Abstract

Information-based scoring systems predictive of outcomes of midline laparotomy are needed; these systems can support surgical decisions with the aim of improving patient outcomes and quality of life, and reducing the risk of secondary surgical procedures. All study subjects were followed for a minimum of 6 months after operation. Numerous demographic, clinical, treatment, and outcomes-related perioperative factors were recorded to determine statistical association with the primary end point: incisional hernia development. The first analysis was designed to establish the statistical model (scoring system) for estimating the risk of incisional hernia within 6 months of midline laparotomy. Univariate and multivariate analyses were performed. A simple additive model was constructed using stepwise logistic and linear regression. The second part of the study analysis was validation of the scoring systems developed initially. A logistic linear minimum regression model was developed based on four covariates independently predictive of incisional hernia: Body mass index (BMI) > 24.4kg/m(2); fascial suture to incision ratio (SIR) < 4.2; deep surgical site, deep space, or organ infection (SSI); and time to suture removal or complete epithelialization >16 days (TIME). The hernia risk scoring system equation [p(%) = 32(SIR) + 30(SSI) + 9(TIME) + 2(BMI)] provided accurate estimates of incisional hernia according to stratified risk groups based on total score: low (0 to 5 points), 1.0%; moderate (6 to 15 points), 9.7%; increased (16 to 50 points), 30.2%; and markedly increased (>50 points), 73.1%. A statistically valid, straightforward, and clinically useful predictive model was developed for estimating the risk of incisional hernia within 6 months of midline laparotomy. Prospective independent validation of this model appears indicated.

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