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Record W4304692081 · doi:10.26443/mjm.v21i1.851

Approach to: Venous Thromboembolism

2022· article· en· W4304692081 on OpenAlexaffvenueabout
S. Ramdani

Bibliographic record

VenueMcGill Journal of Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineTachypneaPulmonary embolismThrombosisVenous thrombosisDeep veinPeripheral edemaTachycardiaPulmonary edemaPhysical examinationEdemaVenous thromboembolismVenographySigns and symptomsChest painCardiologyIntensive care medicineSurgeryInternal medicineLungAdverse effect

Abstract

fetched live from OpenAlex

Venous thromboembolisms can manifest as a spectrum of diseases and complications, such as deep vein thrombosis (DVT) and pulmonary embolism (PE), as a consequence of hypercoagulability, endothelial damage and/or venous stasis. DVT can present as localized pain or heaviness, unilateral edema, dilatation of superficial nonvaricose veins, a palpable cord or Homans’s sign. Symptoms of PE include acute or worsening shortness of breath and pleuritic chest pain while physical examination may be remarkable for tachycardia and tachypnea. However, given their non-specificity, using these signs and symptoms alone allows for poor differentiation between VTE and other entities. This review will focus on a multi-step diagnostic tree allowing for evidence-based interpretation of tests following a determined pre-test probability (PTP), as per Thrombosis Canada recommendations and ASH clinical guidelines. An introduction to VTE in Pediatrics and pregnancy will also be discussed.

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)0.000
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.075
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0750.057

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 head0.036
GPT teacher head0.292
Teacher spread0.255 · 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
GenreOther

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

Citations0
Published2022
Admission routes3
Has abstractyes

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