Predictive Feasibility Of Colonoscopy Without Sedation Using A Nomogram Model.

Area of Science:

• Gastroenterology
• Medical Diagnostics
• Public Health

Background:

• Colorectal cancer is a significant global health issue.
• Colonoscopy is a vital screening method for colorectal cancer.
• Unsedated colonoscopy offers patient benefits but faces challenges in procedure completion.

Purpose of the Study:

• To identify risk factors associated with unsedated colonoscopy incompletion.
• To develop a predictive model for identifying patients at high risk of unsedated colonoscopy incompletion.
• To enhance the completion rates and patient experience of unsedated colonoscopies.

Main Methods:

• Retrospective analysis of 745 patients undergoing unsedated colonoscopy.
• Division of patients into completion (n=670) and incompletion (n=75) groups.
• Univariate and multivariate logistic regression analyses to identify risk factors; nomogram model development and validation.

Main Results:

• Constipation (OR=4.981), high anxiety (OR=8.499), and examination by less experienced physicians (OR=3.319) were independent risk factors for incompletion.
• The developed nomogram showed good predictive accuracy (Hosmer-Lemeshow: χ²=4.561, p=0.683) and discriminative ability (AUC=0.886).

Conclusions:

• A predictive model incorporating constipation, anxiety, and physician experience can identify patients likely to incompletely undergo unsedated colonoscopy.
• Preoperative identification of high-risk patients allows for optimized procedural planning, potentially including sedation or targeted interventions.
• Improving unsedated colonoscopy completion rates can enhance patient adherence to screening protocols and improve overall outcomes.