Surgical Site Infections at Shirati KMT Hospital in Northeastern Tanzania.

Abstract

Despite improved guidelines for surgical practices and better surgical methods and tools, surgical site infection (SSI) is still a common cause of morbidity and mortality with increased rates in resource-limited nations. In Tanzania, there is limited data on SSI and associated risk factors for developing an effective surveillance system for SSI. In this study, we aimed to establish for the first time the baseline SSI rate and its associated factors at the Shirati KMT Hospital in Northeastern Tanzania. We collected hospital records of 423 patients who had undergone major and minor surgeries between January 1 and June 9, 2019, at the hospital. After accounting for incomplete records and missing information, we analyzed a total of 128 patients and found an SSI rate of 10.9% and performed univariate and multivariate logistic regression analyses for elucidating the relationship between risk factors and SSI. All patients with SSI had undergone major operations. Moreover, we observed trends of increased association of SSI with patients who are 40 or younger, female, and had received antimicrobial prophylaxis or more than one type of antibiotics. In addition, patients who had received an American Society of Anesthesiologists (ASA) score of II or III, as one category, or undergone elective operations or operations lasting longer than 30 minutes were prone to develop SSI. Although these findings were not statistically significant, both univariate and multivariate logistic regression analyses showed a significant correlation between clean contaminated wound class and SSI, consistent with previous reports. The study is the first to elucidate the rate of SSI and its correlated risk factors at the Shirati KMT Hospital. We conclude that, based on the obtained data, clean contaminated wound class is a significant predictor of SSI at the hospital and that an effective surveillance system for SSI should begin with adequate record keeping of all patients' hospitalization and an efficient follow-up system. Moreover, a future study should aim to explore more widespread SSI predictors such as premorbid illness, HIV status, duration of hospitalization prior to operation, and type of surgery.