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Record W2165410879 · doi:10.1182/blood.v99.9.3102

How we diagnose and treat deep vein thrombosis

2002· review· en· W2165410879 on OpenAlexaff
Jack Hirsh, Agnes Lee

Bibliographic record

VenueBlood · 2002
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsMedicineVenographyDeep veinThrombosisPre- and post-test probabilityThrombophiliaLow molecular weight heparinVenous thrombosisHeparinRadiologySurgeryD-dimerVeinClinical trialAnticoagulantInternal medicine

Abstract

fetched live from OpenAlex

Making a diagnosis of deep vein thrombosis (DVT) requires both clinical assessment and objective testing because the clinical features are nonspecific and investigations can be either falsely positive or negative. The initial step in the diagnostic process is to stratify patients into high-, intermediate-, or low-risk categories using a validated clinical model. When the clinical probability is intermediate or high and the venous ultrasound result is positive, acute symptomatic DVT is confirmed. Similarly, when the probability is low and the ultrasound result is normal, DVT is ruled out. A low clinical probability combined with a negative D-dimer result can also be used to rule out DVT, thereby obviating the need for ultrasonography. In contrast, when the clinical assessment is discordant with the results of objective testing, serial venous ultrasonography or venography is required to confirm or refute a diagnosis of DVT. Once a patient is diagnosed with an acute DVT, low-molecular-weight heparin (LMWH) is the agent of choice for initial therapy and oral anticoagulant therapy is the standard for long-term secondary prophylaxis. Therapy should continue for at least 3 months; the decision to continue treatment beyond 3 months is made by weighing the risks of recurrent thrombosis and anticoagulant-related bleeding, and is influenced by patient preference. Screening for associated thrombophilia is not indicated routinely, but should be performed in selected patients whose clinical features suggest an underlying hypercoagulable state. Several new anticoagulants with theoretical advantages over existing agents are undergoing evaluation in phase 3 studies in patients with venous thromboembolism.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.306
Teacher spread0.250 · 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

Citations178
Published2002
Admission routes1
Has abstractyes

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