The Relationships Among Regionalization, Processes, and Outcomes for Stroke Care
Bibliographic record
Abstract
Regionalization for stroke care, including stroke center designation, is being implemented in the United States, Canada, or other countries. Limited information is available, however, concerning the relationships among regionalization, processes, and outcomes for stroke care. We examined the association of regionalization with processes and outcomes, and the mediating effect of processes of care on the association between regionalization and mortality for acute stroke in Taiwan. We analyzed all 229,568 admissions with acute ischemic stroke from January 2004 to September 2012 through Taiwan's National Health Insurance Research Database. Regionalized care for acute stroke has been implemented since July 2009 in Taiwan. Rates of thrombolytic therapy within 3 hours after onset of ischemic stroke, average numbers of processes of care, and 30-day mortality rates at monthly intervals for baseline (66 months) and 39 months after the implementation of regionalization. After accounting for secular trends and other confounders, changes in rates of thrombolytic therapy (level change 0.269% per month, P = 0.017 and trend change 0.010% per month, P = 0.048), average numbers of processes of care (trend change 0.001 per month, P = 0.030), and 30-day mortality rates (level change -0.442% per month, P = 0.007 and trend change -0.021% per month, P = 0.015) were attributable to regionalization. The processes of care were mediators of the association between regionalization and 30-day mortality after stroke. Regionalization for stroke care may improve timeliness and processes of stroke care, including access to timely thrombolytic therapy from emergency medical services to hospital care, which may in turn enhance stroke outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".