A Simple Risk Score for Predicting Surgical Site Infections in Inflammatory Bowel Disease

医学 炎症性肠病 逻辑回归 克罗恩病 溃疡性结肠炎 单变量分析 疾病 内科学 弗雷明翰风险评分 结肠切除术 外科 手术部位感染 结直肠外科 手术伤口 多元分析 腹部外科
作者
Karim Alavi,Paul R. Sturrock,W. Brian Sweeney,Justin A. Maykel,J. Andres Cervera-Servin,Jennifer F. Tseng,E. Francis Cook
出处
期刊:Diseases of The Colon & Rectum [Lippincott Williams & Wilkins]
卷期号:53 (11): 1480-1486 被引量:30
标识
DOI:10.1007/dcr.0b013e3181f1f0fd
摘要

Patients with inflammatory bowel disease are often at highest risk for surgical site infections. We sought to define the predictors of surgical site infections and to develop a risk score for predicting those at highest risk.Patients undergoing a bowel resection for Crohn's disease or ulcerative colitis were identified from National Surgical Quality Improvement Program 2008. Univariate and multivariate analyses were conducted to identify predictors of surgical site infections. Clinically relevant prediction categories were developed and the predictive behavior of the model was validated by use of National Surgical Quality Improvement Program 2007. An integer-based scoring system risk score was created proportional to the logistic regression coefficients, grouping patients into categories of similar risk.We identified 271,368 patients; 3981 of these patients underwent an operation for Crohn's disease (n = 2895) or ulcerative colitis (n = 1086). Nine hundred (22.6%) patients developed surgical site infections. Predictors included weight loss, smoking, emergent surgery, wound class, operative time (minutes), and an ASA score >2. A risk score was developed by stratifying patients into low (0-5), 15.6%; medium (6-8), 25.2%; and high (>8), 36.1% risk.Patients with inflammatory bowel disease are at high risk for surgical site infections. Preoperative factors including weight loss, smoking, emergent surgery and an ASA score >2 are strong predictors of surgical site infections. Operative time and wound class are important intraoperative predictors. A risk score, based on pre- and intraoperative variables, can be used to identify patients at highest risk of developing surgical site infections. This may allow for appropriate process measures to be implemented to prevent and lessen the impact of surgical site infections in this high-risk population.

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