Trajectory of left ventricular ejection fraction in response to therapies in patients with muscular dystrophy
Bibliographic record
Abstract
BACKGROUND: Patients with muscular dystrophy (MD) are at elevated risk of serious cardiac complications and clinical assessment is limited due to inherent physical limitations. We assessed the utility of left ventricular ejection fraction (LVEF) derived from transthoracic echocardiogram (TTE) as a prognostic marker for major adverse cardiac events (MACE) in a mixed adult MD cohort. METHODS: One hundred and sixty-five MD patients (median age: 36 (interquartile range [IQR]: 23.0-49.0) years; 65 [39.4%] females) were enrolled in our prospective cohort study. Diagnoses included dystrophinopathies (n = 42), limb-girdle MD (n = 31), type 1 myotonic dystrophy (n = 71), and facioscapulohumeral MD (n = 21). Left ventricular ejection fraction, ventricular dimensions at end-diastole and end-systole, and serial measures (n = 124; follow-up period: 2.19 [IQR: 1.05-3.32] years) stratified patients for MACE risk. RESULTS: Cardiomyopathy was diagnosed in 60 (36.4%) patients of the broader cohort (median LVEF: 45.0 [IQR: 35.0-50.0] %). Ninety-eight MACE occurred over the 7-year study period. At baseline, patients with a LVEF < 55.0% had a high risk of MACE (adjusted odds ratio: 8.30; 95% confidence interval [CI]: 3.18-21.7), concordant with the analysis of LV dimensions. Forty-one percent of these patients showed an improvement in LVEF with the optimization of medical and device therapies. Relative to patients with preserved LVEF, patients with reduced LVEF were at an elevated risk of MACE (adjusted hazard ratio [aHR]: 7.21; 95% CI: 1.99-26.1), and improved LVEF resulted in comparable outcomes (aHR: 1.84; 95% CI: .49-6.91) associated with optimization of medical and device therapies. Reduction in QRS duration by CRT therapy was associated with an improvement in LVEF (average improvement: 12.8 [± 2.30] %; p = .04). CONCLUSIONS: Reduction in LVEF indicates an increased risk of cardiovascular events in patients with MD. Baseline and serial LVEF obtained by TTE can prognosticate patients for MACE and guide clinical management.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".