Impact of regular physical activity on weekly warfarin dose requirement
Bibliographic record
Abstract
Warfarin is an oral anticoagulant agent with a narrow therapeutic index. There is a marked inter- and intra-patient variability in warfarin dose requirement. All factors influencing warfarin response are not known and this study aims to evaluate if regular physical activity (RPA) is a determining factor. RPA level was collected with the Stanford Brief Activity Survey in 1064 incident warfarin users, as part of the Quebec Warfarin Cohort (QWC), and with the Global Physical Activity Questionnaire in 618 patients from the Montreal Heart Institute (MHI) Biobank. Linear regression was performed to model relationship of warfarin dose after 3 months of therapy in the QWC with RPA, while controlling for height, weight, age, CYP2C9 (*2 and *3 alleles) and VKORC1 (*2 allele) genotype. Warfarin dose of prevalent users was modeled in the MHI Biobank for replication. A higher level of physical activity was associated with higher doses of warfarin in both cohorts. In the QWC, physical activity could explain 5.4 % (P < 0.001) and 0.9 % (P = 3.23 × 10(-5)) of variance in dose, in univariate and multivariable models, respectively. Similarly, RPA was found to be associated with 1.7 % (P = 0.0012) and 0.5 % (P = 0.0391) of inter-individual variability in warfarin dose requirement before and after adjustment for other covariables, respectively. RPA is associated with higher warfarin dose requirement. The relevance of clinical recommendations on RPA to maintain a steady response to warfarin should be assessed in further studies.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".