustment to insulin orders occurred infrequently and no more often than prior to the intervention. That we did not see greater improvements in glycemic control overall may also reflect the fact that 81% of study patients with inpatient hyperglycemia received basal insulin prior to the intervention.

The reduction in patient LOS was somewhat surprising given the relatively small sample size. However, the results are consistent with those of other studies linking hyperglycemia to LOS18, 19 and we found no evidence for a temporal trend toward lower LOS on the PACE service as a whole during the same time period. While a greater proportion of patients on the PACE service were in the study in the post‐intervention period compared with the preintervention period, we found no evidence that the difference in length of stay was due to increased surveillance for nondiabetics, especially because eligibility criteria depended on phlebotomy glucose values, which were uniformly tested in all inpatients. Also, effects on length of stay were actually stronger when limited to patients with known diabetes. Finally, we controlled for several predictors of length of stay, although we still cannot exclude the possibility of unmeasured confounding between groups.

Since ADA and ACE issued guidelines for inpatient management of diabetes and hyperglycemia, many institutions have developed subcutaneous insulin algorithms, educational curricula, and/or order sets to increase compliance with these guidelines and improve glycemic control. Some of these efforts have been studied and some have been successful in their efforts.13, 14, 2023 Unfortunately, most of these programs have not rigorously assessed their impact on process and outcomes, and the most effective studies published to date have involved interventions much more intensive than those described here. For example, Rush University's intervention was associated with a 50 mg/dL decrease in mean blood glucose but involved an endocrinologist rounding twice daily with house officers for 2 weeks at a time.13 At Northwestern University, a diabetes management service run by nurse practitioners was established, and the focus was on the conversion from intravenous to subcutaneous insulin regimens.14 The RABBIT 2 study that demonstrated the benefits of a basal‐bolus insulin regimen used daily rounding with an endocrinologist.12 More modestly, a program in Pitt County Memorial Hospital in Greenville, NC, relied mostly on diabetes nurse case managers, a strategy which reduced hospital‐wide mean glucose levels as well as LOS, although the greatest improvements in glycemic control were seen in the ICU.19 Our findings are much more consistent with those from University of California San Diego, as yet unpublished, which also used an algorithm, computerized order set, education, as well as continuous quality improvement methods to achieve its aims.22

Our study has several limitations, including being conducted on 1 general medicine service at 1 academic medical center. Moreover, this service, using a physician assistant/hospitalist model, a closed geographic unit, and fairly generous staffing ratio, is likely different from those in many settings and may limit the generalizability of our findings. However, this model allowed us to conduct the study in a laboratory relatively untouched by other cointerventions. Furthermore, the use of PAs in this way may become more common as both academic and community hospitals rely more on mid‐level providers. Our study had a relatively low percentage of patients without a known diagnosis of diabetes compared with other studies, again potentially but not necessarily limiting generalizability. This finding has been shown in other studies at our institution24 and may be due to the high rate of screening for diabetes in the community. Another limitation is that this was a nonrandomized, before‐after trial. However, all subjects were prospectively enrolled to improve comparability, and we performed rigorous adjustment for multiple potential confounding factors. Also, this study had limited statistical power to detect differences in hypoglycemia rates. The preintervention arm was smaller than planned due to fewer diabetic patients than expected on the service and a higher number of exclusions; we prolonged the postintervention period to achieve the desired sample size for that arm of the study.

Our study also has several strengths, including electronic capture of many processes of care and a methodology to operationalize them into measures of protocol adherence. Our metrics of glycemic control were rigorously designed and based on a national task force on inpatient glycemic control sponsored by the Society of Hospital Medicine, with representation from the ADA and AACE.25

Potential future improvements to this intervention include modifications to the daily adjustment algorithm to improve its usability and ability to improve glucose control. Another is the use of high‐reliability methods to improve order set use and daily insulin adjustment, including alerts within the CPOE system and nurse empowerment to contact medical teams if glucose levels are out of range (eg, if greater than 180 mg/dL, not just if greater than 350 or 400 mg/dL). Future research directions include multicenter, randomized controlled trials of these types of interventions and an analysis of more distal patient outcomes including total healthcare utilization, infection rates, end‐organ damage, and mortality.

In conclusion, we found a relationship between a relatively low‐cost quality improvement intervention and improved glycemic control in the non‐ICU general medical setting. Such a finding suggests the benefits of the algorithm itself to improve glucose control and of our implementation strategy. Other institutions may find this intervention a useful starting point for their own quality improvement efforts. Both the algorithm and implementation strategy are deserving of further improvements and future study.

Is hospital medicine a bona fide specialty? Do something long enough, and as Justice Potter Stewart said when defining a certain taboo carnal subject many years ago, I know it when I see it. Although working groups may struggle to conceive a master set of core competencies for hospitalists, I will tell you this: no texts are needed, and you know that you are on to something when 2 hospitalists practicing 3000 miles apart shoot each other a knowing glance and, without words, just understand what the other is thinking. After 10 years of practice in several hospitals, I have had enough mind melds to last a lifetime. Who needs science after all? I mean, how many of us can keep a straight face when asked if we have ever heard this line: Ah, yes, Dr. Flansbaum, umm, I am Dr. Smith from the surgical ICU, and we have a patient hospital day 34 status post Whipple that is no longer surgically active. See, you are smiling already. Do I have to finish the sentence for you?

What follows is a collective experience of things that I call the grind: things so small, so inconsequential, that no one will ever cite them individually as the deal breakers of the day. Collectively, they are the fabric of who we are and that little sore on the inside of our cheek that we just have to touch every few minutes in order to remind ourselves of why dermatologists always look so happy. Any accompanying sage lessons are also free of charge.

• 1

  Why at the end of the day, always on a weekend after you have found a comfortable seat as far away from the nurse's station as possible, do you open up the chart and see 1 line of open space left on the last page of the progress notepaper? Even better, why is the note above it a follow‐up from vascular surgery, written in font size 24, in a form of Sanskrit that not even Steven Hawkings would recognize?

