Pregnancy outcomes in women taking probiotics or prebiotics: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Probiotics are living microorganisms that, when administered in adequate amounts, confer a health benefit. It has been speculated that probiotics might help prevent preterm birth, but in two previous systematic reviews possible major increases in this risk have been suggested. Our objective was to perform a systematic review and meta-analysis of the risk of preterm birth and other adverse pregnancy outcomes in pregnant women taking probiotics, prebiotics or synbiotics. Methods: We searched six electronic databases (MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, Web of Science's Core collection and BIOSIS Preview) up to September 2016 and contacted authors for additional data. We included randomized controlled trials in which women with a singleton pregnancy received a probiotic, prebiotic or synbiotic intervention. Two independent reviewers extracted data using a piloted form and assessed the risk of bias using the Cochrane risk of bias tool. We used random-effects meta-analyses to pool the results. Results: We identified 2574 publications, screened 1449 non-duplicate titles and abstracts and read 160 full text articles. The 49 publications that met our inclusion criteria represented 27 studies. No study used synbiotics, one used prebiotics and the rest used probiotics. Being randomized to take probiotics during pregnancy neither increased nor decreased the risk of preterm birth < 34 weeks (RR 1.03, 95% CI 0.29-3.64, I 2 0%, 1017 women in 5 studies), preterm birth < 37 weeks (RR 1.08, 95% CI 0.71-1.63, I 2 0%, 2484 women in 11 studies), or most of our secondary outcomes, including gestational diabetes mellitus. Conclusions: We found no evidence that taking probiotics or prebiotics during pregnancy either increases or decreases the risk of preterm birth or other infant and maternal adverse pregnancy outcomes. Trial registration: We prospectively published the protocol for this study in the PROSPERO database (CRD42016048129).
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it