The Effect of Warfarin Administration Time on Anticoagulation Stability (INRange): A Pragmatic Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE Without supporting evidence, clinicians commonly recommend that warfarin be taken in the evening. We conducted a randomized controlled trial to evaluate the effect of administration time (morning vs evening) on the stability of warfarin’s anticoagulant effect. METHODS A total of 236 primary care physicians serving 54 western Canadian communities mailed letters of invitation to all their warfarin-using patients. Eligible patients were community-dwelling warfarin users (any indication) with at least 3 months of evening warfarin use and no plans for discontinuation. Participants were randomized (by web-based allocation) to morning vs continued evening warfarin ingestion. We used the Rosendaal method to determine the proportion of time within therapeutic range (TTR) of the international normalized ratio (INR) blood test month 2 to 7 postrandomization vs the 6 months prerandomization. The primary outcome was the percent change in proportion of time outside target INR range (with an a priori minimum clinically important difference of ±20%). All analyses were intention to treat. RESULTS Between March 8, 2015 and September 30, 2016, we randomized 109 participants to morning and 108 to evening warfarin use. TTR rose from 71.8% to 74.7% in the morning group, and from 72.6% to 75.6% in the evening group, for a change in TTR of 2.9% in the former vs 3.0% in the latter (difference, –0.1%; P = .97; 95% CI for the difference, –6.1% to 5.9%). The difference in percent change in proportion of time outside the therapeutic INR range (obtained via Hodges-Lehmann estimation of the difference in medians) was 4.4% (P = .62; 95% CI for the difference, –17.6% to 27.3%). CONCLUSIONS Administration time has no statistically significant nor clinically important impact on the stability of warfarin’s anticoagulant effect. Patients should take warfarin whenever regular compliance would be easiest.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".