ECHO-MPS, a dual modality strategy of cardiac imaging to identify myocardial ischemia
Bibliographic record
Abstract
PURPOSE: We aimed to evaluate an approach with resting echocardiography (TTE) and stress myocardial perfusion scintigraphy (MPS) compared to standard MPS in patients with stable angina and normal left ventricle (LV). We hypothesized that normal LV on TTE may allow for the elimination of rest MPS without compromising accuracy and offering an efficient diagnostic pathway with reduced radiation exposure. METHODS: In a prospective, non-randomized study TTE was performed prior to MPS in patients (pts) referred for assessment of coronary artery disease (CAD). In pts with normal LV assessment was performed using the hybrid and the standard approach. TTE and MPS were interpreted by two TTE readers (ER1-2) and two MPS readers (NR1-2). ECHO-MPS was compared with standard MPS for diagnostic accuracy. RESULTS: 103 patients, mean age 61 ± 12 year, (63 M, 40 W) were recruited. Standard MPS were normal in 75 patients and abnormal in 28 patients, with the hybrid approach 79 studies were reported as normal and 24 studies as abnormal. Kappa values were 0.580, (p < 0.001) for large, 0.394, (p < 0.001) for medium, and 0.298 (p = 0.002) for small defects. With standard MPS as a reference, sensitivity for detection of perfusion defects by ECHO-MPS was 75% (95% CI 0.67-0.83) [NR2] and 78% (95% CI 0.70-0.86)[NR1]. Specificity was 95% (95% CI 0.90-0.99) [NR2] and 95% (CI 95%CI 0.90-0.99) [NR1]. CONCLUSIONS: ECHO-MPS protocol provides similar diagnostic accuracy as standard stress-rest MPS. In patients with normal systolic LV function in TTE, performing only stress MPS provides similar information as standard rest and stress MPS.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".