National trends in hospital admission, case fatality, and sex differences in atrial fibrillation-related strokes
Bibliographic record
Abstract
BACKGROUND AND AIM: Atrial fibrillation is associated with increased risk of ischemic stroke and its global prevalence is increasing. We aimed to describe the contemporary temporal trends in hospital admissions, case fatality rate, as well as sex differences in atrial fibrillation-related stroke in Canada. METHODS: We conducted a retrospective cohort study using Canadian national administrative data to identify admissions to hospital for stroke with comorbid atrial fibrillation between 1 April 2007 and 31 March 2016. We determined temporal trends in the crude and the age- and sex-standardized admission and case fatality rates. We also evaluated for any sex differences in these outcomes. RESULTS: There were 222,100 admissions to hospital for ischemic (n = 182,990) or hemorrhagic (n = 39,110) stroke. Comorbid atrial fibrillation was present in 20.2% of admissions for ischemic strokes and 10.1% for hemorrhagic strokes. Over the study period, the age-sex adjusted proportion of admissions with atrial fibrillation increased from 16.3% to 20.5% (p = 0.02) for ischemic stroke and was stable for hemorrhagic stroke. In-hospital case fatality rate decreased for ischemic stroke with and without comorbid atrial fibrillation. Women aged 65 years and older with ischemic stroke were more likely to have comorbid atrial fibrillation compared to men, while this association was reversed in younger women. There were no sex differences in the case fatality rate for people with atrial fibrillation-related ischemic stroke. CONCLUSION: Atrial fibrillation is present in an increasing proportion of people hospitalized in Canada with ischemic stroke and disproportionately affects older women. Renewed focus is needed on atrial fibrillation-related stroke prevention with particular attention to sex disparities.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".