Diagnostic Performance of Treadmill Exercise Cardiac Magnetic Resonance: The Prospective, Multicenter Exercise CMR's Accuracy for Cardiovascular Stress Testing (EXACT) Trial
Bibliographic record
Abstract
BACKGROUND: Stress cardiac magnetic resonance (CMR) has typically involved pharmacologic agents. Treadmill CMR has shown utility in single-center studies but has not undergone multicenter evaluation. METHODS AND RESULTS: Patients referred for treadmill stress nuclear imaging (SPECT) were prospectively enrolled across 4 centers. After rest (99m)Tc SPECT, patients underwent resting cine CMR. In-room stress was then performed using an MR-compatible treadmill with continuous 12-lead electrocardiogram monitoring. At peak stress, (99m)Tc was injected, and patients rapidly returned to the MR scanner isocenter for real-time, free-breathing stress cine and perfusion imaging. After recovery, cine and rest perfusion followed by late gadolinium enhancement acquisitions concluded CMR imaging. Stress SPECT was then acquired in adjacent nuclear laboratories. A subset of patients not referred for invasive coronary angiography within 2 weeks of stress underwent coronary computed tomography angiography. Angiographic data available in 94 patients showed sensitivity of 79%, specificity of 99% for exercise CMR with positive predictive value of 92% and negative predictive value of 96%. Agreement between treadmill stress CMR and angiography was strong (κ=0.82), and moderate between SPECT and angiography (κ=0.46) and CMR versus SPECT (κ=0.48). CONCLUSIONS: The multicenter EXACT trial indicates excellent diagnostic value of treadmill stress CMR in typical patients referred for exercise SPECT.
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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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".