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Background <p>Inadequate bowel preparation (IBP) seriously compromises the quality of colonoscopy. Existing prediction models for IBP before colonoscopy lack generalizability and are insufficiently validated across diverse bowel preparation regimens. This study aimed to develop a novel model for prediction of IBP based on a systematic review and meta-analysis, and then validate its performance against those of existing prediction models in a multicenter cohort.</p> Methods <p>In the development cohort, statistically significant risk factors for IBP were systematically reviewed, and included in the novel model and weighted according to their coefficients. In the external validation cohort, the discrimination and calibration performance of the novel model was evaluated and quantified by the concordance statistic (C-statistic) and calibration slope, respectively, and then compared against existing prediction models, which were systematically reviewed and identified, in a multicenter cohort study.</p> Results <p>Twenty-five cohorts comprising 39,403 patients (11,883 with IBP) were included in the meta-analysis regarding risk factors of IBP. Age, sex, body mass index, smoking, constipation, diabetes mellitus, ASA score, history of colorectal surgery, and use of antidepressants and opioids were finally included in the novel model. By collecting 2,360 patients (445 with IBP) from 4 medical centers, its performance was externally validated [C-statistics: 0.806 and 0.744 for split-dose and full-dose 3&#xa0;L polyethylene glycol (PEG) regimens], respectively; calibration slope: 1.009 and 0.985, respectively], and superior to four existing models.</p> Conclusion <p>A novel model was developed and was shown to have a favorable predictive performance of IBP in patients receiving either split-dose or full-dose 3&#xa0;L PEG regimens.</p> Registry <p>ClinicalTrials.gov, TRN: NCT06438237, Registration date: 27 May 2024.</p>

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Development and multicenter external validation of a novel prediction model for inadequate bowel preparation before colonoscopy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月23日

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  • Weiyi Wang,
  • Libo Tong,
  • Shiyang Li,
  • Wei He,
  • Jinyuan Huang,
  • Xiaofeng Liu,
  • Cui Wang,
  • Junqi Xia,
  • Xingshun Qi,
  • Caiping Song

摘要

Background

Inadequate bowel preparation (IBP) seriously compromises the quality of colonoscopy. Existing prediction models for IBP before colonoscopy lack generalizability and are insufficiently validated across diverse bowel preparation regimens. This study aimed to develop a novel model for prediction of IBP based on a systematic review and meta-analysis, and then validate its performance against those of existing prediction models in a multicenter cohort.

Methods

In the development cohort, statistically significant risk factors for IBP were systematically reviewed, and included in the novel model and weighted according to their coefficients. In the external validation cohort, the discrimination and calibration performance of the novel model was evaluated and quantified by the concordance statistic (C-statistic) and calibration slope, respectively, and then compared against existing prediction models, which were systematically reviewed and identified, in a multicenter cohort study.

Results

Twenty-five cohorts comprising 39,403 patients (11,883 with IBP) were included in the meta-analysis regarding risk factors of IBP. Age, sex, body mass index, smoking, constipation, diabetes mellitus, ASA score, history of colorectal surgery, and use of antidepressants and opioids were finally included in the novel model. By collecting 2,360 patients (445 with IBP) from 4 medical centers, its performance was externally validated [C-statistics: 0.806 and 0.744 for split-dose and full-dose 3 L polyethylene glycol (PEG) regimens], respectively; calibration slope: 1.009 and 0.985, respectively], and superior to four existing models.

Conclusion

A novel model was developed and was shown to have a favorable predictive performance of IBP in patients receiving either split-dose or full-dose 3 L PEG regimens.

Registry

ClinicalTrials.gov, TRN: NCT06438237, Registration date: 27 May 2024.