Abstract
BackgroundSurgical site infections (SSI) are an important cause of peri-surgical morbidity with risks that vary extensively between patients and surgeries. Quantifying SSI risk would help identify candidates most likely to benefit from interventions to decrease the risk of SSI.MethodsWe randomly divided all surgeries recorded in the National Surgical Quality Improvement Program from 2010 into a derivation and validation population. We used multivariate logistic regression to determine the independent association of patient and surgical covariates with the risk of any SSI (including superficial, deep, and organ space SSI) within 30 days of surgery. To capture factors particular to specific surgeries, we developed a surgical risk score specific to all surgeries having a common first 3 numbers of their CPT code.ResultsDerivation (n = 181 894) and validation (n = 181 146) patients were similar for all demographics, past medical history, and surgical factors. Overall SSI risk was 3.9%. The SSI Risk Score (SSIRS) found that risk increased with patient factors (smoking, increased body mass index), certain comorbidities (peripheral vascular disease, metastatic cancer, chronic steroid use, recent sepsis), and operative characteristics (surgical urgency; increased ASA class; longer operation duration; infected wounds; general anaesthesia; performance of more than one procedure; and CPT score). In the validation population, the SSIRS had good discrimination (c-statistic 0.800, 95% CI 0.795–0.805) and calibration.ConclusionSSIRS can be calculated using patient and surgery information to estimate individual risk of SSI for a broad range of surgery types.
Highlights
Surgical site infections [SSIs] are important events
Determining the likelihood that a particular patient develops an SSI is essential for deciding whether or not particular preventive strategies [such as prophylactic antibiotics] should be used. This is because the probability that a particular patient benefits from such strategies is inversely associated with baseline risk of the event
SSI risk for an individual patient can be estimated with this model via a webpage that we have developed or using a point system created from the model
Summary
Surgical site infections [SSIs] are important events They are one of the most common nosocomial infections [1], occurring in 2–5% of the estimated 30 million operations occurring annually in the United States [2]. They are associated with significantly increased health care costs [3]. Determining the likelihood that a particular patient develops an SSI is essential for deciding whether or not particular preventive strategies [such as prophylactic antibiotics] should be used This is because the probability that a particular patient benefits from such strategies is inversely associated with baseline risk of the event.
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