Rationale, design, and preliminary results of the Quebec Warfarin Cohort Study
Bibliographic record
Abstract
Over- and undercoagulation with warfarin are associated with hemorrhagic and thromboembolic events, respectively. Genetic and clinical factors affect warfarin response, and the causes of this variability remain unclear. We present descriptive statistics and test for predictors of poor anticoagulation control. The Quebec Warfarin Cohort (QWC) comprises 1059 new warfarin users, with prospective follow-up using telephone questionnaires every 3 months for 1 year, and using healthcare administrative databases (RAMQ and Med-Echo) for 5 years prior to cohort entry and up to 10 years following active patient participation. Genetic material was collected, and genotyping of CYP2C9 and VKORC1 genes was conducted. Measured outcomes included the percentage of time patients spent within therapeutic range, anticoagulation control, warfarin dose, bleeding, and thromboembolic events. We report baseline characteristics and outcomes after 1 year of follow-up. Poor anticoagulation control was defined as time in therapeutic range <60% in the 3- to 12-month interval. Participants had a mean age of 71 years, and 62% were men. The most common indication for warfarin was atrial fibrillation (87%). Mean time in therapeutic range was 56% (±25%) in the 3 months following warfarin initiation, and 70% (±21%) in the 3- to 12-month interval. During follow-up, the rate of stroke or systemic embolism was 1.8 events per 100 person-years; for major bleeding events, 3.3 events per 100 person-years. Independent predictors of poor anticoagulation control were chronic kidney disease, heart failure, dyslipidemia, and age. The QWC represents a good research cohort to investigate clinical and genetic factors in a warfarin-anticoagulated population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".