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External validation of two prediction models for adequate bowel preparation in Asia: a prospective study

医学 置信区间 内科学 接收机工作特性 结肠镜检查 前瞻性队列研究 肝病学 曲线下面积 肠道准备 便秘 人口 结直肠癌 环境卫生 癌症
作者
Xin Yuan,Huizhi Gao,Cenqin Liu,Weihong Wang,Jiarong Xie,Zhixin Zhang,Lei Xu
出处
期刊:International Journal of Colorectal Disease [Springer Science+Business Media]
卷期号:37 (6): 1223-1229 被引量:3
标识
DOI:10.1007/s00384-022-04156-0
摘要

Several models for predicting adequate bowel preparation are available but have never been externally validated. The aim of this study is to compare the available models in an independent population.This study prospectively recruited 500 consecutive patients from August to December 2020 from the Endoscopy Center of a tertiary hospital. All patients underwent the same bowel preparation regimen. The discrimination of the prediction models was quantified with the area under the receiver operating characteristic curve (AUC), and the 95% confidence interval (CI) was calculated for each AUC.Finally, 461 patients were eligible for this study. A total of 110 (23.9%) patients were deemed to show inadequate bowel preparation during colonoscopy. There were significant differences between patients with and without adequate bowel preparation in terms of current hospitalization, procedure time, comorbidities (including diabetes and constipation), American Society of Anesthesiologists Physical Status Classification System score (ASA) ≥ 3, medication usage, and abdominal/pelvic surgery. The prediction models performed as follows: the Dik ≥ 2 model, the Dik ≥ 3 model, and the Antonio > 1.225 model had AUCs of 0.660 (95% CI = 0.604-0.717), 0.691 (95% CI = 0.646-0.733), and 0.645 (95% CI = 0.615-0.704), respectively. Comparison of the two prediction models showed no significant improvement (Antonio > 1.225 vs. Dik ≥ 3, 1.801, 95% CI = -0.004-0.096, P = 0.072).Both models are potentially helpful. However, it is necessary to develop or improve a prediction model to obtain a more suitable and detailed model.ClinicalTrials.gov, Number NCT04607161.
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