Validating a 3-point prediction rule for surgical site infection after coronary artery bypass surgery.
BACKGROUND: Surgical site infection (SSI) after coronary artery bypass graft (CABG) surgery is an increasing healthcare problem. Investigators from Australia proposed a new, 3-point scale that assesses SSI risk on the basis of diagnosis of diabetes mellitus and body mass index. OBJECTIVE: To validate the Australian Clinical Risk Index among patients undergoing CABG surgery in the United States. DESIGN AND SETTING: Nested case-control study involving patients undergoing CABG surgery at 9 hospitals during 1991-2002. PATIENTS: Case patients were those who developed SSIs after CABG surgery. Control subjects were matched to case patients on the basis of hospital, age, and procedure date. METHODS: Odds ratios (ORs) for SSIs were calculated for the comparison of case patients with control subjects for all risk categories determined using the Australian Clinical Risk Index and National Nosocomial Infections Surveillance System (NNIS) risk index. An adjusted area under the curve was used to compare predictive values among risk indices. RESULTS: Four hundred sixty patients were studied, including 269 patients with SSI and 191 control subjects. NNIS risk group 2 was associated with increased rate of SSI (OR, 1.79; 95% confidence interval [CI], 1.19-2.67). No patient had an NNIS risk index of 3. The remaining NNIS categories were not predictive of infection. In contrast, an increase in Australian Clinical Risk Index was associated with an increase in risk of SSI (category 2: OR, 2.39 [95% CI, 1.33-4.29]; category 3: OR, 4.46 [95% CI, 1.83-10.85]). CONCLUSIONS: The NNIS risk index predicts the risk of SSI associated with many procedures, but it has limited use in predicting the risk of SSI after CABG surgery. The new Australian Clinical Risk Index stratified patients into discrete groups associated with increased risk of SSI. Data from our study support the use of this new risk index in the US population.
Chen, LF; Anderson, DJ; Kaye, KS; Sexton, DJ
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