• 2

  Okay, how about this: For patients with loooong lengths of stay, how many creative ways can you write Awaiting placement, afebrile, no complaints (in compliance with billing rules of course)? The correct answer is between 16 and 23. A thesaurus helps for word number 1try stable to startand change your pen from fine point to medium point on odd days. Then add tolerated breakfast on Monday, lunch on Tuesday, and dinner on Wednesday. Voila! Who said this was tough?

• 3

  Okay, this one boggles my mind. You wish to auscultate a set of lungs. The patient is sitting on his gown. You attempt to lift the gown, and instead of raising his tush, the patient continues to sit while you tug away. Is this just me? It happens every week.

• 4

  The medical students are great. They are ambitious and make teaching fun. Why though, at 9:59 _AM, with an upcoming meeting with your chief at 10, are there no PC terminals at the station available except for the MSIII on MySpace.com with the chart you could not find (for 5 minutes) underneath his clipboard? Yes, Virginia, make me remember those days.

• 5

  Clearly, this is one of the more helpful lines you can get from a consult: Patient needs to be medically optimized, and consider head MRI. Consider? Is not that why I called the consult in the first place? Let us consider not to use the word consider any more. Consider that. I feel better.

• 6

  While we are on the topic of consultants, a dollar goes to you if this has never happened during your time on the wards: (1) the consultant visits, (2) the consultant evaluates, (3) you speak with the consultant, (4) all of you agree that the patient can go home, and (5) you then read the consult after the patient is dressed and his IV is out. Umm, a head CT before discharge and please have the neurosurgery clear the patient before discharge? Am I working in a parallel universe? Too much caffeine? Lord, give me strength.

• 7

  Your beeper goes off at 2:57 _PM. At 2:57 _PM plus 5 seconds, you call the number you were paged from and no one answers. Does the word ponderous come to mind? This invariably happens every day, of course, typically when I am in the midst of multitasking 4 conversations. However, I extract some form of perverse cosmic revenge when I need to make a call and pick up an open extension from a ringing multiline phone. Invariably, I click the button to engage a line and, oops, good bye caller. I am only kidding; that never happens (is my nose really growing?). Just think, I could have been the one screaming, Is Laverne here?

• 8

  You get an admission, a patient whom you have never met, and his room is listed as 428. You walk in, and the patient nearest to you is a well‐groomed middle‐age individual with a welcoming smile. The patient next to him is breathing fire, screaming at an imaginary executioner, and claiming that you are the guilty party and need to die. Which patient do you think is yours?

• 9

  Those of you who work with housestaff will appreciate this one (file it under systems issue: fix next week): You have a discussion with a patient regarding his _PM discharge at 11 _AM. You arrange the follow‐up, you review the new medications, you discuss who will pick him up after dinner, and so forth. You get that warm and fuzzy feeling that you have done your job and all is right in the universe. Naturally, you also tell the resident that the patient can go home. Lo and behold, you look at your census the following morning, and the name of the aforementioned patient radiates like a beacon from the screen. You then poke your head into the room, feeling assured that it is merely an error, and the aforementioned patient is lying in bed, smiling and happy to see you. You ask, What happened? The reply, I don't know. Didn't your son come last night to pick you up? The response is yes. After the penetrating ulcer in your stomach bores a little deeper, you discover the official discharge order did not occur, and the patient was content eating chipped beef and sleeping on said contoured mattress 1 more night. Serenity now, serenity now.

• 10

  The fifth vital sign? Is that the new black? Heck, number 5, I think we are up to 11 or 12 these days. Need a new metric installed? You guessed it: add it to the list!

• 11

  Do you ever get LOS fatigue with a particular patient that is so severe you go to bed the previous night and have problems falling asleep? Really, what do you say to a person when his hospital stay exceeds, say, 5 months? Yes, I actually think of topics and issues that I can incorporate into the conversation which will spice up the relationship. New bed sheets, a fresh coat of paint? It would make a good Seinfeld episode, no?

• 12

  Is it me, or is having 2 patients in the same room like being a flight attendant wheeling around the beverage cart? Get one the peanuts, and then the other wants the pretzels. For sure, add 10 minutes to your time in room 728 tomorrow.

• 13

  If a patient is unable to leave the hospital for reasons unrelated to discharge planning (locked out of his house, the child is out of town until the next morning, etc.), why do I feel so naughty when I get off the phone with the MCO medical director after offering explanations? I do not get it. You think that the hospital employs a battery of runners to padlock homes and steal patient's clothing. Who wrote this playbook?

• 14

  I love my consultants. Really, I do. I am not picking on them today. The high points of my day are the exchanges that I have with my subspecialty colleagues. However, the myopia that pervades some sign off notes give me pause. For example, a patient admitted for gastrointestinal bleed, s/p EGD, and stable at 72 hours post arrival receives a consultant note as follows: if patient eating and ambulating, can be discharged home as per PMD. Surely, when the level of transferred oversight shifts to the level of caloric ingestion and sneaker use, well, let us just say that I am all for some new E&M codes. They did not tell me about this in hospitalist school.

• 15

  Don't you love the feeling of your beeper going off, and 30 seconds after the first page, boom, it goes off againboth to the same extension? I mean really, I am a nice guy, but do you really want to rile me up this early in the morning?

• 16

  The nurse pages you from 1 floor away10 seconds from where you are standing. You recognize that number, you knew that it was coming, and for sure, waiting on the other end is that family member who hails from a foreboding place. How quickly does your brain do the computationdo I use the phone and let my fingers do the talking, or make that stroll and have that face‐to‐face summit? No sarcastic comment is needed. I see us now, hands joined, joyfully singing Kumbaya in a loving embrace.

• 17

  Gee, it is not busy today. Say that on the wards and you get a leering glance. However, say that in the emergency room and you will meet your death. There is something about that phrase and the emergency department. The nurses there do not forget, although a Starbucks cappuccino does put a nice salve on the wound.

