Abstract 9904: Trends in Enrollment, Patient Characteristics, Treatments and Outcomes of Older Adults With Non-ST-segment Elevation Acute Coronary Syndromes (ACS) in Clinical Trials
Bibliographic record
Abstract
Introduction: Whereas individuals aged ≥75 years account for >1/3 of non-ST-segment elevation (NSTE) ACS episodes and the majority of deaths due to NSTE ACS in current practice, little is known about their participation in NSTE ACS clinical trials. Methods: We studied 79,133 NSTE ACS patients enrolled in 11 phase III clinical trials (GUSTO IIb, PURSUIT, PARAGON-A, PARAGON-B, PRISM, PRISM-PLUS, GUSTO IV-ACS, SYNERGY, EARLY ACS, TRACER, APPRAISE-2) during 5 time periods (1994-97, 1998-01, 2002-05, 2006-10) over 17 years. We characterized the population according to age, patient characteristics, medical therapy, and outcomes (severe bleeding, 30-day mortality, 6-month mortality, 30-day composite of death or MI) and examined changes in these parameters over time. Results: Overall, 19.7% of patients enrolled in the selected trials were aged ≥75 years; while this proportion increased during the 1998-01 and 2002-05 periods, it declined in 2006-10 (Table). The prevalence of comorbidities varied (Table). Use of evidence-based medications at discharge among patients aged ≥75 years increased overall (aspirin 66.6 to 93.5%; beta-blockers 40.9 to 78.2%; thienopyridines 5.8 to 76.9%, lipid-lowering drugs 8.0 to 83.4%, ACE inhibitors 24.6 to 62.6% in 1994-97 to 2006-10). 30-day and 6-month mortality consistently declined. During the interval between 1994-97 and 2006-10, severe bleeding and the 30-day composite of death or MI for patients aged ≥75 years declined overall (2.0% to 1.6% for severe bleeding, and 17.6% to 9.3% for composite of 30-day death or MI). Conclusions: Despite significant improvements in clinical care and outcomes among patients aged ≥75 years, their enrollment in NSTE ACS clinical trials is not representative of the NSTE ACS population. Representative enrollment of elderly patients in clinical trials constitutes a critical unmet need to advance their evidence-based care and apply more novel approaches to lower morbidity and mortality.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".