Predictive value of CMR criteria for LV functional improvement in patients with acute myocarditis
Bibliographic record
Abstract
AIM: We assessed the value of cardiovascular magnetic resonance (CMR) criteria ('Lake Louise Criteria') for predicting left ventricular (LV) functional improvement in patients with acute myocarditis. METHODS AND RESULTS: We studied 37 patients who referred for acute myocarditis during clinically acute myocarditis and after a 12-month follow-up. CMR sequences sensitive for oedema, hyperaemia, and irreversible injury were applied. Global and regional oedema were defined using published quantitative signal intensity (SI) cut-off values (area with an SI of >2 SD above visually normal myocardium). LV function was analysed using six long-axis views, with an increase of at least 5% of left ventricular ejection fraction considered as improvement. Out of a total of 37 patients, 29 met the CMR Lake Louise criteria (LL+) and eight did not (LL-). Baseline and 12-month ejection fraction (EF) were significantly lower in LL+ (53.2 ± 8 vs. 62.2 ± 5, P = 0.007 and 58.9 ± 4 vs. 62.9 ± 5, P = 0.045, respectively). At follow-up, EF increased in LL+ but remained unchanged within normal limits in LL- groups (delta EF: 5.7 ± 9.8 vs. 0.7 ± 2.0). The presence of global or regional myocardial oedema was strongly associated with an increase of EF ≥5%. In a multivariate analysis, the presence of global and/or regional oedema on admission was the only independent predictor of an increase of EF (P = 0.046). CONCLUSION: In patients with clinically suspected acute myocarditis, the presence of positive CMR criteria is associated with LV function recovery. Myocardial oedema as defined by CMR was the strongest parameter, indicating that the observed increase of EF may be due to the recovery of reversibly injured (oedematous) myocardium.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".