MétaCan
Menu
Back to cohort
Record W2013336295 · doi:10.1136/pgmj.2005.044107

Prevention of venous thromboembolism in medically ill patients: a clinical update

2006· review· en· W2013336295 on OpenAlexaff
Alexander G.G. Turpie, Alain Leizorovicz

Bibliographic record

VenuePostgraduate Medical Journal · 2006
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsHamilton Health SciencesHamilton General Hospital
Fundersnot available
KeywordsMedicineVenous thromboembolismIntensive care medicineVenous thrombosisSurgeryThrombosis

Abstract

fetched live from OpenAlex

The risk of venous thromboembolism (VTE) in hospitalised medically ill patients is often underestimated, despite the fact that it remains a major cause of preventable morbidity and mortality in this group. It is not well recognised that the risk of VTE in many hospitalised medically ill patients is at least as high as in populations after surgery. This may partly be attributed to the clinically silent nature of VTE in many patients, and the difficulty in predicting which patients might develop symptoms or fatal pulmonary embolism. Two large studies, Prospective Evaluation of Dalteparin Efficacy for Prevention of VTE in Immobilized Patients Trial and prophylaxis in MEDical patients with ENOXaparin, have shown that low-molecular-weight heparins provide effective thromboprophylaxis in medically ill patients, without increasing bleeding risk. Recent guidelines from the American College of Chest Physicians recommend that acutely medically ill patients admitted with congestive heart failure or severe respiratory disease, or those who are confined to bed and have at least one additional risk factor for VTE, should receive thromboprophylaxis.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.403
Teacher spread0.347 · 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.

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

Citations8
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePostgraduate Medical JournalSame topicVenous Thromboembolism Diagnosis and ManagementFrench-language works237,207