Age-Related Differences in Characteristics, Performance Measures, Treatment Trends, and Outcomes in Patients With Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Prior studies have suggested lower use of guideline-recommended therapy and worse poststroke outcomes in older patients. We sought to examine age-related differences in characteristics, performance measures, temporal trends, and early clinical outcomes for acute ischemic stroke in a large contemporary cohort. METHODS AND RESULTS: The relationships between age and clinical characteristics, performance measures, and in-hospital outcomes were analyzed in 502 036 ischemic stroke admissions from 1256 hospitals in the Get With the Guidelines-Stroke program from 2003 to 2009. Data were analyzed by age groups (<50, 50 to 59, 60 to 69, 70 to 79, 80 to 89, and >/=90 years) and with age as a continuous variable. Seven predefined performance measures and 2 summary measures were analyzed. Mean age of ischemic stroke patients was 71.0+/-14.6 years; 52.5% were women. Older patients were more likely to have a history of atrial fibrillation or hypertension and less likely to be black, Hispanic, or current/recent smokers. Although modest age-related differences in each individual performance measure were identified, there were substantial temporal improvements in performance measures from 2003 to 2009 in each age group, and many age-related treatment gaps were narrowed or eliminated over time. Older patients were less likely to be discharged home (adjusted odds ratio, 0.69; 95% confidence interval, 0.68 to 0.69) and more likely to die in hospital (adjusted odds ratio, 1.27; 95% confidence interval, 1.25 to 1.29) for each 10-year age increase. CONCLUSIONS: Older patients with ischemic stroke differ in clinical characteristics and experience higher in-hospital mortality than younger patients. Performance measure-based treatment rates improved substantially over time for ischemic stroke patients in all age groups, resulting in smaller age-related treatment gaps.
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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".