Initial Invasive Versus Conservative Management of Stable Ischemic Heart Disease in Patients With a History of Heart Failure or Left Ventricular Dysfunction
Bibliographic record
Abstract
Background: Whether an initial invasive strategy in patients with stable ischemic heart disease and at least moderate ischemia improves outcomes in the setting of a history of heart failure (HF) or left ventricular dysfunction (LVD) when ejection fraction is ≥35% but <45% is unknown. Methods: Among 5179 participants randomized into ISCHEMIA (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches), all of whom had left ventricular ejection fraction (LVEF) ≥35%, we compared cardiovascular outcomes by treatment strategy in participants with a history of HF/LVD at baseline versus those without HF/LVD. Median follow-up was 3.2 years. Results: There were 398 (7.7%) participants with HF/LVD at baseline, of whom 177 had HF/LVEF >45%, 28 HF/LVEF 35% to 45%, and 193 LVEF 35% to 45% but no history of HF. HF/LVD was associated with more comorbidities at baseline, particularly previous myocardial infarction, stroke, and hypertension. Compared with patients without HF/LVD, participants with HF/LVD were more likely to experience a primary outcome composite of cardiovascular death, nonfatal myocardial infarction, or hospitalization for unstable angina, HF, or resuscitated cardiac arrest (4-year cumulative incidence rate, 22.7% versus 13.8%; cardiovascular death or myocardial infarction, 19.7% versus 12.3%; and all-cause death or HF, 15.0% versus 6.9%). Participants with HF/LVD randomized to the invasive versus conservative strategy had a lower rate of the primary outcome (17.2% versus 29.3%; difference in 4-year event rate, −12.1% [95% CI, −22.6 to −1.6%]), whereas those without HF/LVD did not (13.0% versus 14.6%; difference in 4-year event rate, −1.6% [95% CI, −3.8% to 0.7%]; P interaction = 0.055). A similar differential effect was seen for the primary outcome, all-cause mortality, and cardiovascular mortality when invasive versus conservative strategy–associated outcomes were analyzed with LVEF as a continuous variable for patients with and without previous HF. Conclusions: ISCHEMIA participants with stable ischemic heart disease and at least moderate ischemia with a history of HF or LVD were at increased risk for the primary outcome. In the small, high-risk subgroup with HF and LVEF 35% to 45%, an initial invasive approach was associated with better event-free survival. This result should be considered hypothesis-generating. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01471522.
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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".