• 18

  On your day off, do you ever notice that your beeper vibrates on your belt and you are not wearing it? I am not kidding.

• 19

  An irony of life: I have developed an immunity to cigarette smoke in hospital bathrooms. Why is that? It is like peanut butter and jelly. They just seem so happy together.

• 20

  Do you want to transfer that patient to psychiatry? No, no, no, you silly hospitalistdid you not notice that abnormal BUN and atypical lymphocyte on the peripheral smear? Hey, Dr. Freud, can you write me for some of that Prozac too!

• 21

  We need to consult a rulebook on chair ownership. Did you ever notice (a tinge of Andy Rooney here) that case managers own their seats? I know that the world is not quite right when a case manager shoots me that dastardly glare, as if to say, Flee, you silly physician, I live at this station, you are merely my guest! As far as that chair is concerned, perhaps if a small plaque is added to the backrest with a suitable donation, my legs will finally get their deserved daily rest.

• 22

  Finally, do you want to become invisible? Go to the reading board and stand behind a radiologist at 10:30 _AM. Do it long enough, and after a few days, you will be saying I'm Good Enough, I'm Smart Enough, and Doggone It, People Like Me! Do you want to disappear completely? Try it on a Friday.

Okay, okay, I will stop there. It is funny, though; this stuff really happens. Despite the aggravation, I see these commonalities as the glue that binds us, assists in building the esprit de corps in our profession, and adds a little levity to the work place. Outside the hospital (not inside, of course), I can confidently state that these routines are part of who I am. After all, it is all about the knowing glance that I mentioned previously. The humorous part is that we are certainly on someone else's list. Probably a nurse, an emergency room doctor, or maybe a physician's assistant is scribing away at this minute, and we are number 7: Those hospitalists really tick me off.

EPILOGUE

Note to selflook in the mirror occasionally; you might learn something.

I apologize to all my nonhospitalist colleagues if you sneered. I love all of you. Today.

Is hospital medicine a bona fide specialty? Do something long enough, and as Justice Potter Stewart said when defining a certain taboo carnal subject many years ago, I know it when I see it. Although working groups may struggle to conceive a master set of core competencies for hospitalists, I will tell you this: no texts are needed, and you know that you are on to something when 2 hospitalists practicing 3000 miles apart shoot each other a knowing glance and, without words, just understand what the other is thinking. After 10 years of practice in several hospitals, I have had enough mind melds to last a lifetime. Who needs science after all? I mean, how many of us can keep a straight face when asked if we have ever heard this line: Ah, yes, Dr. Flansbaum, umm, I am Dr. Smith from the surgical ICU, and we have a patient hospital day 34 status post Whipple that is no longer surgically active. See, you are smiling already. Do I have to finish the sentence for you?

What follows is a collective experience of things that I call the grind: things so small, so inconsequential, that no one will ever cite them individually as the deal breakers of the day. Collectively, they are the fabric of who we are and that little sore on the inside of our cheek that we just have to touch every few minutes in order to remind ourselves of why dermatologists always look so happy. Any accompanying sage lessons are also free of charge.

• 1

  Why at the end of the day, always on a weekend after you have found a comfortable seat as far away from the nurse's station as possible, do you open up the chart and see 1 line of open space left on the last page of the progress notepaper? Even better, why is the note above it a follow‐up from vascular surgery, written in font size 24, in a form of Sanskrit that not even Steven Hawkings would recognize?

• 2

  Okay, how about this: For patients with loooong lengths of stay, how many creative ways can you write Awaiting placement, afebrile, no complaints (in compliance with billing rules of course)? The correct answer is between 16 and 23. A thesaurus helps for word number 1try stable to startand change your pen from fine point to medium point on odd days. Then add tolerated breakfast on Monday, lunch on Tuesday, and dinner on Wednesday. Voila! Who said this was tough?

• 3

  Okay, this one boggles my mind. You wish to auscultate a set of lungs. The patient is sitting on his gown. You attempt to lift the gown, and instead of raising his tush, the patient continues to sit while you tug away. Is this just me? It happens every week.

• 4

  The medical students are great. They are ambitious and make teaching fun. Why though, at 9:59 _AM, with an upcoming meeting with your chief at 10, are there no PC terminals at the station available except for the MSIII on MySpace.com with the chart you could not find (for 5 minutes) underneath his clipboard? Yes, Virginia, make me remember those days.

• 5

  Clearly, this is one of the more helpful lines you can get from a consult: Patient needs to be medically optimized, and consider head MRI. Consider? Is not that why I called the consult in the first place? Let us consider not to use the word consider any more. Consider that. I feel better.

• 6

  While we are on the topic of consultants, a dollar goes to you if this has never happened during your time on the wards: (1) the consultant visits, (2) the consultant evaluates, (3) you speak with the consultant, (4) all of you agree that the patient can go home, and (5) you then read the consult after the patient is dressed and his IV is out. Umm, a head CT before discharge and please have the neurosurgery clear the patient before discharge? Am I working in a parallel universe? Too much caffeine? Lord, give me strength.

• 7

  Your beeper goes off at 2:57 _PM. At 2:57 _PM plus 5 seconds, you call the number you were paged from and no one answers. Does the word ponderous come to mind? This invariably happens every day, of course, typically when I am in the midst of multitasking 4 conversations. However, I extract some form of perverse cosmic revenge when I need to make a call and pick up an open extension from a ringing multiline phone. Invariably, I click the button to engage a line and, oops, good bye caller. I am only kidding; that never happens (is my nose really growing?). Just think, I could have been the one screaming, Is Laverne here?

• 8

  You get an admission, a patient whom you have never met, and his room is listed as 428. You walk in, and the patient nearest to you is a well‐groomed middle‐age individual with a welcoming smile. The patient next to him is breathing fire, screaming at an imaginary executioner, and claiming that you are the guilty party and need to die. Which patient do you think is yours?

