Abstract 10733: Cardiac Magnetic Resonance Characteristics Including Feature Tracking in a Multi-Center Pediatric Study of Atypical Myocarditis
Bibliographic record
Abstract
Introduction: Atypical myocarditis, presenting as isolated chest pain, elevated troponin and preserved cardiac output in childhood is rare. Beyond small volume single center case series, limited data are reported on CMR characteristics at initial presentation and follow up. Methods: This is a pediatric multi-center retrospective study. Patients with chest pain and elevated cardiac troponin who underwent an echo and CMR within 30 days of each other were included. Clinical, echo and CMR parameters were collected at presentation and follow up. CMR global longitudinal strain (GLS) was performed with feature tracking technology (TomTec). Cases were divided into CMR myocarditis positive (Myo+) and CMR myocarditis negative (Myo-) based on Lake Louise criteria. Findings were compared to 19 age matched controls. Results: A total of 108 cases were included (88 Myo+ and 20 Myo-). Majority were male (88%) with average age of 15.6 ± 2.1 years. Median troponin was 13 (0.18-260.1 ng/mL), median BNP was 270.8 (12-3949 pg/ml). Abnormal ECG findings were present in 79% at presentation. While CMR LVEF did not differ between cases (56 ± 9%) and controls (60 ± 4%, p 0.06), GLS was significantly worse in cases (-16.2 ± 2.7%) compared to controls (-19.2 ± 2.1%, p <0.001). Unlike LVEF, GLS was significantly worse in Myo+ (-15.7 ± 2.8%) compared to Myo- cases (-18.0 ± 1.3%, p < 0.001). Fifty-four subjects had follow up data with 35 repeat CMRs. Median follow up was 204 (30-944) days. Late gadolinium enhancement (LGE) persisted in 82% of the Myo+ cases. Of the cases with abnormal GLS at presentation, 77% had persistent LGE. At follow up, 14% of cases were on heart failure medications, 33% had abnormal GLS and 39% had abnormal LVEF (<55%). Neither treatment with steroids or IVIG at presentation nor LGE on initial or follow up CMR were associated with the need for heart failure medications or persistent symptoms at follow up. Conclusions: In atypical myocarditis, CMR GLS can help differentiate between Myo+ and Myo- cases. Abnormal CMR GLS at presentation has higher association with persistence of LGE at follow up, irrespective of type of treatment. Future studies are needed to identify other characteristics that predict persistently abnormal findings important to clinical management and prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".