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Topics/Small and Large Bowel/Defecography Metrics in Chronic Constipation: Gastroenterology | March 2026

Defecography Metrics in Chronic Constipation: Gastroenterology | March 2026

Clinical knowledge base curated and reviewed by GastroAGI TeamLast updated March 1, 2026

Quick Answer

Introduction Chronic constipation is frequently evaluated using physiologic testing such as fluoroscopic defecography and high-resolution anorectal manometry to identify pelvic floor dysfunction and evacuation disorders. A recent study combined these techniques to define a synchronous “proctomanometric” signature of constipation.


Introduction

Chronic constipation is frequently evaluated using physiologic testing such as fluoroscopic defecography and high-resolution anorectal manometry to identify pelvic floor dysfunction and evacuation disorders. A recent study combined these techniques to define a synchronous “proctomanometric” signature of constipation. However, concerns have been raised about the methodological assumptions used to classify evacuation patterns. Accurate definitions and patient phenotyping are crucial because diagnostic thresholds and analytic models can strongly influence the interpretation of anorectal physiology and the clinical diagnosis of pelvic floor dyssynergia.

Summary

The correspondence highlights three methodological issues. First, the study defined “successful evacuation” as expelling ≥25% of rectal barium within three attempts lasting ≤17 seconds, a threshold that may be overly restrictive and physiologically unrealistic. Prior studies demonstrate that even healthy individuals may take >30 seconds to evacuate similar volumes, suggesting that strict time limits could generate false-positive diagnoses of impaired evacuation. Second, the study combined functional constipation (FC) and constipation-predominant IBS (IBS-C) using older Rome III criteria, despite Rome IV guidelines recognizing important pathophysiologic differences between these conditions. Pooling them may confound interpretation of anorectal pressure patterns. Third, the study applied machine-learning models with many predictors but limited sample size, raising concerns about overfitting and lack of reproducibility.

The author proposes more physiologic evacuation metrics, Rome IV–based patient stratification, and more robust statistical validation to improve translation of these findings into clinical practice.

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