Abstract 240: Regional Variation in 30-Day Ischemic Stroke Mortality and Readmissions in Get With the Guidelines-Stroke Hospitals
Bibliographic record
Abstract
Objective: To explore regional variation and correlation between 30-day ischemic stroke mortality and readmissions in ischemic stroke patients treated at Get With The Guidelines (GWTG)-Stroke hospitals. Methods: Hospital-level 30-day ischemic stroke mortality and readmission rates were generated by linking GWTG-Stroke national registry data (2007-11) to Medicare fee-for-service data. We then aggregated GWTG-Stroke hospitals into hospital referral regions (HRR) as defined by the Dartmouth Atlas. Frequency-weighted 30-day event rates were estimated for each HRR, which were risk-adjusted using HRR-level patient and hospital characteristics. A Pearson correlation coefficient (r) was used to estimate the linear relationship between mortality and readmission rates at the HRR level. Results: There were 429,631 ischemic stroke patients at least 65 years of age treated at 1,344 GWTG-Stroke hospitals in 282 different HRRs. The average HRR-level risk adjusted 30-day mortality rate was 10.3% (SD=1.1%), with range 7.4% to 15.6%. The average HRR-level risk adjusted readmission rate was 13.2% (SD=1.4%), with range 9.7% to 23.3%. HRR-level maps suggest that some regions with higher than average mortality - such as the Mountain West and Upper Midwest regions - had lower than average readmission rates. (Figure 1) There was a modest, but statistically significant negative correlation between 30-day mortality and readmission rates (r = -0.23, p<0.0001). (Figure 2) Conclusions: HRR-level 30-day ischemic stroke mortality and readmission rates exhibit substantial regional variation and are inversely correlated. Further research is ongoing to determine the origin of the regional variation and correlation between 30-day event rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".