Abstract WP166: Longitudinal Outcomes of Medicare Beneficiaries With Transient Ischemic Attack: a GWTG-Stroke Study
Bibliographic record
Abstract
Background: We sought to examine the longitudinal outcomes following admission for transient ischemic attack (TIA) among Medicare beneficiaries admitted at GWTG-Stroke participating hospitals and to examine this varies by ABCD 2 score categories. Methods: We identified TIA hospitalizations from GWTG-Stroke and linked these with Medicare claims for January 1, 2011 to December 31, 2014 to determine 1-year event rates of mortality, all-cause hospital readmission, composite outcome of mortality and all-cause readmission, and readmissions related to ischemic stroke (IS) and major vascular events. Patients were identified as high risk (ABCD 2 score ≥ 4) or low risk (ABCD 2 score 0-3) to assess differences in outcomes by risk group. Results: Of 394,920 patients from 1,779 hospitals with IS/TIA, 77,819 (19.7%) had a diagnosis of TIA at hospital discharge. Mean age was 80 years and 39.4% were male. Outcomes at 1-year included mortality in 11.9%, all-cause readmission 44.2%, composite of mortality/all-cause readmission 47.1%, ischemic stroke related admission 3.5%, and readmission related to major vascular events 5.3%. Of the 40,825 patients with complete data to calculate an ABCD 2 score, 86% were high risk (n=35,118) and 14% low risk (n= 5,707). There was a significant difference between these two groups in adjusted risk for 1-year outcomes of mortality, mortality/all-cause readmission and ischemic stroke admission but not major vascular readmission (Table 1). Conclusions: There was a high rate of adverse events including mortality and ischemic stroke admission, among Medicare beneficiaries admitted with TIA at GWTG-Stroke participating hospitals. The ABCD 2 score identified TIA patients at higher risk of adverse outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".