***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: People with diabetes are more likely to be hospitalized and to have longer duration s of hospital stay than those without diabetes . A recent survey estimated that 22 % of all hospital inpatient days were incurred by people with diabetes and that hospital inpatient care accounted for half of the 174 billion USD total U.S. medical expenditures for this disease ( 1 ) . These findings are due , in part , to the continued expansion of the worldwide epidemic of type 2 diabetes . In the U.S. alone , there are ∼1.6 million new cases of diabetes each year , with an over all prevalence of 23.6 million people ( 7.8 % of the population , with one-fourth of the cases remaining undiagnosed ) . An additional 57 million American adults are at high risk for type 2 diabetes ( 2 ) . Although the costs of illness-related stress hyperglycemia are not known , they are likely to be considerable in light of the poor prognosis of such patients ( 3–6 ) . There is substantial observational evidence linking hyperglycemia in hospitalized patients ( with or without diabetes ) to poor outcomes . Cohort studies as well as a few early r and omized controlled trials ( RCTs ) have suggested that intensive treatment of hyperglycemia improved hospital outcomes ( 5–8 ) . In 2004 , this evidence led the American College of Endocrinology ( ACE ) and the American Association of Clinical Endocrinologists ( AACE ) , in collaboration with the American Diabetes Association ( ADA ) and other medical organizations , to develop recommendations for treatment of inpatient hyperglycemia  ( 9 ) . In 2005 , the ADA added recommendations for treatment  of hyperglycemia in the hospitalto itsannual St and ards of Medical Care ( 10 ) . Recommendations from the ACE and the ADA generally endorsed tight glycemic control in critical care units . For patients in general medical and surgical units , where RCT evidence regarding treatment targets was lacking , glycemic goals similar to those advised for out patients were advocated ( 9 , BACKGROUND Glycemic control is important to patients ' outcomes . However , the process of maintaining glycemic control is risk laden and labor intensive for nurses . OBJECTIVES To examine the effects of using a computerized insulin dose calculator to facilitate management of glycemic control for critically ill cardiac patients . METHODS A prospect i ve r and omized controlled trial was conducted with a sample of 300 intensive care patients , 141 r and omized to the calculator group and 159 in the control ( paper protocol ) group . A convenience sample of 44 intensive care nurses responded to a nurse satisfaction survey . RESULTS A significantly higher percentage of glucose measurements were in the target range in the calculator group than in the control group ( 70.4 % [ SD , 15.2 % ] vs 61.6 % [ SD , 17.9 % ] , Z = -4.423 , P < .001 ) , and glucose variance was significantly less in the calculator group ( 35.5 [ SD , 18.3 ] mg/dL vs 42.3 [ SD , 21.2 ] mg/dL , Z = -3.845 , P < .001 ) . Fewer hypoglycemic events occurred in the calculator group ( 7 vs 18 ) , although this difference was not statistically significant . Nurse satisfaction was higher for the calculator group than for the control group ( 8.4 [ SD , 1.4 ] vs 4.8 [ SD , 2.4 ] , Z = -5.055 , P < .001 ) . Nurses ' deviation from the protocol was also less in the calculator group than in the control group . CONCLUSIONS Management of glycemic control and nurse satisfaction were improved with use of the dose calculator . Improving nurses ' processes of care may improve nurses ' use of time and patient care overall . Studies with larger sample sizes over time are needed to determine these relationships BACKGROUND Intensive glycemic control has been associated with reduced morbidity and mortality in critically ill patients . Web-based , patient-specific insulin nomograms may facilitate improved glucose control . OBJECTIVE To compare 2 algorithms for individualizing insulin infusion therapy ( a web-based system [ Glucomm and er method ] and a st