The Alternative Imaging Modalities in Ischemic Heart Failure (AIMI-HF) Trial—IMAGE HF Project 1A
Bibliographic record
Abstract
Background The role of advanced (cardiac magnetic resonance [CMR] or positron emission tomography [PET]) vs single-photon emission computerized tomography (SPECT) ischemia imaging to guide management remains unclear in patients with ischemic heart failure (IHF). The primary aim was to determine the effect of imaging modality on a composite cardiovascular endpoint and cardiac death in patients with IHF who require ischemia assessment. Methods Patients with IHF were randomized to advanced or SPECT imaging. A parallel registry also was performed. The primary endpoint was the composite of cardiac death, infarction, arrest, and cardiac rehospitalization. The key secondary endpoint was cardiac death. Results Patients in the randomized population (advanced imaging [PET or CMR; n=64] or SPECT [n = 56]) had a cumulative incidence rate (CIR) for the primary endpoint of 33.1% and 33.0%, respectively (hazard ratio [HR] 0.94, 95% confidence interval [CI] 0.49, 1.80, P = 0.853). CIRs for cardiac death were 13.8% and 25.1%, respectively (HR 0.62, 95% CI 0.25, 1.80, P = 0.296). In the parallel registry (n = 336 advanced; n=216 SPECT), the primary endpoint CIRs were 31.2% and 35.3%, respectively (HR 0.81, 95% CI 0.56, 1.19, P = 0.284). CIRs for cardiac death were 11.0% and 16.6%, respectively (HR 0.53, 95% CI 0.27, 1.04, P = 0.066). Patients were followed for a median (interquartile range) of 24.1 (11.6, 27.5) months. Pooled analysis from the randomized and registry populations revealed a significant benefit of advanced imaging for reduction of cardiac death (HR 0.56, 95% CI 0.33, 0.96, P = 0.04) with minimal heterogeneity (I 2 = 0%). Conclusion Among IHF patients assessed for ischemia, advanced imaging (PET or CMR) was not associated with reduced composite cardiac events, compared to SPECT. Clinical Trial Registration NCT01288560.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".