Effects of restricted caffeine intake by mother on fetal, neonatal and pregnancy outcome
Bibliographic record
Abstract
BACKGROUND: Maternal caffeine consumption during pregnancy may have adverse effects on fetal, neonatal and maternal outcomes. OBJECTIVES: This review investigates the effects of restricting caffeine intake by mothers on fetal, neonatal and pregnancy outcomes. SEARCH METHODS: We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (31 October 2012), scanned bibliographies of published studies and corresponded with investigators. SELECTION CRITERIA: Randomised controlled trials (RCTs) including quasi-RCTs investigating the effect of caffeine and/or supplementary caffeine versus restricted caffeine intake or placebo on pregnancy outcomes. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trial quality and extracted data. MAIN RESULTS: Two studies met the inclusion criteria but only one contributed data for the prespecified outcomes. Caffeinated instant coffee (568 women) was compared with decaffeinated instant coffee (629 women) and it was found that reducing the caffeine intake of regular coffee drinkers (3+ cups/day) during the second and third trimester by an average of 182 mg/day did not affect birthweight or length of gestation. AUTHORS' CONCLUSIONS: There is insufficient evidence to confirm or refute the effectiveness of caffeine avoidance on birthweight or other pregnancy outcomes. There is a need to conduct high-quality, double-blinded RCTs to determine whether caffeine has any effect on pregnancy outcome.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".