Does infant formula containing synbiotics support adequate growth in infants? A meta-analysis and systematic review of randomized controlled trials
Bibliographic record
Abstract
In recent years, several studies have shown that formulas that contain synbiotics, i.e. composed prebiotics and probiotics have been proposed to have a beneficial effect on anthropometric indices. However, the results are inconsistent thus this meta-analysis was performed to assess this effect. PubMed/MEDLINE, Web of Science, SCOPUS, and Embase were systematically searched up to May-2020. Weight gain, length gain, head circumstance gain, weight-for-age z scores, and length-for-age z scores were considered as the outcomes. Weighted mean differences (WMD) with the 95% CI were applied for estimating the combined effect size. Subgroup analysis was performed to specify the source of heterogeneity among studies. Consumption of formulas containing synbiotics did not affect growth significantly in healthy infants (weight gain (WMD = 2.06, 95% CI: − 4.08 to 8.21; p = 0.51), length gain (WMD = − 0.05, 95% CI: − 0.70 to 0.60; p = 0.88), head circumstance (WMD = − 0.28, 95% CI: − 0.66 to 0.11; p = 0.15), on weight-for-age z-scores (WMD = − 0.05, 95% CI: − 0.23 to 0.13; p = 0.57) and length-for-age z-scores (WMD = − 0.16, 95% CI: − 0.50 to 0.19; p = 0.37)). The main results indicate a non-significant increase in infant’s growth following synbiotics supplementation of infant formula. Further large-scale studies are warranted to confirm present findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.033 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".