Objective To explore the influencing factors for hypoglycemia in elderly patients during peri-colonoscopy,construct and validate a risk prediction model.Methods The factors influencing hypoglycemia in elderly patients during the peri-colonoscopy period were identified through a literature review and semi-structured interviews.After two rounds of Delphi expert consultation,the survey questionnaire was determined.From January to September 2023,convenience sampling was used to select elderly patients who underwent colonoscopy in the Department of Gastroenterology at the Affiliated Hospital of Qingdao University as participants for a questionnaire survey.Univariate and multivariate Logistic regression was used to explore the influencing factors of hypoglycemia in elderly patients during the peri-colonoscopy period,and a nomogram model of hypoglycemia risk in elderly patients during the peri-colonoscopy period was drawn.The area under the receiver operating characteristic curve(AUC)of the subjects and the Hosmer-Lemeshow goodness of fit test were used to evaluate the model's predictive performance.The clinical decision curve of DCA was implemented to evaluate the model's clinical benefit ability.Results A total of 558 questionnaires were distributed(392 for the modeling group and 166 for the validation group)and 558 valid questionnaires were collected,with a valid response rate of 100.00％.Among 558 elderly patients,a total of 130 cases(89 in the modeling group and 41 in the validation group)experienced hypoglycemia during the peri-colonoscopy period,with an incidence of 23.30％.Multivariate Logistic regression analysis showed that serum albumin,age,previous hypoglycemia frequency,insulin use,fasting time,and nutritional risk were independent influencing factors(all P＜0.05).The AUCs of the modeling and validation groups were 0.933 and 0.899,respectively.Hosmer Lemeshow test showed that the model had good calibration accuracy,and the DCA curve indicated that the model had good clinical effectiveness.Conclusions The nomogram model has good predictive performance and can intuitively and concisely predict the risk of hypoglycemia in elderly patients during the peri-colonoscopy period,providing reference for medical and nursing staff.
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