Hospital Case Volume Is Associated With Mortality in Patients Hospitalized With Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND: Prior studies have suggested that hospital case volume may be associated with improved outcomes after subarachnoid hemorrhage (SAH), but contemporary national data are limited. OBJECTIVE: To assess the association between hospital case volume for SAH and in-hospital mortality. METHODS: Using the Get With The Guidelines-Stroke registry, we analyzed patients with a discharge diagnosis of SAH between April 2003 and March 2012. We assessed the association of annual SAH case volume with in-hospital mortality by using multivariable logistic regression adjusting for relevant patient, hospital, and geographic characteristics. RESULTS: Among 31,973 patients with SAH from 685 hospitals, the median annual case volume per hospital was 8.5 (25th-75th percentile, 6.7-12.9) patients. Mean in-hospital mortality was 25.7%, but was lower with increasing annual SAH volume: 29.5% in quartile 1 (range, 4-6.6), 27.0% in quartile 2 (range, 6.7-8.5), 24.1% in quartile 3 (range, 8.5-12.7), and 22.1% in quartile 4 (range, 12.9-94.5). Adjusting for patient and hospital characteristics, hospital SAH volume was independently associated with in-hospital mortality (adjusted odds ratio 0.79 for quartile 4 vs 1, 95% confidence interval, 0.67-0.92). The quartile of SAH volume also was associated with length of stay but not with discharge home or independent ambulatory status. CONCLUSION: In a large nationwide registry, we observed that patients treated at hospitals with higher volumes of SAH patients have lower in-hospital mortality, independent of patient and hospital characteristics. Our data suggest that experienced centers may provide more optimized care for SAH patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".