Potential Association of Holidays on Internationalized Normalized Ratio in Warfarin-Users at a Multidisciplinary Clinic
Bibliographic record
Abstract
Background: Warfarin is approved by the United States Food and Drug Administration for numerous clinical indications. The effectiveness of warfarin is highly dependent on the time-in-therapeutic range based on the international normalized ratio (INR) goal, which may be altered by changes in diet, alcohol intake, concomitant drugs, and travel, all of which are prevalent during the holidays. At this time, there are no published studies assessing the impact of holidays on INR in warfarin-users. Methods: A retrospective chart review was conducted on all adult patients taking warfarin and managed at a multidisciplinary clinic. Patients were included if they were taking warfarin at home regardless of indication for anticoagulation. The INR pre- and post-holiday was assessed. Results: Of a total of 92 patients, the mean age was 71.5 ± 14.3 years, and most patients were on warfarin with an INR goal of 2 - 3 (89%). There were significant differences in INR before and after Independence Day (2.55 vs. 2.81, P = 0.043) and Columbus Day (2.39 vs. 2.82, P < 0.001). The remaining holidays showed no significant differences in INR before and after each respective holiday. Conclusions: There may be factors related to Independence and Columbus Day that are increasing the level of anticoagulation in warfarin-users. Although the mean post-holiday INR values, in essence, maintained within the typical target of 2 - 3, our study underscores the specialized care that is warranted in higher risk patients to prevent a continued increase in INR and subsequent toxicities. We hope our results would be hypothesis-generating and aid in the development of larger, prospective evaluations to validate the findings of our present study.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".