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Updated: Dec 12, 2025

Fecal Microbiota Transplantation via Colonoscopy for Recurrent C. difficile Infection
Published on: December 8, 2014
Clinical Predictors of response to Faecal Microbiota Transplantation in patients with active ulcerative colitis
Ajit Sood1, Arshdeep Singh1, Ramit Mahajan1
1Internal Medicine, DM Gastroenterology, Department of Gastroenterology, Dayanand Medical College, Ludhiana, Punjab, India.
Background:
Fecal Microbiota Transplantation (FMT) has been shown to be effective for induction of remission in patients with active ulcerative colitis (UC). At present, clinical factors impacting the response to FMT in UC remain unclear.
Methods:
Patients with active UC treated with multisession FMT via colonoscopy at weeks 0, 2, 6, 10, 14, 18, and 22, were analysed. Response to FMT was defined as achievement of corticosteroid free clinical remission at week 30. Patient and disease characteristics were evaluated to determine the predictors of response to FMT.
Results:
Out of 140 patients with active UC treated with FMT, 93 patients [mean age 34.96±11.27 years, 62.36% males (n=58), mean Mayo clinic score 8.07±2.00] who completed the multi-session FMT protocol were analysed. Fifty-seven (61.29%) patients achieved clinical remission. Younger age (OR for age 0.93, 95% CI 0.89-0.97, p=0.001), moderate (Mayo clinic score 6-9) disease severity (OR 3.01, 95% CI 1.12 to 8.06, p=0.025) and endoscopic Mayo score 2 (OR 5.55, 95% CI 2.18-14.06, p<0.001) were significant predictors of remission on univariate analysis. Younger age, disease extent E2 and endoscopic mayo score 2 (OR 0.925, 95% CI 0.88-0.97, p=0.002; OR 2.89, 95% CI 1.01-8.25, p=0.04 and OR 8.43, 95% CI 2.38-29.84, p=0.001, respectively) were associated with clinical remission on multivariate logistic regression. A mathematical model (nomogram) was developed for estimating the probability of remission with FMT protocol.
Conclusion:
Younger age, disease extent E2, and endoscopic mayo score 2 significantly predict achievement of clinical remission with FMT in active UC. The prediction model can help in selecting individuals for FMT. Validation in larger cohorts is needed.
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