• 9

  Those of you who work with housestaff will appreciate this one (file it under systems issue: fix next week): You have a discussion with a patient regarding his _PM discharge at 11 _AM. You arrange the follow‐up, you review the new medications, you discuss who will pick him up after dinner, and so forth. You get that warm and fuzzy feeling that you have done your job and all is right in the universe. Naturally, you also tell the resident that the patient can go home. Lo and behold, you look at your census the following morning, and the name of the aforementioned patient radiates like a beacon from the screen. You then poke your head into the room, feeling assured that it is merely an error, and the aforementioned patient is lying in bed, smiling and happy to see you. You ask, What happened? The reply, I don't know. Didn't your son come last night to pick you up? The response is yes. After the penetrating ulcer in your stomach bores a little deeper, you discover the official discharge order did not occur, and the patient was content eating chipped beef and sleeping on said contoured mattress 1 more night. Serenity now, serenity now.

• 10

  The fifth vital sign? Is that the new black? Heck, number 5, I think we are up to 11 or 12 these days. Need a new metric installed? You guessed it: add it to the list!

• 11

  Do you ever get LOS fatigue with a particular patient that is so severe you go to bed the previous night and have problems falling asleep? Really, what do you say to a person when his hospital stay exceeds, say, 5 months? Yes, I actually think of topics and issues that I can incorporate into the conversation which will spice up the relationship. New bed sheets, a fresh coat of paint? It would make a good Seinfeld episode, no?

• 12

  Is it me, or is having 2 patients in the same room like being a flight attendant wheeling around the beverage cart? Get one the peanuts, and then the other wants the pretzels. For sure, add 10 minutes to your time in room 728 tomorrow.

• 13

  If a patient is unable to leave the hospital for reasons unrelated to discharge planning (locked out of his house, the child is out of town until the next morning, etc.), why do I feel so naughty when I get off the phone with the MCO medical director after offering explanations? I do not get it. You think that the hospital employs a battery of runners to padlock homes and steal patient's clothing. Who wrote this playbook?

• 14

  I love my consultants. Really, I do. I am not picking on them today. The high points of my day are the exchanges that I have with my subspecialty colleagues. However, the myopia that pervades some sign off notes give me pause. For example, a patient admitted for gastrointestinal bleed, s/p EGD, and stable at 72 hours post arrival receives a consultant note as follows: if patient eating and ambulating, can be discharged home as per PMD. Surely, when the level of transferred oversight shifts to the level of caloric ingestion and sneaker use, well, let us just say that I am all for some new E&M codes. They did not tell me about this in hospitalist school.

• 15

  Don't you love the feeling of your beeper going off, and 30 seconds after the first page, boom, it goes off againboth to the same extension? I mean really, I am a nice guy, but do you really want to rile me up this early in the morning?

• 16

  The nurse pages you from 1 floor away10 seconds from where you are standing. You recognize that number, you knew that it was coming, and for sure, waiting on the other end is that family member who hails from a foreboding place. How quickly does your brain do the computationdo I use the phone and let my fingers do the talking, or make that stroll and have that face‐to‐face summit? No sarcastic comment is needed. I see us now, hands joined, joyfully singing Kumbaya in a loving embrace.

• 17

  Gee, it is not busy today. Say that on the wards and you get a leering glance. However, say that in the emergency room and you will meet your death. There is something about that phrase and the emergency department. The nurses there do not forget, although a Starbucks cappuccino does put a nice salve on the wound.

• 18

  On your day off, do you ever notice that your beeper vibrates on your belt and you are not wearing it? I am not kidding.

• 19

  An irony of life: I have developed an immunity to cigarette smoke in hospital bathrooms. Why is that? It is like peanut butter and jelly. They just seem so happy together.

• 20

  Do you want to transfer that patient to psychiatry? No, no, no, you silly hospitalistdid you not notice that abnormal BUN and atypical lymphocyte on the peripheral smear? Hey, Dr. Freud, can you write me for some of that Prozac too!

• 21

  We need to consult a rulebook on chair ownership. Did you ever notice (a tinge of Andy Rooney here) that case managers own their seats? I know that the world is not quite right when a case manager shoots me that dastardly glare, as if to say, Flee, you silly physician, I live at this station, you are merely my guest! As far as that chair is concerned, perhaps if a small plaque is added to the backrest with a suitable donation, my legs will finally get their deserved daily rest.

• 22

  Finally, do you want to become invisible? Go to the reading board and stand behind a radiologist at 10:30 _AM. Do it long enough, and after a few days, you will be saying I'm Good Enough, I'm Smart Enough, and Doggone It, People Like Me! Do you want to disappear completely? Try it on a Friday.

Okay, okay, I will stop there. It is funny, though; this stuff really happens. Despite the aggravation, I see these commonalities as the glue that binds us, assists in building the esprit de corps in our profession, and adds a little levity to the work place. Outside the hospital (not inside, of course), I can confidently state that these routines are part of who I am. After all, it is all about the knowing glance that I mentioned previously. The humorous part is that we are certainly on someone else's list. Probably a nurse, an emergency room doctor, or maybe a physician's assistant is scribing away at this minute, and we are number 7: Those hospitalists really tick me off.

EPILOGUE

Note to selflook in the mirror occasionally; you might learn something.

I apologize to all my nonhospitalist colleagues if you sneered. I love all of you. Today.

Is hospital medicine a bona fide specialty? Do something long enough, and as Justice Potter Stewart said when defining a certain taboo carnal subject many years ago, I know it when I see it. Although working groups may struggle to conceive a master set of core competencies for hospitalists, I will tell you this: no texts are needed, and you know that you are on to something when 2 hospitalists practicing 3000 miles apart shoot each other a knowing glance and, without words, just understand what the other is thinking. After 10 years of practice in several hospitals, I have had enough mind melds to last a lifetime. Who needs science after all? I mean, how many of us can keep a straight face when asked if we have ever heard this line: Ah, yes, Dr. Flansbaum, umm, I am Dr. Smith from the surgical ICU, and we have a patient hospital day 34 status post Whipple that is no longer surgically active. See, you are smiling already. Do I have to finish the sentence for you?

