Escalating Levels of Access to In-Hospital Care and Stroke Mortality
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Organized stroke care is an integrated approach to managing stroke to improve stroke outcomes by ensuring that optimal treatment is offered. However, limited information is available comparing different levels of organized care. Our aim was to determine whether escalating levels of organized care can improve stroke outcomes. METHODS: Cohort study including patients with acute ischemic stroke between July 2003 and March 2005 in the Registry of the Canadian Stroke Network (RCSN). The RCSN is the largest clinical database of patients with acute stroke patients seen at selected acute care hospitals in Canada. As stroke unit admission does not automatically imply receipt of comprehensive care, we created the organized care index to represent different levels of access to organized care ranging from 0 to 3 as determined by the presence of occupational therapy/physiotherapy, stroke team assessment, and admission to a stroke unit. The primary end point was early stroke mortality. Secondary end points include 30-day and 1-year mortality. RESULTS: Overall, 3631 ischemic stroke patients were admitted to 11 hospitals. Seven day stroke mortality was 6.9% (249/3631), 30-day stroke mortality was 12.6% (457/3631), and 1-year stroke mortality was 23.6% (856/3631). Risk-adjusted 7-day mortality was 2.0%, 3.2%, 7.8%, and 22.5% for organized care index of 3, 2, 1, and 0. Higher level of care was associated with lower adjusted mortality (for organized care index 3, OR 0.03, 95% CI 0.02 to 0.07 for 7-day mortality; OR 0.09, 95% CI 0.05 to 0.17 for 30-day mortality; and OR 0.40, 95% CI 0.25 to 0.64 for 1-year mortality). CONCLUSIONS: Higher level of access to care was associated with lower stroke mortality rates. Establishing a well-organized and multidisciplinary system of stroke care will help improve the quality of service delivered and reduce the burden of stroke.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".