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Protein C and protein S levels can be accurately determined within 24 hours of diagnosis of acute venous thromboembolism

2006· article· en· W2009189029 on OpenAlexaff
M.J. Kovacs, Judy Kovacs, Josdalyne Anderson, Marc Rodger, Karen MacKinnon, Philip S. Wells

Bibliographic record

VenueClinical & Laboratory Haematology · 2006
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsOttawa HospitalLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineConfidence intervalProspective cohort studyProtein SProtein CFalse positive paradoxVenous thromboembolismInternal medicineGastroenterologyThrombosis

Abstract

fetched live from OpenAlex

In the 50% of cases of acute idiopathic venous thromboembolism, laboratory testing for inherited causes is often performed. Most physicians are under the impression that assays for protein C and protein S should not be measured at the time of diagnosis because of a high false positive rate. We performed a prospective cohort study from two outpatient thromboembolism clinics on consecutive patients with an objectively confirmed diagnosis of first acute idiopathic venous thromboembolism. Assays for protein C and protein S were performed prior to the initiation of oral anticoagulation therapy and within 24 h of diagnosis of venous thromboembolism. Abnormal results were repeated when patients discontinued oral anticoagulant therapy. Of 253 patients tested for both protein C and protein S, 229 (91%; 95% confidence interval 87-94%) were negative and 484 of 508 (95%) tests were normal. Of the 24 initial abnormal results, 21 were repeated and 10 (48%; 95% confidence interval 26-70%) were still abnormal. Overall, 97.8% of initial protein C and protein S results were accurate. If protein C and protein S are measured at the time of diagnosis of acute venous thromboembolism, the majority of the results will be normal and false positives are uncommon.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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)0.0000.000

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 head0.059
GPT teacher head0.354
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.

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

Citations25
Published2006
Admission routes1
Has abstractyes

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