Hospital Readmission Rates Among Mechanically Ventilated Patients With Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Tracheostomy is frequently performed in patients with severe ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. Little is known about readmission rates among stroke patients who undergo mechanical ventilation. METHODS: We used previously validated International Classification of Diseases, Ninth Edition-Clinical Modification codes and data on all discharges from nonfederal acute care hospitals in 3 states. We compared readmission rates among mechanically ventilated patients with stroke who were discharged with or without a tracheostomy. RESULTS: Among 39,881 patients who underwent mechanical ventilation during the index stroke hospitalization and survived to discharge, 10,690 (26.8%; 95% confidence interval, 26.4%-27.2%) underwent tracheostomy. During a mean follow-up period of 3.4 (±2.0) years, the overall incidence rate of readmissions was 4.25 (95% confidence interval, 4.22-4.28) per 100 patients per 30 days. The rate of any readmissions within 30 days was 26.9% among patients with tracheostomy compared with 22.5% among those without a tracheostomy (absolute risk difference, 4.4%; 95% confidence interval, 3.5%-5.4%; P<0.001). After adjustment for potentially confounding variables, tracheostomy was associated with a slightly increased readmission rate (incidence rate ratio, 1.07; 95% confidence interval, 1.03-1.11). CONCLUSIONS: Approximately one quarter of mechanically ventilated patients with stroke who survive to discharge are readmitted to the hospital within 30 days. Readmission rates are significantly higher in patients with stroke who undergo tracheostomy, but the difference is not clinically meaningful. Thirty-day readmission rates among mechanically ventilated patients with stroke are similar to Medicare beneficiaries hospitalized with major medical diseases such as pneumonia.
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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".