Efficacy of AI-Assisted Personalized Microbiome Modulation by Diet in Functional Constipation: A Randomized...

Area of Science:

• Gastroenterology
• Microbiome Research
• Artificial Intelligence in Medicine

Background:

• Conventional treatments for functional constipation (FC) show limited efficacy.
• Individualized dietary interventions targeting the gut microbiome may offer a novel therapeutic approach for FC.

Purpose of the Study:

• To investigate the impact of microbiome modulation through a customized diet on chronic constipation.
• To compare the efficacy of an AI-assisted personalized diet versus conventional therapy for functional constipation.

Main Methods:

• Fifty patients with functional constipation (Rome IV criteria) were randomized into a control group (conventional treatment) and a study group.
• The study group received an individualized diet guided by microbiome analysis and a soft computing system.
• Outcomes measured after 6 weeks included complete bowel movements per week (CBMpW) and Patient Assessment of Constipation-Quality of Life (PAC-QoL) scores.

Main Results:

• The AI-assisted customized diet led to a 2.5-fold increase in CBMpW (1.7 to 4.3) and an 83% achievement of >3 CBMpW.
• Patient satisfaction scores increased fourfold in the study group.
• Significant improvements in PAC-QoL scores (>50% improvement) were observed in 88% of the study group versus 40% in the control group (p=0.001).

Conclusions:

• AI-assisted customized diets based on individual microbiome analysis demonstrate superior efficacy in treating functional constipation compared to conventional therapies.
• This approach significantly improves patient-reported outcomes, including bowel movement frequency and quality of life.