Prediction model for irreversible intestinal ischemia in strangulated bowel obstruction

Author:

Kobayashi Toshimichi,Chiba Naokazu,Koganezawa Itsuki,Nakagawa Masashi,Yokozuka Kei,Ochiai Shigeto,Gunji Takahiro,Sano Toru,Tomita Koichi,Tabuchi Satoshi,Hidaka Eiji,Kawachi Shigeyuki

Abstract

AbstractBackgroundPreoperatively diagnosing irreversible intestinal ischemia in patients with strangulated bowel obstruction is difficult. Therefore, this study aimed to establish a prediction model for irreversible intestinal ischemia in strangulated bowel obstruction.MethodsWe included 83 patients who underwent emergency surgery for strangulated bowel obstruction between January 2014 and March 2022. The predictors of irreversible intestinal ischemia in strangulated bowel obstruction were identified using logistic regression analysis, and a prediction model for irreversible intestinal ischemia in strangulated bowel obstruction was established using the regression coefficients. Receiver operating characteristic analysis and fivefold cross-validation was used to assess the model.ResultsThe prediction model (range, 0–4) was established using a white blood cell count of ≥ 12,000/µL and the computed tomography value of peritoneal fluid that was ≥ 20 Hounsfield units. The areas of the receiver operating characteristic curve of the new prediction model were 0.814 and 0.807 after fivefold cross-validation. A score of ≥ 2 was strongly suggestive of irreversible intestinal ischemia in strangulated bowel obstruction and necessitated bowel resection (odds ratio = 15.938). The bowel resection rates for the prediction scores of 0, 2, and 4 were 15.2%, 66.7%, and 85.0%, respectively.ConclusionOur model may help predict irreversible intestinal ischemia that necessitates bowel resection for strangulated bowel obstruction cases and thus enable surgeons to recognize the severity of the situation, prepare for deterioration of patients with progression of intestinal ischemia, and select the appropriate surgical procedure for treatment.

Publisher

Springer Science and Business Media LLC

Subject

General Medicine,Surgery

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