RESUMO
INTRODUCTION: Most patients with irritable bowel syndrome (IBS) and dual-diagnosis IBS and inflammatory bowel disease (IBD) report that symptoms originate from or are exacerbated by trigger foods. Despite patient interest and need, there is no consensus on what diet is optimal. Popular diets have notable limitations including cost, length, implementation complexity, and lack of personalization. METHODS: This pilot study evaluated the feasibility, desirability, and effect on gastrointestinal symptoms of a digitally delivered personalized elimination diet for patients with IBS and comorbid IBS/IBD, powered by machine learning. Participants were recruited online and were provided access to a digital personalized nutrition tool for 9 weeks (N = 37; IBS only = 16, Crohn's disease and IBS = 9, and ulcerative colitis and IBS = 12). RESULTS: Significant symptom improvement was seen for 81% of participants at study midpoint and persisted for 70% at end point, measured by the relevant symptom severity score (IBS symptom severity score, Patient Simple Clinical Colitis Activity Index, or Mobile Health Index for Crohn's disease). Clinically significant symptom improvement was observed in 78% of participants at midpoint and 62% at end point. Twenty-five participants (67.6%) achieved total symptomatic resolution by the end of study. Patient-reported quality of life improved for 89% of participants. Ninety-five percentage daily engagement, 95% retention, 89% adherence and 92% satisfaction with the program were reported. DISCUSSION: Dietary elimination can improve symptoms and quality of life in patients with IBS and comorbid IBS/IBD. Digital technology can personalize dietary interventions and improve adherence. Randomized controlled trials are warranted.