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Low–molecular-weight Heparin and Recurrent Placenta-mediated Pregnancy Complications: A Meta-Analysis of Individual Patient Data From Randomized Controlled Trials

2017· article· en· W2746610066 on OpenAlexaff
Marc Rodger, Jean‐Christophe Gris, Johanna I.P. de Vries, Ida Martinelli, É. Rey, E Schleußner, Saskia Middeldorp, Risto Kaaja, Nicole Langlois, Tim Ramsay, R Mallick, Shannon M. Bates, Carolien N. H. Abheiden, Annalisa Perna, David Petroff, Paulien de Jong, Marion E. van Hoorn, P.D. Bezemer, Alain Mayhew

Bibliographic record

VenueObstetric Anesthesia Digest · 2017
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicinePlacental abruptionObstetricsPreeclampsiaPregnancyMeta-analysisLow molecular weight heparinPlacentaRandomized controlled trialSmall for gestational ageHeparinGestational ageFetusSurgeryInternal medicine

Abstract

fetched live from OpenAlex

( Lancet . 2016;388:2629–2641) Placenta-mediated pregnancy complications include preeclampsia, birth of a small for gestational age (SGA) neonate, placental abruption, and late pregnancy loss. They are significant contributors to maternal and neonatal morbidity and mortality. Patients experiencing these complications are also at risk of placenta-mediated complications occurring in subsequent pregnancies. Effective preventive measures for these complications are generally lacking. The current investigators had previously published a study-level meta-analysis that indicated low–molecular-weight heparin (LMWH) could reduce the risk of recurrence. However, there was significant heterogeneity in that study so they decided to perform an individual patient data meta-analysis to evaluate the efficacy of LMWH to prevent recurrent placenta-mediated complications in subsequent pregnancies.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.142
GPT teacher head0.358
Teacher spread0.216 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

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