Consumo de cafeína: o que aconselhar na preconceção e gravidez?
Bibliographic record
Abstract
Objective: To determine if there is a relationship between caffeine consumption during preconception and pregnancy and the occurrence of spontaneous abortion or stillbirth in healthy women. Data sources: MEDLINE database, National Guideline Clearinghouse, Canadian Medical Association Practice Guidelines Infobase, Cochrane Library, Bandolier, DARE, Trip Database, and Index of Portuguese medical journals. Methods: An evidence based review of relevant scientific papers published within the past five years (from 01/08/2010 to 31/08/2015), in English, French, Italian, Spanish and Portuguese was conducted. The MESH terms used were ‘caffeine’, ‘spontaneous abortion’ and ‘fetal death’. To evaluate the levels of evidence (LE) and strength of recommendation, the authors used the Strength of recommendation taxonomy of the American Family Physician. Results: The search revealed 84 papers, four of which were included in this survey. We included three systematic reviews (all with LE 2) and one prospective cohort study (LE 1). These papers show an increased occurrence of spontaneous abortion or stillbirth with moderate-to-high consumption of caffeine (over 100-150mg/day) during pregnancy. There is insufficient evidence for an association between these adverse events and caffeine consumption during preconception. Conclusions: Moderate to high caffeine consumption during pregnancy increases the risk of spontaneous abortion and stillbirth (Strength of recommendation B). We recommend that caffeine consumption during this period should be reduced (
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 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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".