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Record W2056369632 · doi:10.1097/ccm.0000000000000713

Failure of Anticoagulant Thromboprophylaxis

2014· article· en· W2056369632 on OpenAlexafffund
Wendy Lim, Maureen O. Meade, François Lauzier, Ryan Zarychanski, Sangeeta Mehta, François Lamontagne, Peter Dodek, Lauralyn McIntyre, Richard Hall, Diane Heels‐Ansdell, Robert Fowler, Menaka Pai, Gordon Guyatt, Mark Crowther, Theodore E. Warkentin, P.J. Devereaux, Stephen D. Walter, John Muscedere, Margaret S. Herridge, Alexis F. Turgeon, William Geerts, Simon Finfer, Michael J. Jacka, Otávio Berwanger, Marlies Ostermann, Ismael Qushmaq, Jan O. Friedrich

Bibliographic record

VenueCritical Care Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsSt. Thomas HospitalUniversity of AlbertaQuebec - Clinical Research Organization in CancerQueen Elizabeth II Health Sciences CentreUniversity of OttawaUniversity of British ColumbiaUniversité de SherbrookeUniversity of TorontoCARE CanadaUniversity of ManitobaMcMaster UniversityThe Quebec Population Health Research NetworkQueen's UniversitySt. Paul's Hospital
FundersCanadian Institutes of Health ResearchIntensive Care SocietySanofiBayer HealthCareHeart and Stroke Foundation of CanadaGlaxoSmithKline
KeywordsMedicinePulmonary embolismHazard ratioDeep veinBody mass indexLow molecular weight heparinHeparinAnticoagulantThrombosisInternal medicineVenous thrombosisSurgeryAnesthesiaConfidence interval

Abstract

fetched live from OpenAlex

OBJECTIVES: To identify risk factors for failure of anticoagulant thromboprophylaxis in critically ill patients in the ICU. DESIGN: Multivariable regression analysis of thrombosis predictors from a randomized thromboprophylaxis trial. SETTING: Sixty-seven medical-surgical ICUs in six countries. PATIENTS: Three thousand seven hundred forty-six medical-surgical critically ill patients. INTERVENTIONS: All patients received anticoagulant thromboprophylaxis with low-molecular-weight heparin or unfractionated heparin at standard doses. MEASUREMENTS AND MAIN RESULTS: Independent predictors for venous thromboembolism, proximal leg deep vein thrombosis, and pulmonary embolism developing during critical illness were assessed. A total of 289 patients (7.7%) developed venous thromboembolism. Predictors of thromboprophylaxis failure as measured by development of venous thromboembolism included a personal or family history of venous thromboembolism (hazard ratio, 1.64; 95% CI, 1.03-2.59; p = 0.04) and body mass index (hazard ratio, 1.18 per 10-point increase; 95% CI, 1.04-1.35; p = 0.01). Increasing body mass index was also a predictor for developing proximal leg deep vein thrombosis (hazard ratio, 1.25; 95% CI, 1.06-1.46; p = 0.007), which occurred in 182 patients (4.9%). Pulmonary embolism occurred in 47 patients (1.3%) and was associated with body mass index (hazard ratio, 1.37; 95% CI, 1.02-1.83; p = 0.035) and vasopressor use (hazard ratio, 1.84; 95% CI, 1.01-3.35; p = 0.046). Low-molecular-weight heparin (in comparison to unfractionated heparin) thromboprophylaxis lowered pulmonary embolism risk (hazard ratio, 0.51; 95% CI, 0.27-0.95; p = 0.034) while statin use in the preceding week lowered the risk of proximal leg deep vein thrombosis (hazard ratio, 0.46; 95% CI, 0.27-0.77; p = 0.004). CONCLUSIONS: Failure of standard thromboprophylaxis using low-molecular-weight heparin or unfractionated heparin is more likely in ICU patients with elevated body mass index, those with a personal or family history of venous thromboembolism, and those receiving vasopressors. Alternate management or incremental risk reduction strategies may be needed in such patients.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.313
Teacher spread0.295 · 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

Citations126
Published2014
Admission routes2
Has abstractyes

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