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Record W2127375404 · doi:10.1586/erc.10.169

Venous thromboembolism in pregnancy

2010· review· en· W2127375404 on OpenAlexaff
Wee‐Shian Chan

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2010
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsWomen's College HospitalUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicinePregnancyPulmonary embolismVenous thromboembolismVenous thrombosisIntensive care medicineThrombosisDiseaseObstetricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

The risk of venous thromboembolism is increased during pregnancy. Although the absolute overall risk of deep venous thrombosis (DVT) or pulmonary embolism (PE) in pregnancy is low, clinicians are highly vigilant to the development of this disease in pregnancy because of the severe consequences to both mother and child if this condition is not diagnosed, treated and prevented. Although prompt recognition and diagnosis of DVT or PE is critical to reduce maternal morbidity, diagnosis of both DVT and PE currently relies on data from studies in nonpregnant patients. However, there are some recent studies offering new insights in this area. The development of venous thromboembolism during pregnancy is influenced by inherent patient risk factors, pregnancy-associated risk factors, and the mode and type of delivery. The degree of risk increase from these factors individually and in combination, to warrant routine thromboprophylaxis, weighed against bleeding risks, is not yet defined. With increased use of assisted reproductive techniques to achieve pregnancy, clinicians must also be vigilant to the development of venous thrombosis in early pregnancy, occurring in unusual sites such as the upper extremities.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.043
GPT teacher head0.363
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations69
Published2010
Admission routes1
Has abstractyes

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