What follows is a collective experience of things that I call the grind: things so small, so inconsequential, that no one will ever cite them individually as the deal breakers of the day. Collectively, they are the fabric of who we are and that little sore on the inside of our cheek that we just have to touch every few minutes in order to remind ourselves of why dermatologists always look so happy. Any accompanying sage lessons are also free of charge.

• 1

  Why at the end of the day, always on a weekend after you have found a comfortable seat as far away from the nurse's station as possible, do you open up the chart and see 1 line of open space left on the last page of the progress notepaper? Even better, why is the note above it a follow‐up from vascular surgery, written in font size 24, in a form of Sanskrit that not even Steven Hawkings would recognize?

• 2

  Okay, how about this: For patients with loooong lengths of stay, how many creative ways can you write Awaiting placement, afebrile, no complaints (in compliance with billing rules of course)? The correct answer is between 16 and 23. A thesaurus helps for word number 1try stable to startand change your pen from fine point to medium point on odd days. Then add tolerated breakfast on Monday, lunch on Tuesday, and dinner on Wednesday. Voila! Who said this was tough?

• 3

  Okay, this one boggles my mind. You wish to auscultate a set of lungs. The patient is sitting on his gown. You attempt to lift the gown, and instead of raising his tush, the patient continues to sit while you tug away. Is this just me? It happens every week.

• 4

  The medical students are great. They are ambitious and make teaching fun. Why though, at 9:59 _AM, with an upcoming meeting with your chief at 10, are there no PC terminals at the station available except for the MSIII on MySpace.com with the chart you could not find (for 5 minutes) underneath his clipboard? Yes, Virginia, make me remember those days.

• 5

  Clearly, this is one of the more helpful lines you can get from a consult: Patient needs to be medically optimized, and consider head MRI. Consider? Is not that why I called the consult in the first place? Let us consider not to use the word consider any more. Consider that. I feel better.

• 6

  While we are on the topic of consultants, a dollar goes to you if this has never happened during your time on the wards: (1) the consultant visits, (2) the consultant evaluates, (3) you speak with the consultant, (4) all of you agree that the patient can go home, and (5) you then read the consult after the patient is dressed and his IV is out. Umm, a head CT before discharge and please have the neurosurgery clear the patient before discharge? Am I working in a parallel universe? Too much caffeine? Lord, give me strength.

• 7

  Your beeper goes off at 2:57 _PM. At 2:57 _PM plus 5 seconds, you call the number you were paged from and no one answers. Does the word ponderous come to mind? This invariably happens every day, of course, typically when I am in the midst of multitasking 4 conversations. However, I extract some form of perverse cosmic revenge when I need to make a call and pick up an open extension from a ringing multiline phone. Invariably, I click the button to engage a line and, oops, good bye caller. I am only kidding; that never happens (is my nose really growing?). Just think, I could have been the one screaming, Is Laverne here?

• 8

  You get an admission, a patient whom you have never met, and his room is listed as 428. You walk in, and the patient nearest to you is a well‐groomed middle‐age individual with a welcoming smile. The patient next to him is breathing fire, screaming at an imaginary executioner, and claiming that you are the guilty party and need to die. Which patient do you think is yours?

• 9

  Those of you who work with housestaff will appreciate this one (file it under systems issue: fix next week): You have a discussion with a patient regarding his _PM discharge at 11 _AM. You arrange the follow‐up, you review the new medications, you discuss who will pick him up after dinner, and so forth. You get that warm and fuzzy feeling that you have done your job and all is right in the universe. Naturally, you also tell the resident that the patient can go home. Lo and behold, you look at your census the following morning, and the name of the aforementioned patient radiates like a beacon from the screen. You then poke your head into the room, feeling assured that it is merely an error, and the aforementioned patient is lying in bed, smiling and happy to see you. You ask, What happened? The reply, I don't know. Didn't your son come last night to pick you up? The response is yes. After the penetrating ulcer in your stomach bores a little deeper, you discover the official discharge order did not occur, and the patient was content eating chipped beef and sleeping on said contoured mattress 1 more night. Serenity now, serenity now.

• 10

  The fifth vital sign? Is that the new black? Heck, number 5, I think we are up to 11 or 12 these days. Need a new metric installed? You guessed it: add it to the list!

• 11

  Do you ever get LOS fatigue with a particular patient that is so severe you go to bed the previous night and have problems falling asleep? Really, what do you say to a person when his hospital stay exceeds, say, 5 months? Yes, I actually think of topics and issues that I can incorporate into the conversation which will spice up the relationship. New bed sheets, a fresh coat of paint? It would make a good Seinfeld episode, no?

• 12

  Is it me, or is having 2 patients in the same room like being a flight attendant wheeling around the beverage cart? Get one the peanuts, and then the other wants the pretzels. For sure, add 10 minutes to your time in room 728 tomorrow.

• 13

  If a patient is unable to leave the hospital for reasons unrelated to discharge planning (locked out of his house, the child is out of town until the next morning, etc.), why do I feel so naughty when I get off the phone with the MCO medical director after offering explanations? I do not get it. You think that the hospital employs a battery of runners to padlock homes and steal patient's clothing. Who wrote this playbook?

• 14

  I love my consultants. Really, I do. I am not picking on them today. The high points of my day are the exchanges that I have with my subspecialty colleagues. However, the myopia that pervades some sign off notes give me pause. For example, a patient admitted for gastrointestinal bleed, s/p EGD, and stable at 72 hours post arrival receives a consultant note as follows: if patient eating and ambulating, can be discharged home as per PMD. Surely, when the level of transferred oversight shifts to the level of caloric ingestion and sneaker use, well, let us just say that I am all for some new E&M codes. They did not tell me about this in hospitalist school.

