Cardiovascular Magnetic Resonance Provides Evidence of Abnormal Myocardial Strain and Primary Cardiomyopathy in Marfan syndrome
Bibliographic record
Abstract
OBJECTIVE: Marfan syndrome is an autosomal-dominant genetic disorder caused by mutations in the fibrillin-1 gene. The condition is a connective tissue disease that frequently involves the cardiovascular system. The existence of a primary cardiomyopathy in Marfan syndrome, however, is controversial. The aims of this study were to investigate the prevalence of left ventricular dysfunction with both transthoracic echocardiography and cardiovascular magnetic resonance (CMR) in a cohort of Marfan syndrome patients and to investigate patterns of myocardial strain across the cohort. METHODS: We used an institutional database to identify all patients with a firm diagnosis of Marfan syndrome based on Ghent criteria. Inclusion required left ventricular ejection fraction (LVEF) to have been measured by both CMR and transthoracic echocardiography within 12 months of each other. Normal LVEF was defined as a value of >55% when measured by CMR. Velocity vector imaging was used to measure left ventricular longitudinal strain patterns by application of feature tracking to cine magnetic resonance images. Results were compared with data from 20 age-matched control subjects. RESULTS: Sixty-nine Marfan syndrome patients met the inclusion criteria. The mean age was 35.4 ± 15.0 years, and 56.5% were male. The mean LVEF was 59.0% ± 7.0% by CMR and 59.1% ± 5.8% by echo. One-fifth of Marfan syndrome patients (15/69; 21.7%) had reduced function with LVEF ≤55% by CMR, but only 5 of these were identified by echo. Furthermore, echo identified 5 Marfan syndrome patients as having reduced LVEF in the presence of a normal LVEF by CMR. Some Marfan syndrome patients had abnormal longitudinal strain patterns even with LVEF within the reference range. CONCLUSIONS: These data provide support for a primary cardiomyopathy in some Marfan syndrome patients. Cardiovascular magnetic resonance is more sensitive than echo for identifying cases with mild systolic dysfunction. Strain analysis may be more sensitive than simple LVEF assessment for identifying at-risk individuals.
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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 | 0.000 |
| 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".