Variation in outcome of hospitalization for stroke across hospitals in Québec
Bibliographic record
Abstract
The purpose of this study was to estimate, for stroke, the degree to which outcome of hospitalization, for death and discharge home, differed across hospitals in Quebec and the contribution of hospital-related factors to this variation. The outcomes of in-hospital death and discharge home (among survivors) were ascertained for the period April 1, 1992 to March 31, 1997, using the Quebec hospital discharge database (Med-Echo). The estimator of variation was the ratio of the hospital-specific observed number of stroke admissions that ended in death or discharge home to the risk-adjusted expected number of deaths or discharged home, obtained using logistic regression. A second stage of analysis involved estimating the contribution of hospital-related factors to the log odds of death or discharge home, using multiple linear regression. Over the five-year period of study, 43,357 acute stroke admissions occurred. For death, the estimator of variation varied 3 fold across hospitals (range of 0.6 to 1.8). For discharge home, the same estimator yielded a 2.6 fold variation (range of 0.5 to 1.3). Non-teaching hospitals are associated with higher rates of death (~OR: 1.3 depending on the number of acute stroke hospital admissions per year and the level of urbanization of the area a hospital is located). Hospitals with 40 to 100 acute stroke admissions per year are associated with higher rates of death (~OR: 1.4 depending on teaching status and level of urbanization). Hospitals situated in urban regions are associated with the lowest rates of discharge home (~OR: 1.1 depending on number of acute stroke admissions and teaching status).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".