• 15

  Don't you love the feeling of your beeper going off, and 30 seconds after the first page, boom, it goes off againboth to the same extension? I mean really, I am a nice guy, but do you really want to rile me up this early in the morning?

• 16

  The nurse pages you from 1 floor away10 seconds from where you are standing. You recognize that number, you knew that it was coming, and for sure, waiting on the other end is that family member who hails from a foreboding place. How quickly does your brain do the computationdo I use the phone and let my fingers do the talking, or make that stroll and have that face‐to‐face summit? No sarcastic comment is needed. I see us now, hands joined, joyfully singing Kumbaya in a loving embrace.

• 17

  Gee, it is not busy today. Say that on the wards and you get a leering glance. However, say that in the emergency room and you will meet your death. There is something about that phrase and the emergency department. The nurses there do not forget, although a Starbucks cappuccino does put a nice salve on the wound.

• 18

  On your day off, do you ever notice that your beeper vibrates on your belt and you are not wearing it? I am not kidding.

• 19

  An irony of life: I have developed an immunity to cigarette smoke in hospital bathrooms. Why is that? It is like peanut butter and jelly. They just seem so happy together.

• 20

  Do you want to transfer that patient to psychiatry? No, no, no, you silly hospitalistdid you not notice that abnormal BUN and atypical lymphocyte on the peripheral smear? Hey, Dr. Freud, can you write me for some of that Prozac too!

• 21

  We need to consult a rulebook on chair ownership. Did you ever notice (a tinge of Andy Rooney here) that case managers own their seats? I know that the world is not quite right when a case manager shoots me that dastardly glare, as if to say, Flee, you silly physician, I live at this station, you are merely my guest! As far as that chair is concerned, perhaps if a small plaque is added to the backrest with a suitable donation, my legs will finally get their deserved daily rest.

• 22

  Finally, do you want to become invisible? Go to the reading board and stand behind a radiologist at 10:30 _AM. Do it long enough, and after a few days, you will be saying I'm Good Enough, I'm Smart Enough, and Doggone It, People Like Me! Do you want to disappear completely? Try it on a Friday.

Okay, okay, I will stop there. It is funny, though; this stuff really happens. Despite the aggravation, I see these commonalities as the glue that binds us, assists in building the esprit de corps in our profession, and adds a little levity to the work place. Outside the hospital (not inside, of course), I can confidently state that these routines are part of who I am. After all, it is all about the knowing glance that I mentioned previously. The humorous part is that we are certainly on someone else's list. Probably a nurse, an emergency room doctor, or maybe a physician's assistant is scribing away at this minute, and we are number 7: Those hospitalists really tick me off.

EPILOGUE

Note to selflook in the mirror occasionally; you might learn something.

I apologize to all my nonhospitalist colleagues if you sneered. I love all of you. Today.

Diabetes has reached epidemic proportions in the United States, affecting over 20 million individuals,1 and further rises are expected. A disproportionate increase in diabetes has occurred in the inpatient setting.2 Furthermore, for every 2 patients in the hospital with known diabetes, there may be an additional 1 with newly observed hyperglycemia. Both are common. In 1 report, for example, 24% of inpatients with hyperglycemia had a prior diagnosis of diabetes, whereas another 12% had hyperglycemia without a prior diagnosis of diabetes.3

Although there is a paucity of high quality randomized controlled trials to support tight glycemic control in non‐critical care inpatient settings, poor glycemic control in hospitalized patients is strongly associated with undesirable outcomes for a variety of conditions, including pneumonia,4 cancer chemotherapy,5 renal transplant,6 and postsurgical wound infections.7, 8 Hyperglycemia also induces dehydration, fluid and electrolyte imbalance, gastric motility problems, and venous thromboembolism formation.9

Structured subcutaneous insulin order sets and insulin management protocols have been widely advocated as a method to encourage basal bolus insulin regimens and enhance glycemic control,2, 9, 10 but the effect of these interventions on glycemic control, hypoglycemia, and insulin use patterns in the real world setting has not been well reported. Fear of inducing hypoglycemia is often the main barrier for initiating basal insulin containing regimens and pursuing glycemic targets.2 The evidence would suggest, however, that sliding scale regimens, as opposed to more physiologic basal bolus regimens, may actually increase both hypoglycemic and hyperglycemic excursions.11 A convincing demonstration of the efficacy (improved insulin use patterns and reduced hyperglycemia) and safety (reduced hypoglycemia) of structured insulin order sets and insulin management protocols would foster a more rapid adoption of these strategies.

PATIENTS AND METHODS

In our 400‐bed university hospital, we formed a hospitalist‐led multidisciplinary team in early 2003, with the focus of improving the care delivered to non‐critical care patients with diabetes or hyperglycemia. We used a Plan‐Do‐Study‐Act (PDSA) performance improvement framework, and conducted institutional review board (IRB)‐approved prospective observational research in parallel with the performance improvement efforts, with a waiver for individual informed consent. The study population consisted of all adult inpatients on non‐critical care units with electronically reported point of care (POC) glucose testing from November 2002 through December 2005. We excluded patients who did not have either a discharge diagnosis of Diabetes (ICD 9 codes 250‐251.XX) or demonstrated hyperglycemia (fasting POC glucose >130 mg/dL 2, or a random value of >180 mg/dL) from analysis of glycemic control and hypoglycemia. Women admitted to Obstetrics were excluded. Monthly and quarterly summaries on glycemic control, hypoglycemia, and insulin use patterns (metrics described below) were reported to the improvement team and other groups on a regular basis throughout the intervention period. POC glucose data, demographics, markers of severity of illness, and diagnosis codes were retrieved from the electronic health record.

Interventions

We introduced several interventions and educational efforts throughout the course of our improvement. The 2 key interventions were as follows:

• Structured subcutaneous insulin order sets (November, 2003).

• An insulin management algorithm, described below (May 2005).

