Predicting Responsiveness to Biofeedback Therapy Using High-resolution Anorectal Manometry With Integrated...

Area of Science:

• Gastroenterology
• Physiology
• Medical Technology

Background:

• Biofeedback therapy is a common treatment for chronic constipation, particularly for dyssynergic defecation.
• Predicting response to biofeedback therapy using high-resolution anorectal manometry (HRAM) with novel parameters remains underexplored.

Purpose of the Study:

• To develop a predictive model for biofeedback therapy responders using integrated pressurized volume (IPV) parameters derived from HRAM.
• To evaluate the efficacy of IPV parameters in predicting treatment response compared to conventional manometric parameters.

Main Methods:

• Seventy-one female patients with dyssynergic defecation underwent HRAM and biofeedback therapy.
• Three-dimensional IPV parameters were calculated from HRAM profiles during simulated evacuation.
• Partial least squares regression was used to construct a predictive model.

Main Results:

• 77.5% of patients responded to biofeedback therapy.
• Conventional manometric parameters did not significantly differentiate responders from non-responders.
• The IPV-based model achieved an AUC of 0.84, with 85.5% sensitivity and 62.1% specificity.

Conclusions:

• IPV parameters are superior to conventional parameters for predicting biofeedback therapy response in dyssynergic defecation.
• The combination of IPV parameters and partial least squares regression shows promise for personalized treatment strategies.
• IPV parameters provide a more comprehensive understanding of anorectal physiology than traditional methods.