Intensive glycemic control was associated with a decreased risk of infection (relative risk, 0.41; 95% CI, 0.21–0.77), but this association mainly was derived from studies in surgical settings.
Subgroup analyses demonstrated an association between achieving intensive glycemic goals and an increased risk of hypoglycemia (P=0.01). Hypoglycemia also more commonly occurred in surgical patients.
There was substantial heterogeneity across studies included for all outcomes except infection. The quality of the current evidence supporting a reduction in infection is low and appears mostly derived from patients in surgical settings. The quality of evidence relating to all the other outcomes is also low and is limited by heterogeneity and imprecision.
Bottom line: Intensive control of hyperglycemia in noncritically ill hospitalized patients might reduce the risk of infection in some patients but does not appear to be significantly associated with improvement in other important clinical outcomes.
Citation: Murad MH, Coburn JA, Coto-Yglesias F, et al. Glycemic control in non-critically ill hospitalized patients: a systematic review and meta-analysis. J Clin Endocrinol Metab. 2012;97(1):49-58.
Simple Risk Score Predicts 30-Day Mortality after Noncardiac Surgery
Clinical question: Can 30-day mortality risk after noncardiac surgery be predicted by using a simple bedside-risk index?
Background: While indices exist to quantify the risk of cardiac complications in patients undergoing noncardiac surgery, there is significant perioperative mortality due to noncardiac causes. Therefore, a need exists for a simple risk index to predict all-cause mortality after noncardiac surgery.
Study design: Retrospective cohort study.
Setting: American College of Surgeons National Surgical Quality Improvement Program database of patients in more than 200 hospitals.
Synopsis: The nine-point Surgical Mortality Probability Model (S-MPM) 30-day mortality risk index was empirically created and applied to a randomly split portion of a database, which included 298,772 patients undergoing noncardiac surgery. Three risk factors were included: American Society of Anesthesiologists (ASA) physical status, surgery risk class, and emergency status. Patients with ASA physical status I, II, III, IV, or V were assigned zero, two, four, five, or six points, respectively. Patients undergoing intermediate- or high-risk procedures were assigned one or two points, respectively. Patients undergoing emergency procedures were assigned one point. The S-MPM then was applied to the validation portion of the data set.
The 30-day predicted risk of mortality was less than 0.50% for those patients with combined risk scores of less than five (S-MPM Class I), between 1.5% and 4.0% for risk scores of five to six (Class II), and more than 10% for risk scores greater than six (Class III).
The major limitation of this derived risk score is the reliance on ASA physical status, which has imprecise definitions and might lead to inconsistent ratings.
Bottom line: The S-MPM risk index is a simple bedside scoring system, which can accurately predict 30-day mortality in patients undergoing noncardiac surgery.
Citation: Glance LG, Lustik SJ, Hannan EL, et al. The Surgical Mortality Probability Model: Derivation and validation of a simple risk prediction rule for noncardiac surgery. Ann Surg. 2012;255(4):696-702.
Temperature, White Blood Cell Count Are Not Sensitive Predictors of Bacteremia
Clinical question: In ED patients with suspected infection, are temperature, white blood cell (WBC) count, and bandemia reliable predictors of bacteremia?
Background: Sepsis is a significant cause of morbidity and mortality. Early identification and treatment of sepsis improves patient outcomes. Although systemic inflammatory response syndrome criteria aids in the prompt recognition of sepsis, these markers have variable sensitivity and specificity for true infection or bacteremia, which places patients at high risk for sepsis.
Study design: Post-hoc data analysis of a prospective cohort study.