 

Key Intervention #1: Structured Subcutaneous Insulin Order Set Implementation

In November 2003, we introduced a paper‐based structured subcutaneous insulin order set. This order set encouraged the use of scheduled basal and nutritional insulin, provided guidance for monitoring glucose levels, and for insulin dosing. A hypoglycemia protocol and a standardized correction insulin table were embedded in the order set. This set was similar to examples of structured insulin ordering subsequently presented in the literature.9 In a parallel effort, the University of California, San Diego Medical Center (UCSDMC) was developing a computer physician order entry (CPOE) module for our comprehensive clinical information system, Invision (Siemens Medical Systems, Malvern, PA), that heretofore had primarily focused on result review, patient schedule management, and nursing documentation. In anticipation of CPOE and for the purpose of standardization, we removed outdated sliding scale insulin regimens from a variety preexisting order sets and inserted references to the standardized subcutaneous insulin order set in their stead. The medication administration record (MAR) was changed to reflect the basal/nutritional/correction insulin terminology. It became more difficult to order a stand‐alone insulin sliding scale even before CPOE versions became available. The standardized order set was the only preprinted correction scale insulin order available, and ordering physicians have to specifically opt out of basal and nutritional insulin choices to order sliding scale only regimens. Verbal orders for correction dose scales were deemed unacceptable by medical staff committees. Correctional insulin doses could be ordered as a 1‐time order, but the pharmacy rejected ongoing insulin orders that were not entered on the structured form.

We introduced our first standardized CPOE subcutaneous insulin order set in January 2004 at the smaller of our 2 campuses, and subsequently completed full deployment across both campuses in all adult medical‐surgical care areas by September 2004.

The CPOE version, like the paper version that immediately preceded it, encouraged the use of basal/bolus insulin regimens, promoted the terms basal, nutritional or premeal, and adjustment dose insulin in the order sets and the medication administration record, and was mandatory for providers wishing to order anything but a 1‐time order of insulin. Figure 1 depicts a screen shot of the CPOE version. Similar to the paper version, the ordering physician had to specifically opt out of ordering scheduled premeal and basal insulin to order a sliding scale only regimen. The first screen also ensured that appropriate POC glucose monitoring was ordered and endorsed a standing hypoglycemia protocol order. The CPOE version had only a few additional features not possible on paper. Obvious benefits included elimination of unapproved abbreviations and handwriting errors. Nutritional and correction insulin types were forced to be identical. Fundamentally, however, both the paper and online structured ordering experiences had the same degree of control over provider ordering patterns, and there was no increment in guidance for choosing insulin regimens, hence their combined analysis as structured orders.

Figure 1

Key Intervention #2: Insulin Management Algorithm

The structured insulin order set had many advantages, but also had many limitations. Guidance for preferred insulin regimens for patients in different nutritional situations was not inherent in the order set, and all basal and nutritional insulin options were offered as equally acceptable choices. The order set gave very general guidance for insulin dosing, but did not calculate insulin doses or assist in the apportionment of insulin between basal and nutritional components, and guidance for setting a glycemic target or adjusting insulin was lacking.

Recognizing these limitations, we devised an insulin management algorithm to provide guidance incremental to that offered in the order set. In April 2005, 3 hospitalists piloted a paper‐based insulin management algorithm (Figure 2, front; Figure 3, reverse) on their teaching services. This 1‐page algorithm provided guidance on insulin dosing and monitoring, and provided institutionally preferred insulin regimens for patients in different nutritional situations. As an example, of the several acceptable subcutaneous insulin regimens that an eating patient might use in the inpatient setting, we advocated the use of 1 preferred regimen (a relatively peakless, long‐acting basal insulin once a day, along with a rapid acting analog nutritional insulin with each meal). We introduced the concept of a ward glycemic target, provided prompts for diabetes education, and generally recommended discontinuation of oral hypoglycemic agents in the inpatient setting. The hospitalists were introduced to the concepts and the algorithm via 1 of the authors (G.M.) in a 1‐hour session. The algorithm was introduced on each teaching team during routine teaching rounds with a slide set (approximately 15 slides) that outlined the basic principles of insulin dosing, and gave example cases which modeled the proper use of the algorithm. The principles were reinforced on daily patient work rounds as they were applied on inpatients with hyperglycemia. The pilot results on 25 patients, compared to 250 historical control patients, were very promising, with markedly improved glycemic control and no increase in hypoglycemia. We therefore sought to spread the use of the algorithm. In May 2005 the insulin management algorithm and teaching slide set were promoted on all 7 hospitalist‐run services, and the results of the pilot and concepts of the algorithm were shared with a variety of house staff and service leaders in approximately a dozen sessions: educational grand rounds, assorted noon lectures, and subsequently, at new intern orientations. Easy access to the algorithm was assured by providing a link to the file within the CPOE insulin order set.

Figure 2

Figure 3

Other Attempts to Improve Care

Several other issues were addressed in the context of the larger performance improvement effort by the team. In many cases, hard data were not gathered to assess the effectiveness of the interventions, or the interventions were ongoing and could be considered the background milieu for the key interventions listed above.

During each intervention, education sessions were given throughout the hospital to staff, including physicians, residents, and nurses, using departmental grand rounds, nursing rounds, and in‐services to describe the process and goals. Patient education programs were also redesigned and implemented, using preprinted brochure. Front‐line nursing staff teaching skills were bolstered via Clinical Nurse Specialist educational sessions, and the use of a template for patient teaching. The educational template assessed patient readiness to learn, home environment, current knowledge, and other factors. Approximately 6 conferences directed at various physician staff per year became part of the regular curriculum.

We recognized that there was often poor coordination between glucose monitoring, nutrition delivery, and insulin administration. The traditional nursing practice of the 6:00 _AM finger stick and insulin administration was changed to match a formalized nutrition delivery schedule. Nutrition services and nursing were engaged to address timeliness of nutrition delivery, insulin administration, and POC glucose documentation in the electronic health record.

