Impact of Lactobacillus GG on weight loss in post-bariatric surgery patients: a randomized, double-blind clinical trial
Nasir, M.; Stone, S.; Mahoney, I.; Chang, J.; Kim, J.; Shah, S.; McDermott, L.; Sebastiani, P.; Tighiouart, H.; Snydman, D.; Doron, S.
Show abstract
Introduction and ObjectivesThere is increasing evidence suggesting the impact of human gut microbiota on digestion and metabolism. It is hypothesized that the microbiome in obese subjects is more efficient than that in lean subjects in absorbing energy from food, thus predisposing to weight gain. A transformation in gut microbiota has been demonstrated in patients who have undergone bariatric surgery which has been positively associated with post-surgical weight loss. However, there is lack of studies investigating the impact of probiotics on weight loss in post-bariatric surgery patients. The objectives of our study were to investigate the impact of a probiotic, Lactobacillus GG (LGG), on weight loss and quality of life in patients who have undergone bariatric surgery. MethodsThe study was registered with ClinicalTrials.gov NCT01870544. Subjects were randomized to receive either LGG or placebo capsules. Percent total weight loss at their post-operative visits was calculated and differences between the two groups were tested using a t-test with unequal variances. The effect of LGG on Gastrointestinal Quality of Life Index (GIQLI) scores was estimated using a mixed model repeated measures model. ResultsThe mean rate of change in percent total weight loss at the 30-day post-operative visit for the placebo and treatment groups was 0.098 and 0.079 (p = 0.41), respectively, whereas that at the 90-day post-operative visit was 0.148 and 0.126 (p = 0.18), respectively. The difference in GIQLI scores on 30-day and 90-day visits were 0.5 (-7.1, 8.0), p=0.91 and 3.7 (-4.9, 12.3), p=0.42, respectively. LGG was recovered from the stools of 3 out of 5 subjects in the treatment group. ConclusionWe did not appreciate a significant difference in the mean rate of weight loss or GIQLI scores between the groups who received LGG versus placebo. This study demonstrated survival of lactobacillus during transit through the gastrointestinal tract.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Effects of a spore-forming probiotic blend on bowel habits and physical well-being in adults with functional constipation: a randomized, double-blind, placebo-controlled trial 95%
- Role of CCK1 receptor in metabolic benefits of intestinal enteropeptidase inhibition in mice 93%
- A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection 93%
Similar papers in this journal
- Effect of a novel food rich in miraculin on the intestinal microbiome of malnourished patients with cancer and dysgeusia 94%
- Efficacy and Safety of Habitual Consumption of a Food Supplement Containing Miraculin in Malnourished Cancer Patients: the CLINMIR Pilot Study 93%
- Multi-strain fermented milk promotes gut microbiota recovery after Helicobacter pylori therapy: a randomised, controlled trial 92%
Similar papers in this journal
- Effect of ginger supplementation on the fecal microbiome in subjects with prior colorectal adenoma 95%
- Assessment of Gut Microbial β-Glucuronidase and β-Glucosidase Activity in Women with Polycystic Ovary Syndrome 93%
- Effects of different environmental intervention durations on the intestinal mucosal barrier and the brain-gut axis in rats with colorectal cancer 93%
Similar papers in this journal
- Efficacy of AI-assisted personalized microbiome modulation by diet in functional constipation: a randomized controlled trial 96%
- The development of a multidisciplinary care pathway for patients with inflammatory bowel disease before, during and after pregnancy 91%
- Changes in back pain scores after bariatric surgery in obese patients: A systematic review and meta-analysis 91%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.