Prognostic Utility of Cardiovascular Magnetic Resonance–Based Phenotyping in Patients With Muscular Dystrophy
Bibliographic record
Abstract
Background The prognostic utility of cardiovascular magnetic resonance imaging, including strain analysis and tissue characterization, has not been comprehensively investigated in adult patients with muscular dystrophy. Methods and Results We prospectively enrolled 148 patients with dystrophinopathies (including heterozygotes), limb‐girdle muscular dystrophy, and type 1 myotonic dystrophy (median age, 36.0 [interquartile range, 23.0–50.0] years; 51 [34.5%] women) over 7.7 years in addition to an age‐ and sex–matched healthy control cohort (n=50). Cardiovascular magnetic resonance markers, including 3‐dimensional strain and fibrosis, were assessed for their respective association with major adverse cardiac events. Our results showed that markers of contractile performance were reduced across all muscular dystrophy groups. In particular, the dystrophinopathies cohort experienced reduced left ventricular (LV) ejection fraction and high burden of replacement fibrosis. Patients with type 1 myotonic dystrophy showed a 26.8% relative reduction in LV mass with corresponding reduction in chamber volumes. Eighty‐two major adverse cardiac events occurred over a median follow‐up of 5.2 years. Although LV ejection fraction was significantly associated with major adverse cardiac events (adjusted hazard ratio [aHR], 3.0 [95% CI, 1.4–6.4]) after adjusting for covariates, peak 3‐dimensional strain amplitude demonstrated greater predictive value (minimum principal amplitude: aHR, 5.5 [95% CI, 2.5–11.9]; maximum principal amplitude: aHR, 3.3 [95% CI, 1.6–6.8]; circumferential amplitude: aHR, 3.4 [95% CI, 1.6–7.2]; longitudinal amplitude: aHR, 3.4 [95% CI, 1.7–6.9]; and radial strain amplitude: aHR, 3.0 [95% CI, 1.4–6.1]). Minimum principal strain yielded incremental prognostic value beyond LV ejection fraction for association with major adverse cardiac events (change in χ 2 =13.8; P <0.001). Conclusions Cardiac dysfunction is observed across all muscular dystrophy subtypes; however, the subtypes demonstrate distinct phenotypic profiles. Myocardial deformation analysis highlights unique markers of principal strain that improve risk assessment over other strain markers, LV ejection fraction, and late gadolinium enhancement in this vulnerable patient population.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".