Adverse event rates associated with oral anticoagulant treatment early versus later after hospital discharge in older adults: a retrospective population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Oral anticoagulants are commonly used high-risk medications, but little is known about their safety in transition from hospital to home. Our objective was to measure the rates of hemorrhage and thromboembolic events among older adults receiving oral anticoagulant treatment early after hospital discharge compared to later. METHODS: We conducted a retrospective population-based cohort study among Ontario residents aged 66 years or more who started, continued or resumed oral anticoagulant therapy at hospital discharge between September 2010 and March 2015. We calculated the rates of hemorrhage and thromboembolic events requiring hospital admission or an emergency department visit over a 1-year follow-up period, stratified by the first 30 days after discharge and the remainder of the year. We used multivariable regression models, adjusting for covariates, to estimate the effect of sex, prevalent versus incident use, and switching anticoagulants on events. RESULTS: A total of 123 139 patients (68 408 women [55.6%]; mean age 78.2 yr) were included. About one-quarter (32 563 [26.4%]) had a Charlson Comorbidity Index score of 2 or higher. The rates of hemorrhage and thromboembolic events per 100 person-years were highest during the first 30 days after hospital discharge (25.8, 95% CI 24.8-26.8 and 19.3, 95% CI 18.4-20.2, respectively), falling to 15.7 (95% CI 15.3-16.1) and 6.9 (95% CI 6.6-7.1), respectively, during the subsequent 11 months. Multivariable analysis showed that patients whose anticoagulant was switched in hospital and men had more hemorrhages and thromboembolic events in follow-up. INTERPRETATION: The first few weeks following hospital discharge represent a very high-risk period for adverse events related to oral anticoagulant treatment among older adults. The results support an intervention trial addressing anticoagulation management in the early postdischarge period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".