ArticleScientific reports2025
Development and validation of a gut motility based model for predicting bowel preparation quality.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk prediction models for inadequate bowel preparation before colonoscopy: A systematic review and meta-analysis.PloS one · 2026Pooled it
- A Machine Learning-Based Clinical Tool for Predicting Inadequate Bowel Preparation: Development and Validation.Clinical and translational gastroenterology · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Inadequate bowel preparation negatively impacts the quality of colonoscopy, potentially resulting in missed lesions and the need for repeat procedures. Although gut motility plays a key role in bowel cleansing, it is often neglected in risk prediction. This study developed and validated a predictive model and simplified scoring system that integrates gut motility parameters to identify individuals at risk of inadequate bowel preparation. A total of 1,165 patients from two hospitals were enrolled, with 815 forming the training set and 350 forming the external validation cohort. The overall rate of inadequate bowel preparation was 9.8%. Multivariate analysis revealed that altered bowel movement frequency, stool consistency based on the Bristol Stool Scale, low polyethylene glycol (PEG) volume, and delayed last bowel movement were significant predictors of poor preparation. These variables were incorporated into a user-friendly scoring system that demonstrated good discriminative ability, with area under the curve values of 0.778 and 0.774 in the training and validation cohorts, respectively. A cutoff score of 3.0 yielded a sensitivity of 75.0%, specificity of 66.9%, and a negative predictive value of 96.3% in external validation. This model provides a practical, motility-informed approach for risk stratification and personalized preparation regimens, offering potential to enhance the effectiveness and efficiency of colonoscopy in diverse clinical settings.
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Registered trials
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