Admission-specific chronic disease scores as alternative predictors of surgical site infection for patients undergoing coronary artery bypass graft surgery

Objective. To evaluate the admission chronic disease score ( ACDS) and a variant of the ACDS as predictors of surgical site infection (SSI) for study participants who underwent coronary artery bypass graft (CABG) surgery. Design. Retrospective case-control study. Setting. A 750-bed academic medical center. Participants. All participants with an SSI that was identified through hospital-based surveillance (defined as case patients) and a random sample of participants without SSI following CABG surgery (defined as control subjects) between July 1, 1999, and June 30, 2001. results. An ACDS based on medications ordered on the day of hospital admission was determined for 264 study participants admitted prior to the day of the surgical procedure. A preadmission chronic disease score (PACDS) based on outpatient medications was calculated for 281 participants, using the record of preadmission medications in the patient's discharge summary. The ACDS and PACDS were significantly higher for case patients, compared with control subjects (and, respectively). American Society of Anesthe. siologists (ASA) score and the standard National Nosocomial Infection Surveillance system (NNIS) risk index were not significant predictors of SSI. In logistic regression models, only the ACDS (odds ratio, 1.02 per 100 ACDS points), the PACDS (odds ratio, 1.02 per 100 PACDS points), the highest PACDS quintile (odds ratio, 2.89 [compared with lowest quintile]), and a modified NNIS-PACDS score of 2 (odds ratio, 3.5 [compared with a score of 0]) were significant predictors of SSI. Conclusions. Because preoperative medications are likely to reflect comorbidities that influence the risk of SSI, medication-based scoring systems such as the ACDS and PACDS may allow for better risk stratification than the standard NNIS risk index, particularly for patient populations with relatively homogenous wound classification and ASA score distributions.