Abstract 17: Association Between Age And Health Status In Chronic Coronary Disease With An Initial Invasive Or Conservative Strategy: Insights From The ISCHEMIA Trial
Bibliographic record
Abstract
Background: Patients with chronic coronary disease (CCD) and at least moderate ischemia who were randomized in the ISCHEMIA trial to an invasive strategy (INV) had greater benefit in angina-related health status during follow-up than with a conservative strategy (CON). Whether this benefit varies by age is unknown. Methods: Angina-related health status was assessed with the 7-item Seattle Angina Questionnaire (SAQ; score range 0-100; higher score=less angina). Linear regression models assessed the association of treatment strategy (INV vs CON) with 1-year health status, including a treatment-by-age interaction using splines, adjusted for sex, ejection fraction, eGFR, diabetes, and baseline health status. Results: Among 4617 ISCHEMIA patients with complete health status data, mean age was 64±10 years; 2239 (48.5%) were <65, 1713 (37.1%) were 65-74, and 665 (14.4%) were ≥75. Baseline SAQ Summary scores were higher in patients aged 65-74 and ≥75 compared with those <65 (76.2 vs 75.4 vs 71.8 points). At 1 year, an INV strategy resulted in higher mean SAQ Summary Scores for all age groups but with greater benefit in younger patients (<65 vs 65-74 vs ≥75: +5.1 vs +2.5 vs +1.5 points). In adjusted analyses, the largest health status benefits of INV treatment were observed with younger age, with significant interactions between age and treatment strategy for SAQ Summary (p=0.007) and Quality of Life (QOL) scores (p=0.02) ( Figure ). At age 80, the benefits of an INV over CON strategy diminished for SAQ Summary Score, Physical Limitations, and QOL, despite increases in SAQ Angina Frequency scores. Similar trends were observed when patients without angina were excluded. Conclusion: CCD patients of all ages had better health status with an INV vs CON strategy, but these benefits were greater in younger patients and diminished with increasing age. These data suggest an initial CON strategy may be preferred in older patients with CCD, based on goals of care.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".