Preliminary data from a surveillance study on surgical site infections and assessment of risk factors in a university hospital

Authors: MUSTAFA NAMIDURU, İLKAY KARAOĞLAN, RIZA ÇAM, VUSLAT BOŞNAK, AYŞE ÖZLEM METE

Abstract: Surgical site infections (SSIs) lead to substantial mortality, morbidity, and socioeconomic loss. To explore the rate of infections and risk factors for the development of infection in surgical units. Materials and methods: All patients (n = 1397) who underwent a surgical intervention and were hospitalized for >48 h in surgical units (except the ophthalmology unit) of Gaziantep University Medical Faculty Hospital between 17 March 2008 and 15 July 2008 were included in the study. The Center for Disease Control and Prevention criteria were used for identifying and diagnosing SSIs. Rate of SSI was calculated as the number of SSIs observed after every 100 surgical procedures. Potential risk factors for SSIs were evaluated by multivariate logistic regression model. Results: SSIs occurred in 131 (9.4%) of the 1397 patients during this period. SSIs extended length of stay by 12.8 days. In the multivariate logistic regression analysis, diabetes mellitus (OR: 2.660, CI: 1.389-5.093), use of surgical drains (OR: 3.706, CI: 1.910-7.191), perioperative transfusion (OR: 1.787, CI: 1.077-2.965), trauma (OR: 2.244, CI: 1032-4.880), reoperation (OR: 7.408, CI: 3.315-16.555), contaminated (OR: 3.291, CI: 1.433-7.556) or dirty-infected (OR: 3.451, CI: 1.888-6.310) wound types, and each point increase in the National Nosocomial Infection Surveillance (NNIS) risk index (OR: 7.499, CI: 4.336-12.967) were detected as independent risk factors for developing SSIs. Conclusion: In an effort to decrease SSI rate, risk factors should be determined and essential measures should be implemented regarding preventable factors. In this context, the excess transfusion of blood and blood products and unnecessary use of surgical drains should be avoided, and surgical drains should be removed as soon as possible. In addition, traditional wound classification and NNIS risk index may be used in the prediction of SSIs.

Keywords: Surgical site infection, risk factors

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