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Clinical Assessment and <scp>d</scp>-dimer Testing in Deep Venous Thrombosis

2002· article· en· W2040485253 on OpenAlexaffabout
Clive Kearon

Bibliographic record

VenueAnnals of Internal Medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineVenous thrombosisD-dimerThrombosisInternal medicine

Abstract

fetched live from OpenAlex

Letters3 September 2002Clinical Assessment and d-dimer Testing in Deep Venous ThrombosisClive Kearon, MB, PhD and Jeffrey S. Ginsberg, MDClive Kearon, MB, PhDMcMaster University; Hamilton, Ontario L8V 1C3, CanadaSearch for more papers by this author and Jeffrey S. Ginsberg, MDMcMaster University; Hamilton, Ontario L8V 1C3, CanadaSearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-137-5_Part_1-200209030-00027 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:Dr. Wakai is concerned that other clinical centers, and particularly emergency departments, may have difficulty replicating the results of our study. We believe that the two limitations he discusses, which are common to most diagnostic tests, are interrelated and can be readily overcome. In contrast to other d-dimer assays, the assay we used in our study, SimpliRED (AGEN Biomedical, Ltd., Brisbane, Australia), can be performed at the bedside on a fingerstick sample and yields a result within minutes. At our institution, a nurse or a technician with previous training performs the test; we estimate that it takes about ...References1. Chunilal SD, Brill-Edwards PA, Stevens PB, Joval JP, McGinnis JA, Rupwate M, et al . The sensitivity and specificity of a red blood cell agglutination d-dimer assay for venous thromboembolism when performed on venous blood. Arch Intern Med. 2002;162:217-20. [PMID: 11802756] CrossrefMedlineGoogle Scholar2. Turkstra F, van Beek EJ, Büller HR. Observer and biological variation of a rapid whole blood d-dimer test. Thromb Haemost. 1998;79:91-3. [PMID: 9459330] CrossrefMedlineGoogle Scholar3. Farrell S, Hayes T, Shaw M. A negative SimpliREDd-dimer assay result does not exclude the diagnosis of deep vein thrombosis or pulmonary embolus in emergency department patients. Ann Emerg Med. 2000;35:121-5. [PMID: 10650228] CrossrefMedlineGoogle Scholar4. Perrier A, Desmarais S, Miron MJ, de Moerloose P, Lepage R, Slosman D, et al . Non-invasive diagnosis of venous thromboembolism in outpatients. Lancet. 1999;353:190-5. [PMID: 9923874] CrossrefMedlineGoogle Scholar5. Bates SM, Grand'Maison A, Johnston M, Naguit I, Kovacs MJ, Ginsberg JS. A latex d-dimer reliably excludes venous thromboembolism. Arch Intern Med. 2001;161:447-53. [PMID: 11176771] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: McMaster University; Hamilton, Ontario L8V 1C3, Canada PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoManagement of Suspected Deep Venous Thrombosis in Outpatients by Using Clinical Assessment and d-dimer Testing Clive Kearon , Jeffrey S. Ginsberg , James Douketis , Mark Crowther , Patrick Brill-Edwards , Jeffrey I. Weitz , and Jack Hirsh Clinical Assessment and d-Dimer Testing in Deep Venous Thrombosis Abel Wakai Clinical Assessment and d-Dimer Testing in Deep Venous Thrombosis Abel Wakai Metrics 3 September 2002Volume 137, Issue 5_Part_1Page: 371-372KeywordsBloodD-dimerDeep vein thrombosisEmergency departmentEnzyme linked immunosorbent assayNursesQuality improvementResearch laboratoriesTechniciansVenous thromboembolism ePublished: 3 September 2002 Issue Published: 3 September 2002 CopyrightCopyright © 2002 by American College of Physicians. All Rights Reserved.PDF DownloadLoading ...

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)0.002
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.161
GPT teacher head0.424
Teacher spread0.264 · 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 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".

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Citations0
Published2002
Admission routes2
Has abstractyes

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