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Record W2093679016 · doi:10.1136/ebm.6.4.107

Review: antiplatelet drugs reduce pre-eclampsia, preterm birth, and stillbirth or neonatal death

2001· article· en· W2093679016 on OpenAlexaff
ME Hannah

Bibliographic record

VenueEvidence-Based Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEclampsiaMedicineAspirinPlaceboObstetricsPregnancyInternal medicineGynecologyPathology

Abstract

fetched live from OpenAlex

(2001) BMJ 322, 329. Duley L, Henderson-Smart D, Knight M, et al. . Antiplatelet drugs for prevention of pre-eclampsia and its consequences: systematic review. . Feb 10; . : . –33. . [OpenUrl][1][Abstract/FREE Full Text][2] QUESTION: In pregnant women at risk for pre-eclampsia, how effective are antiplatelet drugs in preventing pre-eclampsia and its complications? Studies were identified by searching the Cochrane Pregnancy and Childbirth Group register of trials, the Cochrane Controlled Trials Register, and EMBASE/Excerpta Medica (1994–9) and by handsearching conference abstracts. Studies were selected if they were randomised controlled trials comparing antiplatelet drugs with placebo or no antiplatelet drug in women at risk for developing pre-eclampsia. Exclusion criteria were having no clinical data available, inadequate randomisation, <80% follow up of patients, or having participants at very low risk for pre-eclampsia. Data were extracted on study validity (allocation concealment), patient risk for developing pre-eclampsia (high or moderate), length of gestation (< or ≥20 wks), dose of aspirin (≤75 mg or >75 … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft.stitle%253DBMJ%26rft.issn%253D0007-1447%26rft.aulast%253DDuley%26rft.auinit1%253DL.%26rft.volume%253D322%26rft.issue%253D7282%26rft.spage%253D329%26rft.epage%253D333%26rft.atitle%253DAntiplatelet%2Bdrugs%2Bfor%2Bprevention%2Bof%2Bpre-eclampsia%2Band%2Bits%2Bconsequences%253A%2Bsystematic%2Breview%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.322.7282.329%26rft_id%253Dinfo%253Apmid%252F11159655%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=322/7282/329&atom=%2Febmed%2F6%2F4%2F107.atom

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.004
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0210.002

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 head0.061
GPT teacher head0.337
Teacher spread0.277 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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
Published2001
Admission routes1
Has abstractyes

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