Anticoagulants in Older Patients with Nonvalvular Atrial Fibrillation after Intracranial Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Patients with nonvalvular atrial fibrillation (NVAF) who survive an intracranial hemorrhage (ICH) have an increased risk of ischemic stroke and systemic embolism (IS/ SE). We investigated whether starting oral anticoagulants (OACs) among older NVAF patients after an ICH was associated with a lower risk of IS/SE and mortality but offset by an increase in major bleeding. METHODS: We assembled a patient cohort from the Quebec Régie de l'Assurance Maladie du Québec (RAMQ) and Med-Echo administrative databases. We identified older adults with NVAF from 1995 to 2015. All patients with incident ICH and discharged in community were included. Patients were categorized according to OAC exposure. Outcomes included IS/SE, all-cause mortality, recurrent ICH and major bleeding after a quarantine period of 6 weeks. Crude event rates were calculated at 1-year of follow-up, and Cox proportional hazard models with a time-dependent binary exposure were used to assess adjusted hazard ratios (AHRs). RESULTS: The cohort of 683 NVAF patients with ICH aged 83 years on average. The rates (per 100 person-years) for IS/SE, death, ICH and major bleeding were 3.3, 40.6, 11.4, and 2.7 for the no OAC group; and 2.6, 16.3, 5.2, and 5.2 for OAC group, respectively. The AHR for IS/SE and death was 0.10 (95% confidence interval [CI], 0.05 to 0.21), 0.43 (95% CI, 0.19 to 0.97) for recurrent ICH and 1.73 (95% CI, 0.71 to 4.20) for major extracranial bleeding comparing OAC exposure to non-exposed. CONCLUSIONS: Initiating OAC after ICH in older individuals with NVAF is associated with a reduction of IS/SE and mortality and a trend in recurrent ICH supporting its use after ICH.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".