Establishment and application of a novel assessment system for prognosis of elderly patients with upper gastrointestinal perforation
Objective:To construct a novel assessment system for the prognosis of elderly patients with upper gastrointestinal perforation and the application of machine learning classifiers,for admission to quickly predict the prognosis of elderly patients with upper gastrointestinal perforation.Methods:A total of 95 patients admitted to the Department of Emergency Surgery of Union Hospital of Fujian Medical University from June 2017 to July 2023 with a diagnosis of upper gastrointestinal perforation in the elderly were retrospectively collected.The clinical data and laboratory examination data of the patients were collected,and the postoperative serious complications of the patients were graded.Their prognosis was automatically grouped into good prognosis group(GP group,70 ca-ses)and poor prognosis group(PP group,25 cases)using TWO-STEP cluster grouping(TSC).The prognosis of elderly patients with upper gastrointestinal perforation was predicted by integrating admission multifactors using machine learning classifiers,and the predictive effect was analysed by using the subject's work characteristics(ROC)curve.Results:The postoperative gastrointestinal recovery time,intensive care time,and hospitalisation cost of the patients in the PP group were significantly higher than those in the GP group.Comparing the differen-tiation of hospitalisation days between the TSC assessment system and the severe adverse events(SAE)classifica-tion,it was found that:the TSC assessment system had a better differentiation compared with the SAE classifica-tion(TSC:P＜0.001,SAE:P=0.01).Further comparing the admission status of the two groups,it was found that:the PP group was significantly older than the GP group(77.00[71.50-82.50]vs 72.00[67.00-78.00],P=0.043),and its preoperative peripheral blood albumin level was significantly lower than that of the GP group.Comparing the predictive efficacy of different machine learning classifiers for the TSC assessment system,it was found that:the adaptive boosting classifier(AB)had the best predictive efficacy,with an area under the curve(AUC)of 0.97(95％CI:0.52-1.00,precision 0.86).Conclusion:The TSC assessment system is effective in targeting the prognosis of elderly patients with upper gastrointestinal perforation.Advanced age and hypoalbumin-aemia were independent risk factors for poor prognosis in patients with upper gastrointestinal perforation.The AB helps to rapidly predict the prognosis of elderly patients with upper gastrointestinal perforation on admission and assists in clinical management.
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