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Record W4322012418 · doi:10.14740/cr1448

Potential Association of Holidays on Internationalized Normalized Ratio in Warfarin-Users at a Multidisciplinary Clinic

2023· article· en· W4322012418 on OpenAlexvenueno aff
Rachel Ryu, Khaled Bahjri, Huyentran Tran

Bibliographic record

VenueCardiology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsnot available
FundersLoma Linda University
KeywordsWarfarinMedicineConcomitantMultidisciplinary approachInternal medicineRetrospective cohort studyEmergency medicineAtrial fibrillation

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.121
GPT teacher head0.477
Teacher spread0.356 · 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 teacher head, not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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