Feedback to individual medicine resident teams on reaching glycemic targets, with movie ticket/coffee coupon rewards to high performing teams, was tried from April 2004 to September 2004.

RESULTS

Just over 11,000 patients were identified for POC glucose testing over the 38 month observation period. Of these, 9314 patients had either a diagnosis of diabetes or documented hyperglycemia. The characteristics of this study population are depicted in Table 1. There were no differences between the groups and the demographics of age, gender, or length of stay (P > 0.05 for all parameters). There was a slight increase in the percent of patients with any intensive care unit days over the 3 time periods and a similar increase in the case mix index.

Of the 9314 study patients, 5530 had 8 or more POC glucose values, and were included in a secondary analysis of glycemic control and hypoglycemia.

Insulin Use Patterns

Figure 4 demonstrates the dramatic improvement that took place with the introduction of the structured order set. In the 6 months preceding the introduction of the structured insulin order set (May‐October 2003) 72% of 477 sampled patients with insulin orders were on sliding scale‐only insulin regimens (with no basal insulin), compared to just 26% of 499 patients sampled in the March to August 2004 time period subsequent to order set implementation (P < .0001, chi square statistic). Intermittent monthly checks on insulin use patterns reveal this change has been sustained.

Figure 4

Glycemic Control

A total of 9314 patients with 44,232 monitored patient‐days and over 120,000 POC glucose values were analyzed to assess glycemic control, which was improved with structured insulin orders and improved incrementally with the introduction of the insulin management algorithm.

The percent of patient‐days that were uncontrolled, defined as a monitored day with a mean glucose of 180 mg/dL, was reduced over the 3 time periods (37.8% versus 33.9% versus 30.1%, P < 0.005, Pearson chi square statistic), representing a 21% RR reduction of uncontrolled patient‐days from TP1 versus TP3. Table 2 shows the summary results for glycemic control, including the RR and CIs between the 3 time periods.

Table 2.Glycemic Control Summary for 9,314 Patients with a Diagnosis of Diabetes Mellitus or Documented Hyperglycemia

Time Period (TP)	Baseline	TP2 Structured Orders	TP3 Orders Plus Algorithm	Relative Risk TP3:TP2
* An uncontrolled patient‐day is defined as a monitored patient day with a mean glucose of 180 mg/dL. P value of <0.005. An uncontrolled patient‐stay is defined as a patient‐stay with a day‐weighted mean glucose value of 180 mg/dL.
Patient‐day glucose
Mean SD	179 66	170 65	165 58
Median	160	155	151
Uncontrolled patient‐days*	4,372	7,162	3,465
Monitored patient‐days	11,555	21,135	11,531
% Uncontrolled patient‐days	37.8	33.9	30.1
RR: uncontrolled patient‐day (95% confidence interval)	1.0	0.89 (0.87‐0.92)	0.79 (0.77‐0.82)	0.89 (0.86‐0.92)
Glycemic control by patient‐stay
Day‐weighted mean SD	177 57	174 54	170 50
Day‐weighted median	167	162	158
Uncontrolled patient‐stay (%)	1,038	1,696	784
Monitored patient‐stay	2,504	4,515	2,295
% Uncontrolled patient‐stays	41.5	37.6	34.2
RR: uncontrolled patient‐stay (95% confidence interval)		0.91 (0.85‐0.96)	0.84 (0.77‐0.89)	0.91 (0.85‐0.97)

In a similar fashion, the percent of patients with uncontrolled patient‐stays (day‐weighted mean glucose 180 mg/dL) was also reduced over the 3 time periods (41.5% versus 37.6% versus 34.2%, P < 0.05, Pearson chi square statistic, with an RR reduction of 16% for TP3:TP1). Figure 5 depicts a statistical process control chart of the percent of patients experiencing uncontrolled patient‐stays over time, and is more effective in displaying the temporal relationship of the interventions with the improved results.

Figure 5

Uncontrolled hyperglycemic days and stays were reduced incrementally from TP3 versus TP2, reflecting the added benefit of the insulin management algorithm, compared to the benefit enjoyed with the structured order set alone.

When the analyses were repeated after excluding patients with fewer than 8 POC glucose readings (Table 3), the findings were similar, but as predicted, the effect was slightly more pronounced, with a 23% relative reduction in uncontrolled patient‐days and a 27% reduction in uncontrolled patient‐stays of TP3 versus TP1.

Table 3.Glycemic Control Summary for 5530 Patients with a Diagnosis of Diabetes Mellitus or Documented Hyperglycemia and 8 POC Glucose Values Available

Time Period (TP)	Baseline	TP2 Structured Orders	TP3 Orders Plus Algorithm	Relative Risk TP3:TP2
* An uncontrolled patient‐day is defined as a monitored patient day with a mean glucose of 180 mg/dL. P value of <0.005. An uncontrolled patient‐stay is defined as a patient‐stay with a day‐weighted mean glucose value of 180 mg/dL.
Patient‐day glucose
Mean SD	172 65	169 64	163 57
Median	159	154	149
Uncontrolled patient‐days*	3,469	5,639	2,766
Monitored patient‐days	9,304	17,278	9,671
% Uncontrolled patient‐days	37.3	32.6	28.6
RR: uncontrolled patient‐day (95% confidence interval)	1.0	0.87 (0.85‐0.90)	0.77 (0.74‐0.80)	0.88 (0.84‐0.91)
Glycemic control by patient‐stay
Day‐weighted mean SD	175 51	169 47	166 45
Day‐weighted median	167	158	155
Uncontrolled patient‐stay (%)	588	908	425
Monitored patient‐stay	1,439	2,659	1,426
% Uncontrolled patient‐stays	40.1	34.1	29.8
RR: Uncontrolled patient‐stay (95% confidence interval)		0.84 (0.77‐0.91)	0.73 (0.66‐0.81)	0.87 (0.79‐0.96)