Constructing a risk prediction model for anastomotic leakage after esophageal cancer resection. Issue 4 (April 2020)

• Record Type: Journal Article
• Authors: Sun, Zhong-Wen; Du, Hui; Li, Jia-Rui; Qin, Hui-Ying
• Is Part Of: Journal of international medical research. Volume 48:Issue 4(2020)
• Publication Date: 2020-04
• Subjects: Esophageal cancer resection -- anastomotic leakage -- risk prediction model -- early diagnosis -- pleural effusion -- exudation; Medicine -- Periodicals; Pharmacology -- Periodicals; 610.5
• DOI: 10.1177/0300060519896726
• Languages: English
• ISSNs: 0300-0605

Abstract

Objective: The purpose of this study was to investigate a newly constructed risk prediction model for anastomotic leakage after esophageal cancer resection. Methods: A retrospective survey of 205 patients who underwent esophageal cancer resection was conducted using a self-designed questionnaire. The influencing factors were explored by single factor analysis, and a logistic regression analysis was performed to construct the prediction equation. A receiver operating characteristic curve was used to evaluate the model. Results: The incidence of anastomotic leakage after esophageal cancer resection was 11.73%. There were five independent risk factors entered into the regression equation. The risk prediction equation was Z = 0.108 × age + 2.011 × preoperative chemotherapy history + 3.007 ×incision redness/exudation + 2.632 × pleural effusion + 1.934 × increased white blood cell count − 12.304. According to the receiver operating characteristic curve test, the area under the curve was 0.946, the sensitivity was 0.833, the specificity was 0.912, and the Youden index was 0.745. Conclusion: The risk model of anastomotic leakage after esophageal cancer resection had a good predictive effect that was of significance for guiding clinical observation and early-screening.