The quality of bowel preparation is pivotal for successful colonoscopy, yet studies indicate around 25% of procedures encounter inadequate preparation. A recent study conducted by researchers from The First Affiliated Hospital of Zhejiang University sought to address this issue by deriving and validating a prediction model aimed at identifying outpatients who may struggle with preparation.
This prospective observational study, which took place between December 15, 2022, and August 12, 2023, involved 1,314 elective colonoscopy patients. The primary goal was to analyze factors influencing bowel preparation outcomes and to create a predictive model based on these insights.
Utilizing the Boston Bowel Preparation Scale, scores were assigned to evaluate preparation quality, with inadequate preparation defined as any total score below six. The researchers identified six key risk factors through multivariate logistic regression: male sex, diabetes, chronic constipation, previous colorectal surgery, the consumption of a high-fiber diet within 24 hours pre-colonoscopy, and the time elapsed from preparation to the procedure exceeding five hours.
Among the derivation cohort of 1,035 patients, 260 (25.1%) were noted to have inadequate bowel preparation. The validation cohort included 279 patients, reinforcing the model's applicability with similar findings. The predictive model demonstrated adequate calibration and clinical utility, with the area under the curve (AUC) consistently maintaining around 0.704 across both cohorts, indicating reasonable accuracy.
"A model was constructed and validated to identify patients who were at high risk of inadequate bowel preparation by using six simple variables," the authors stated, highlighting the framework's significance. The clinical decision curve analysis indicated beneficial outcomes for clinicians, allowing for targeted interventions based on predictive scores.
This model not only aids healthcare providers but also focuses on improving patient outcomes by identifying high-risk individuals who may require extra guidance on proper bowel preparation techniques.
Looking forward, researchers advocate for broader validation studies to confirm the model's efficacy across different populations and settings. They suggest integrating this prediction tool within electronic health records to help clinicians during pre-colonoscopy assessments.
Healthcare professionals, especially those managing outpatient colonoscopy patients, are encouraged to adopt such predictive frameworks, which can lead to enhanced colonoscopy success rates and potentially lower associated risks of complications arising from poor preparation.