Early probiotics to prevent childhood metabolic syndrome: A systematic review
Bibliographic record
Abstract
AIM: To conduct a systematic review of studies on early probiotic supplementation to prevent childhood metabolic syndrome (MS). METHODS: Using the Cochrane systematic review strategy we searched PubMed, EMBASE, CENTRAL, CINAHL, and the conference proceedings of the Pediatric American Society meetings and trial registries in December 2014. Randomised controlled trials (RCTs) and non RCTs of probiotic supplementation to the mother and/or infant for a minimum duration of 4 wk were selected. Of these, studies that reported on MS or its components (obesity, raised blood pressure, hyperglycemia, dyslipidemia) in children between 2-19 years were to be eligible for inclusion in the review. Risk of bias (ROB) in selected RCTs and quality assessment of non-RCT studies were to be assessed by the Cochrane ROB assessment table and New Castle Ottawa scale. RESULTS: There were no studies on early probiotic administration for prevention of childhood MS (CMS). Follow up studies of two placebo controlled RCTs (n = 233) reported on the effects of early probiotics on one or more components of MS in children aged 2-19 years. Meta-analysis of those two studies could not be performed due to differences in the patient population, type of outcomes studied and the timing of their assessment. Assessment of childhood metabolic outcomes was not the primary objective of these studies. The first study that assessed the effects of prenatal and postnatal supplementation of Lactobacillus rhamnosus GG on body mass index till 10 years, did not report a significant benefit. In the second study, Lactobacillus paracasei 19 was supplemented to healthy term infants from 4-13 mo. No significant effect on body mass index, body composition or metabolic markers was detected. CONCLUSION: Current evidence on early probiotic administration to prevent CMS is inadequate. Gaps in knowledge need to be addressed before large RCTs can be planned.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".