and ard paper-based nomogram ) in a cardiovascular surgery intensive care unit ( ICU ) . METHODS In this prospect i ve , before-after cohort study , measures of glycemic control for 50 patients receiving insulin according to the Glucomm and er system  were compared with a control group ( n = 50 ) who received insulin according to the st and ard paper-based nomogram used in the cardiovascular surgery ICU . RESULTS There was no significant difference between the 2 groups with respect to time to target blood glucose ( 5.1 - 8.0 mmol/L ) , percentage of time within the target range , or mean amplitude of glucose excursion . Patients in the intervention group spent less time above the target range ( p = 0.007 ) and more time below the target range ( p < 0.001 ) , and the mean glucose was lower in this group compared with the control group ( 7.9 versus 8.6 mmol/L , p = 0.002 ) . The percentage of blood glucose measurements below 4 mmol/L was higher in the intervention group than in the control group ( 3.7 % versus 1.4 % , p = 0.003 ) . Satisfaction surveys revealed that the program was well accepted by the nursing staff in the cardiovascular surgery ICU . CONCLUSIONS A web-based insulin nomogram was an easy-to-use instrument for achieving tighter glucose control for patients in the cardiovascular surgery ICU . Use of the Glucomm and er system led to lower mean blood glucose but an increase in episodes of hypoglycemia OBJECTIVE We performed a r and omized trial to compare three insulin-titration protocol s for tight glycemic control ( TGC ) in a surgical intensive care unit : an absolute glucose ( Matias ) protocol , a relative glucose change ( Bath ) protocol , and an enhanced model predictive control ( eMPC ) algorithm . RESEARCH DESIGN AND METHODS A total of 120 consecutive patients after cardiac surgery were r and omly assigned to the three protocol s with a target glycemia range from 4.4 to 6.1 mmol/l . Intravenous insulin was administered continuously or in combination with insulin boluses ( Matias protocol ) . Blood glucose was measured in 1- to 4-h intervals as requested by the protocol s. RESULTS The eMPC algorithm gave the best performance as assessed by time to target ( 8.8 ± 2.2 vs. 10.9 ± 1.0 vs. 12.3 ± 1.9 h ; eMPC vs. Matias vs. Bath , respectively ; P < 0.05 ) , average blood glucose after reaching the target ( 5.2 ± 0.1 vs. 6.2 ± 0.1 vs. 5.8 ± 0.1 mmol/l ; P < 0.01 ) , time in target ( 62.8 ± 4.4 vs. 48.4 ± 3.28 vs. 55.5 ± 3.2 % ; P < 0.05 ) , time in hyperglycemia > 8.3 mmol/l ( 1.3 ± 1.2 vs. 12.8 ± 2.2 vs. 6.5 ± 2.0 % ; P < 0.05 ) , and sampling interval ( 2.3 ± 0.1 vs. 2.1 ± 0.1 vs. 1.8 ± 0.1 h ; P < 0.05 ) . However , time in hypoglycemia risk range ( 2.9–4.3 mmol/l ) in the eMPC group was the longest ( 22.2 ± 1.9 vs. 10.9 ± 1.5 vs. 13.1 ± 1.6 ; P < 0.05 ) . No severe hypoglycemic episode ( < 2.3 mmol/l ) occurred in the eMPC group compared with one in the Matias group and two in the Bath group . CONCLUSIONS The eMPC algorithm provided the best TGC without increasing the risk of severe hypoglycemia while requiring the fewest glucose measurements . Overall , all protocol s were safe and effective in the maintenance of TGC in cardiac surgery patients OBJECTIVE Diabetes mellitus is a risk factor for death after coronary artery bypass grafting . Its relative risk may be related to the level of perioperative hyperglycemia . We hypothesized that strict glucose control with a continuous insulin infusion in the perioperative period would reduce hospital mortality . METHODS All patients with diabetes undergoing coronary artery bypass grafting ( n = 3554 ) were treated aggressively with either subcutaneous insulin ( 1987 - 1991 ) or with continuous insulin infusion ( 1992 - 2001 ) for hyperglycemia . Predicted and observed hospital mortalities were compared with both internal and external ( Society of Thoracic Surgeons 1996 ) multivariable risk models . RESULTS Observed mortality with continuous insulin infusion ( 2.5 % , n = 65/2612 ) was significantly lower than with subcutaneous insulin ( 5.3 % , n = 50/942 , P < .0001 ) . Likewise , glucose control was significantly better with continuous insulin infusion ( 177 + /- 30 mg/dL vs 213 + /- 41 mg/dL , P < .0001 ) . For internal comparison , multivariable analysis showed that continuous insulin infusion was independently protective against death ( odds ratio 0.43 , P = .001 ) . Conversely , cardiogenic shock , renal failure , reoperation , nonelective operative status , older age , concomitant peripheral or cerebral vascular disease , decreasing ejection fraction , unstable angina , and history of atrial fibrillation increased the risk of death . For external comparison , observed mortality with continuous insulin infusion was significantly less than that predicted by the model ( observed/expected ratio 0.63 , P < .001 ) . Multivariable analysis revealed that continuous insulin infusion added an independently protective effect against death ( odds ratio 0.50 , P = .005 ) to the constellation of risk factors in the Society of Thoracic Surgeons risk model . CONCLUSION Continuous insulin infusion eliminates the incremental increase in in-hospital mortality after coronary artery bypass grafting associated with diabetes . The protective effect of continuous insulin infusion may stem from the effective metabolic use of excess glucose to favorably alter pathways of myocardial adenosine triphosphate production . Continuous insulin infusion should become the st and ard of care for glycometabolic control in patients with diabetes undergoing coronary artery bypass grafting BACKGROUND : Critically ill cardiothoracic patients are prone to hyperglycemia and an increased risk of surgical site infections postoperatively . Aggressive insulin treatment is required to achieve tight glycemic control ( TGC ) and improve outcomes . OBJECTIVE : To examine and report on the performance of an insulin infusion protocol to maintain TGC , defined as a blood glucose level of 80–150 mg/dL , in critically ill cardiothoracic surgical patients . METHODS : A nurse-driven insulin infusion protocol was developed and initiated in postoperative cardiothoracic surgical intensive care patients with or without diabetes . In this before — after cohort study , 2 periods of measurement were performed : a 6–month baseline period prior to the initiation of the insulin infusion protocol  ( control group , n = 174 ) followed by a 6–month intervention period in which the protocol was used ( TGC group , n = 168 ) . RESULTS : Findings showed percent and time of blood glucose measurements within the TGC range ( control 47 % vs TGC 61 % ; p = 0.001 ) , AUC of glucose exposure > 150 mg/dL versus time for the first 24 hours of the insulin infusion ( control 28.4 vs TGC 14.8 ; p < 0.001 ) , median time to blood glucose < 150 mg/dL ( control 9.4 h vs TGC 2.1 h ; p < 0.001 ) , and percent blood glucose < 65 mg/dL as a marker for hypoglycemia ( control 9.8 % vs TGC 16.7 % ; NS ) . CONCLUSIONS : An insulin infusion protocol design ed to achieve a goal blood glucose range of 80–150 mg/dL efficiently and significantly improved TGC in critically ill postoperative cardiothoracic surgery patients without significantly increasing the incidence of hypoglycemia BACKGROUND Diabetes mellitus is a risk factor for deep sternal wound infection after open heart surgical procedures . We previously showed that elevated postoperative blood glucose levels are a predictor of deep sternal wound infection in diabetic patients . Therefore , we hypothesized that aggressive intravenous pharmacologic control of postoperative blood glucose levels would reduce the incidence of deep sternal wound infection . METHODS In a prospect i ve study of 2,467 consecutive diabetic patients who underwent open heart surgical procedures between 1987 and 1997 , perioperative 
    Output:
    
There is evidence of a benefit of continuous insulin infusions for patients following cardiac surgery with the computer calculator CII method achieving optimal glycemic control .
IMPLICATION S FOR PRACTICE The implementation of a computer calculator CII algorithm allows for individualized patient treatment .