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PREVALENCE OF FACTOR V LEIDEN AND ACTIVATED PROTEIN C RESISTANCE IN CENTRAL RETINAL VEIN OCCLUSION

2001· article· en· W2052902924 on OpenAlexafffund
T. MARK JOHNSON, Sherif El-Defrawy, William Hodge, Brian C. Leonard, Peter J. Kertes, Sherryl A. Taylor, David Lillicrap

Bibliographic record

VenueRetina · 2001
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsCentral retinal vein occlusionFactor V LeidenMedicineActivated protein C resistanceRisk factorFactor VOdds ratioThrombosisDeep veinInternal medicineProtein CConfidence intervalVenous thrombosisSurgeryOphthalmologyGastroenterologyRetinal

Abstract

fetched live from OpenAlex

PURPOSE: Factor V Leiden is a common inherited mutation that is a significant risk factor for deep vein thrombosis. It results in resistance to activated protein C (APC). The association between factor V Leiden and central retinal vein occlusion (CRVO) remains controversial. This study was designed to determine the prevalence of APC resistance and the factor V Leiden mutation in patients with CRVO in a controlled study. METHODS: The study was designed as a case control study conducted in a tertiary care retina practice. The prevalence of APC resistance and factor V Leiden was determined by genetic testing of blood samples obtained from patients with CRVO and clinic control patients. RESULTS: Factor V Leiden was identified in 2.3% of patients with CRVO and 3.5% of clinic control patients. There was no significant association between the presence of factor V Leiden and CRVO (odds ratio, 1.13; 95% confidence interval, 0.65-1.98; P = 0.66). CONCLUSION: Factor V Leiden does not appear to be associated with CRVO. Routine screening of patients with CRVO does not appear to be warranted.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.270
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 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".

Quick stats

Citations28
Published2001
Admission routes2
Has abstractyes

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