Abstract WP195: Home Time by Stroke Type: a Population-based Study to Evaluate Functional Outcome After a Cerebrovascular Event
Bibliographic record
Abstract
Introduction: Home time has been proposed as a surrogate for functional outcome in ischemic stroke, and is also a highly valued patient-centered outcome that reflects resource utilization. In prospective cohort studies and clinical trials, higher home time has been correlated with lower disability; however, the requirement for informed consent results in selection bias. Therefore, the population distributions of home time after stroke are currently unknown. Additionally, home time distributions have not been reported in hemorrhagic stroke and transient ischemic attack (TIA). We developed a novel administrative data algorithm to compare home time distributions after hospital admission for cerebrovascular events in the population of Alberta, Canada. Methods: Home time was defined as the number of nights not spent in an institution, including acute-care, inpatient rehabilitation facilities, and long-term care, in the 90 days after admission for a cerebrovascular event. Community-dwelling residents of Alberta, Canada with a valid healthcare number admitted for a cerebrovascular event between April 2012 and June 2015 were included. We used the Kruskal-Wallis test to compare the median home-times according to stroke type: ischemic stroke (IS), TIA, or hemorrhagic stroke (HS), including intracerebral and subarachnoid hemorrhage. We correlated admitting age and home time with Spearman correlations and assessed sex and home time with Wilcoxon Rank Sum. Results: A total of 12520 admissions were identified, the median age was 74 years (IQR 22), and 53% were male. There were 8482 (68%) IS, 2434 (19%) TIA, and 1604 (13%) HS. The median (IQR) home time by stroke type was 72 nights (85) for IS, 87 nights (6) for TIA, and 29 nights (79) for HS (p<0.001). For each stroke type, lower home time was correlated with higher age (IS: r=-0.35; TIA: r=-0.31; HS: r=-0.33; p<0.001 for each comparison) and female sex (p≤0.001). Conclusion: In this population with universal healthcare access, TIA had the highest home time (i.e. best outcomes) whereas hemorrhagic stroke had the lowest, consistent with expected functional outcomes based on prospective cohort studies. Home time may be a useful metric to track patient outcomes and healthcare utilization based on administrative health data.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".