Abstract 4146225: Stress Perfusion Cardiac Magnetic Resonance Imaging for Pediatric Patients with Repaired Transposition of the Great Arteries
Bibliographic record
Abstract
Introduction: Patients who underwent arterial switch operation (ASO) for d-transposition of the great arteries (TGA) are at increased risk for early myocardial ischemia. Stress perfusion cardiac MR (SPCMR) is used as a non-invasive tool for risk stratification but interpretation is often challenging. Hypothesis: There is significant interobserver variability in SPCMR image interpretation in patients with repaired TGA. Aims: 1. Determine incidence and severity of adverse effects of stress agents. 2. Evaluate incidence of positive SPCMR. 3. Assess agreement amongst reviewers in image interpretation. Methods: Patients with repaired TGA with SPCMR imaging from 2013 to 2024 were reviewed. Three patients with previous coronary intervention and one with severe chest pain after adenosine, unable to complete SPCMR, were excluded. 61 studies were performed in 56 patients. Images were independently reviewed by two investigators blinded to initial interpretation and clinical outcome. Perfusion defects were displayed on a circumferential polar plot using standard LV segmentation. Results: Median (IQR) age was 15 (11-17) years, weight 55 (36-68) kg, and BSA 1.6 (1.2-1.8) m2. Max heart rate was 110 (100-125) and systolic BP 127 (116-138). Eleven (20%) patients had cardiac symptoms, chest pain in 9 (16%), syncope in 1 (2%), pallor and distress in 1 (2%) infant. Adverse effects from SPCMR in 8/52 (15%) adenosine, 2/4 (50%) dobutamine, and 0/6 (0%) regadenoson were minor and resolved on stress completion. Six (10%) studies were initially interpreted as suspicious (n=5) or definitive (n=1) perfusion defect (Figure). No LGE was detected. Original interpretation did not match blinded reviews for 6 cases (Figure). Blinded reviewers agreed on 3 negative cases but interpretation differed in the other 3 cases (Figure). Conclusions: SPCMR is safe and feasible. Significant interobserver variability highlights the challenges in qualitative SPCMR interpretation for TGA. Quantitative perfusion may reduce interobserver variability. Larger multicenter studies would be helpful in further elucidating the risk profile of patient characteristics and coronary artery arrangements to determine whether routine use of SPCMR is warranted for TGA patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".