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Record W2599857884 · doi:10.32385/rpmgf.v33i1.12024

Consumo de cafeína: o que aconselhar na preconceção e gravidez?

2017· article· pt· W2599857884 on OpenAlexaboutno aff
Filipa Matias, A Jeri, Sofia Esmeraldo Rodrigues

Bibliographic record

VenueRevista Portuguesa de Clínica Geral · 2017
Typearticle
Languagept
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.054
GPT teacher head0.373
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

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