Abstract TP175: Impact of Living Alone on Stroke Outcomes: Results from the Registry of the Canadian Stroke Network
Bibliographic record
Abstract
Background: Social isolation is a risk factor for poor health outcomes and living alone is a commonly used proxy measure for social isolation. We examined the relationships between living alone and stroke outcomes in patients enrolled in the Registry of the Canadian Stroke Network. Methods: Between 2003-2008, 24526 patients with ischemic stroke, hemorrhagic stroke, or TIA were admitted to 11 Ontario registry hospitals. Patients not living at home (n= 7364), repeat stroke admissions (n=1246) or with missing data (n= 1946) were excluded. Outcomes included onset to arrival time ≤2.5 hrs, discharge to home, mortality (in-hospital, 30-day, 1-year, 3-year), and readmission (1-year). The independent effects of living alone on outcomes were determined using multivariable logistic regression. Results: Overall, 22.5% (n= 3146/13970) of patients were living alone at home prior to admission. Compared to patients living at home with others, patients living alone were significantly more likely to be ≥80 years of age (41.6% vs. 28.8%), female (62.7% vs. 41.4%), white (58.9% vs. 53.7%), widowed (53.5% vs. 11.5%), or single (21.7% vs. 3.7%), and significantly less likely to have diabetes (21.8% vs. 24.8%) or dyslipidemia (32.2% vs. 37.3%). The prevalence of severe stroke was similar (12.4% vs. 14.9%). Patients living alone were less likely to arrive ≤2.5 hrs after onset (32.9% vs. 42.7%) or be discharged to home (61.1% vs. 68.2%), however, differences in mortality or readmission rates were minimal (Table). Adjustment for confounding variables did not appreciably change these results. Conclusions: Patients living alone had delayed hospital arrival and were less likely to return home, but were not at increased risk of death or readmission. Further research is needed to understand the inter-relationships between living alone, social isolation, and poor stroke outcomes, especially given the increasing prevalence of living alone in developed countries.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".