Age and gender effects on the extent of myocardial involvement in acute myocarditis: a cardiovascular magnetic resonance study
Bibliographic record
Abstract
OBJECTIVE: Based upon epidemiological studies, male gender and younger age are risk factors for developing fatal myocarditis. The impact of age and gender on myocardial injury pattern in acute myocarditis, however, is not well understood. In patients with clinically acute myocarditis, this study sought to characterise the relation between patient age and gender and the extent of myocardial involvement using cardiovascular magnetic resonance (CMR) imaging. CMR markers for oedema, inflammation and fibrosis defined myocardial involvement. DESIGN, SETTING AND PATIENTS: 65 patients (42 years old (SD 15), 41 male) with clinically acute myocarditis were assessed. Using standard methods, T2-weighted and contrast-enhanced T1-weighted (early and late enhancement) CMR images were acquired. T2 images were visually and quantitatively assessed for oedema. Early enhancement images were quantified for inflammation, as was regional fibrosis in late enhancement images. Data were analysed for groups of age (>40, <40 years) and gender. RESULTS: 62% of all patients had evidence of regional oedema, which was more prevalent in patients below 40 years of age (80.7% vs 51.3%, p<0.05), as was myocardial fibrosis (76.9% vs 48.7%, p<0.05). However, early enhancement was more frequently found in patients above 40 years (84.2% vs 61.5%, p<0.05). Men were twice as likely as women to demonstrate myocardial fibrosis (73.2 vs 37.5%, p<0.01). CONCLUSION: In patients with clinically acute myocarditis, myocardial fibrosis was more frequent in men and in patients younger than 40 years. Injury sustained in younger patients appears to be more regional and more severe, as indicated by a higher incidence of irreversible injury.
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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 | 0.000 | 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) | 0.003 | 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".