Rate of Stroke Recurrence in Patients With Primary Intracerebral Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Primary intracerebral hemorrhage (PICH) is a devastating illness with high early mortality. Hypertension is a major risk factor both for ischemic cerebrovascular disease and for intracranial hemorrhage. Survivors of PICH are at risk for both recurrent hemorrhage and ischemic cerebrovascular disease. We sought to determine the rate of recurrence of ICH or cerebral ischemia in a cohort of PICH patients at the Toronto Hospital, Toronto, Canada. METHODS: A retrospective search of computerized hospital records from 1986 to 1996 for patients with a discharge diagnosis of intracerebral hemorrhage (International Classification of Diseases, Ninth Revision-Clinical Modification [ICD-9-CM] code 431) was conducted to identify the index cases. Charts were abstracted for demographic and clinical characteristics. CT scans, MR scans, or radiologist reports were reviewed. To determine recurrence, the database was linked to the Ontario Provincial Government Vital Statistics Registry and to the Canadian Institute for Health Information database of hospital discharge abstracts. Logistic regression analysis was used to identify predictive factors for mortality after PICH. A Cox proportional hazards model was fitted to identify predictive factors for recurrent ICH or stroke. RESULTS: A total of 746 charts were identified by computer search. After abstraction, 423 index patients with PICH were identified. Of these, 27.4% died in the first 30 days of their admission. Predictors of death were age, intraventricular rupture of hemorrhage, and trilobar hemorrhage. The recurrence rate for PICH was 2.4% (95% CI 1.4% to 3. 9%) per year, whereas the recurrence rate for ischemic cerebrovascular disease was 3.0% (95% CI 1.8% to 4.7%) per year. The only significant predictor of readmission for ICH was lobar location of the index hemorrhage, with a hazard ratio of 3.8 (95% CI 1.2 to 12.0). CONCLUSIONS: PICH has a high 30-day mortality rate. Survival from the initial insult portends a moderate risk of recurrence of 2. 4% per year for PICH and 3.0% per year for ischemic cerebrovascular disease. Patients with PICH are at risk for both ischemic stroke or TIA and recurrent hemorrhage; thus, PICH may be a marker for ischemic stroke. Patients with lobar hemorrhage have a 3.8-fold increased risk of recurrent 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".