Construction of a clinical prediction model for bowel preparation failure in patients undergoing colonoscopy
10.3760/cma.j.cn115682-20250207-00535
- VernacularTitle:结肠镜检查患者肠道清洁失败临床预测模型的构建
- Author:
Hongjun CHEN
1
;
Guangyu ZHU
Author Information
1. 中山大学附属第五医院消化内科，珠海 519000
- Publication Type:Journal Article
- Keywords:
Colonoscopy;
Bowel preparation failure;
Prediction model;
Model construction
- From:
Chinese Journal of Modern Nursing
2025;31(29):4003-4008
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a prediction model for bowel preparation failure in patients undergoing colonoscopy.Methods:A total of 378 inpatients from the Department of Gastroenterology who underwent colonoscopy at the Fifth Affiliated Hospital of Sun Yat-sen University from August 2021 to May 2022 were selected by convenience sampling. The quality of bowel preparation was evaluated using the Boston Bowel Preparation Scale (BBPS). Baseline demographic information, relevant clinical data, and laboratory test results after admission were collected. Logistic regression analysis was performed to identify factors influencing bowel preparation failure and to construct the prediction model. The discriminative ability, calibration, and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curve, nomogram calibration curve, and decision curve analysis.Results:According to BBPS scores, 199 of the 378 patients experienced bowel preparation failure. Logistic regression analysis showed that a history of abdominal surgery, dyslipidemia, hypertension, liver cirrhosis, and colonoscopy timing were independent predictors of bowel preparation failure ( P<0.05). The area under the ROC curve of the constructed model was 0.835 (95% confidence interval: 0.759-0.874). The calibration curve indicated that the deviation between predicted and actual outcomes was small. The decision curve analysis showed favorable clinical utility within a threshold probability range of 0.18-0.85. Conclusions:The prediction model for bowel preparation failure constructed in this study demonstrated good discrimination, calibration, and clinical utility. The model can effectively predict the quality of bowel preparation in patients undergoing colonoscopy, provide scientific support for clinical decision-making, and help optimize bowel preparation regimens, thereby improving the success rate and safety of colonoscopy.
