Death, dependency and health status 90 days following hospital admission for acute stroke in NSW
Bibliographic record
Abstract
BACKGROUND: Stroke is an Australian health priority area causing considerable levels of disability. We report 90-day outcomes for a cohort of acute stroke patients in New South Wales (NSW), Australia prior to randomization to a large cluster randomized controlled trial (CRCT), the Quality in Acute Stroke Care (QASC) trial. AIMS: This paper describes prospectively collected, 90-day outcome data for a cohort of NSW stroke patients, providing pre-intervention data for the QASC trial. METHODS: A consecutive sample of patients from acute stroke units in NSW was recruited. We measured patient death, disability (modified Rankin Score (mRS)), dependency (Barthel Index (BI)) and Health Status (Medical Outcomes Short-Form Health Survey (SF-36)) 90 days post-hospital admission. We also collected self-reported healthcare utilization and patient satisfaction with health professionals' advice and management to reduce risk of subsequent stroke. RESULTS: Ninety-day outcome data were obtained for 687 patients, of which, 335 (49%) had an mRS ≥2; 44 patients (6.4%) had died. For the 643 surviving patients, the mean BI was 87.2 (SD 21.9) and the mean scores for SF-36 Physical Component Summary score and Mental Component Summary score were 46.2 (SD 10.1) and 46.3 (SD 12.6) respectively. CONCLUSIONS: In this pre-intervention cohort of selected acute stroke inpatients, stroke severity was mild to moderate and subsequent clinical outcomes were favourable in the majority. The findings from this study provide a comprehensive description of 90-day health outcomes of patients who have experienced a mild-moderate stroke managed in stroke care units across metropolitan NSW and provide valuable data to inform the subsequent cluster trial.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".