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Record W4210522378 · doi:10.1177/1753495x221074616

VTE prophylaxis in pregnant people with chronic physical disability: Data from a physicians survey and the need for guidance

2022· article· en· W4210522378 on OpenAlexaffabout
Sajida Kazi, Anne McLeod, Anne Berndl

Bibliographic record

VenueObstetric Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreSinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsMedicinePregnancyFamily medicineCross-sectional studySpinal cord injuryPostpartum periodObstetricsPhysical therapySpinal cordPsychiatry

Abstract

fetched live from OpenAlex

Background: International guidelines recommend risk assessment during the antepartum and postpartum period to inform VTE prophylaxis. We aimed to evaluate physicians' approach to VTE prophylaxis of women with chronic physical disability (CPD) during pregnancy. Methods: A cross-sectional study consisting of a self-administered electronic questionnaire was sent to specialists across Canada. Results: Seventy-three participants responded to the survey, and 55 (75.3%) completed the survey including 33 (60%) Maternal Fetal Medicine (MFM) specialists and 22 (40%) Internal Medicine (IM) specialists including physicians with an interest in Obstetric Medicine. Our study shows considerable variation in VTE thromboprophylaxis during pregnancy with CPD. Most respondents favoured antepartum (67.3%) and postpartum (65.5%) VTE prophylaxis for pregnancies within a year of spinal cord injury. Conclusions: In order to better manage this complex population, CPD should be considered as a risk factor for development of VTE.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.068
GPT teacher head0.357
Teacher spread0.289 · 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 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

Citations3
Published2022
Admission routes2
Has abstractyes

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