Information from the abstract
Objective Incisional hernia (IH) is a common complication of abdominal surgery; preoperative identification of high-risk patients enables targeted prevention. We aimed to identify independent preoperative predictors of IH and to derive a simple risk-stratification score in a Thai population. Methods We conducted a retrospective, matched 1:1 case–control study at Vajira Hospital, comparing 100 patients who developed an IH after abdominal surgery with 100 patients who did not, individually matched on type of operation. Preoperative variables ascertained before the index operation were analysed by conditional logistic regression. Discrimination was assessed by the area under the ROC curve (AUC) and calibration by the Hosmer–Lemeshow test; internal validity was examined by 1000-iteration bootstrap resampling. Results Six independent preoperative predictors were identified: hypertension (odds ratio [OR] 4.36, 95% CI 1.53–12.46), diabetes (OR 4.20, 1.11–15.89), female sex (OR 3.66, 1.20–11.15), previous abdominal operation (OR 3.25, 1.37–7.72), body mass index (OR 1.24 per kg/m 2 , 1.10–1.41), and age (OR 1.05 per year, 1.01–1.09). The model showed good discrimination (apparent AUC 0.82; optimism-corrected AUC 0.80) and good calibration (Hosmer–Lemeshow p = 0.72). A 6-factor points score stratified patients into low-, intermediate-, and high-risk groups. Conclusion Six routinely available preoperative factors independently predict IH and can be combined into a practical risk-stratification score to support individualized counselling and preventive strategies. Because of the case–control design, the score stratifies relative risk and is not intended to estimate absolute probability; external, prospective validation is warranted.
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Related topics: Hernia repair and management · Surgical site infection prevention · Abdominal Surgery and Complications
Thai researcher and institutional participation
Suksan Kanoksin · Krin Muangnoijaroen · Suphakarn Techapongsatorn · Chulabhorn Graduate Institute · Chulabhorn Hospital · Navamindradhiraj University
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