Intracerebral Hemorrhage Incidence, Mortality, and Association With Oral Anticoagulation Use
Bibliographic record
Abstract
Background and Purpose: Spontaneous intracerebral hemorrhage (ICH) is a devastating form of stroke associated with significant morbidity and mortality. Recent epidemiological data on incidence, mortality, and association with oral anticoagulation are needed. Methods: Retrospective cohort study of adult patients (≥18 years) with ICH in the entire population of Ontario, Canada (April 1, 2009–March 30, 2019). We captured outcome data using linked health administrative databases. The primary outcome was mortality during hospitalization, as well as at 1 year following ICH. Results: We included 20 738 patients with ICH. Mean (SD) age was 71.3 (15.1) years, and 52.6% of patients were male. Overall incidence of ICH throughout the study period was 19.1/100 000 person-years and did not markedly change over the study period. In-hospital and 1-year mortality were high (32.4% and 45.4%, respectively). Mortality at 2 years was 49.5%. Only 14.5% of patients were discharged home independently. Over the study period, both in-hospital and 1-year mortality reduced by 10.4% (37.5% to 27.1%, P <0.001) and 7.6% (50.0% to 42.4%, P <0.001), respectively. Use of oral anticoagulation was associated with both in-hospital mortality (adjusted odds ratio 1.37 [95% CI, 1.26–1.49]) and 1-year mortality (hazard ratio, 1.18 [95% CI, 1.12–1.25]) following ICH. Conclusions: Both short- and long-term mortality have decreased in the past decade. Most survivors from ICH are likely to be discharged to long-term care. Oral anticoagulation is associated with both short- and long-term mortality following ICH. These findings highlight the devastating nature of ICH, but also identify significant improvement in outcomes over time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".