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Healthy Infants clinical trials

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NCT ID: NCT06361719 Not yet recruiting - Healthy Infants Clinical Trials

Efficacy of Two HMOs in Chinese Infants

Start date: May 31, 2024
Phase: N/A
Study type: Interventional

This is a randomized, controlled, double-blind, intervention trial of healthy male and female term infants to evaluate the efficacy of the 2 HMOs on beneficially modulating the gut microbiota, gut maturation, gut barrier integrity, immune response, and other developmental outcomes in healthy Chinese infants. The trial consists of 2 randomized formula-fed groups, and a non-randomized breastfed reference group.

NCT ID: NCT01249911 Not yet recruiting - Healthy Infants Clinical Trials

Lactobacillus Reuteri DSM 17938 and Prevention of Respiratory and Gastrointestinal Infections in Mexican Infants

Start date: January 2011
Phase: Phase 3
Study type: Interventional

Randomized, doble blind, clinical, controlled trial aimed to investigate the role of Lactobacillus reuteri DSM 17938 in the prevention of gastrointestinal and respiratory tract infections in mexican children who attend day care centers. Primary Outcome: The primary outcome will be "days with diarrhoea". Secondary Outcomes: a) Days with respiratory tract infections (RTI); b) Days of absences from day care centre; c) Days of antibiotic use; d) Days of medical office visits or emergency visits; and e) Direct and Indirect costs. Methods: Prospective, randomized, double blind, placebo controlled trial to realize in 260 healthy term infants, born at term (≥36 weeks of gestation), 6 to 36 months old, who will be recruit from Child Care Centers in Mexico and randomly allocated to receive either 1 x 108 colony-forming units of Lactobacillus reuteri DSM 17938 or placebo, each day for 12 weeks, follow up for other additionally 12 weeks of observation. Days with respiratory tract infections (RTI); days of absences from day care centre; days of antibiotic use; days of medical office visits or emergency visits; and direct and Indirect costs will be compare between groups using bi-variate, multiple lineal regression analysis and cost-effectiveness analysis