Association of material deprivation with discharge location and length of stay after inpatient stroke rehabilitation in Ontario: a retrospective, population-based cohort study
Bibliographic record
Abstract
Background: Low socioeconomic status is associated with increased risk of stroke and worse poststroke functional status. The aim of this study was to determine whether socioeconomic status, as measured by material deprivation, is associated with direct discharge to long-term care or length of stay after inpatient stroke rehabilitation. Methods: We performed a retrospective, population-based cohort study of people admitted to inpatient rehabilitation in Ontario, Canada, after stroke. Community-dwelling adults (aged 19–100 yr) discharged from acute care with a most responsible diagnosis of stroke between Sept. 1, 2012, and Aug. 31, 2017, and subsequently admitted to an inpatient rehabilitation bed were included. We used a multivariable logistic regression model to examine the association between material deprivation quintile (from the Ontario Marginalization Index) and discharge to long-term care, and a multivariable negative binomial regression model to examine the association between material deprivation quintile and rehabilitation length of stay. Results: A total of 18 736 people were included. There was no association between material deprivation and direct discharge to long-term care (most v. least deprived: odds ratio [OR] 1.07, 95% confidence interval [CI] 0.89–1.28); however, people living in the most deprived areas had a mean length of stay 1.7 days longer than that of people in the least deprived areas (p = 0.004). This difference was not significant after adjustment for other baseline differences (relative change in mean 1.02, 95% CI 0.99–1.04). Interpretation: People admitted to inpatient stroke rehabilitation in Ontario had similar discharge destinations and lengths of stay regardless of their socioeconomic status. In future studies, investigators should consider further examining the associations of material deprivation with upstream factors as well as potential mitigation strategies.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| 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".