Cooperative international neuromuscular research group duchenne natural history study demonstrates insufficient diagnosis and treatment of cardiomyopathy in duchenne muscular dystrophy
Bibliographic record
Abstract
INTRODUCTION: Cardiomyopathy is a common cause of morbidity and death in patients with Duchenne muscular dystrophy (DMD). METHODS: This investigation was a cross-sectional cross-sectional analysis of clinical data from the multi-institutional Cooperative International Neuromuscular Research Group (CINRG) DMD Natural History Study of 340 DMD patients aged 2-28 years. Cardiomyopathy was defined as shortening fraction (SF) <28% or ejection fraction (EF) <55%. RESULTS: Two hundred thirty-one participants reported a prior clinical echocardiogram study, and 174 had data for SF or EF. The prevalence of cardiomyopathy was 27% (47 of 174), and it was associated significantly with age and clinical stage. The association of cardiomyopathy with age and clinical stage was not changed by glucocorticoid use as a covariate (P > 0.68). In patients with cardiomyopathy, 57% (27 of 47) reported not taking any cardiac medications. Cardiac medications were used in 12% (15 of 127) of patients without cardiomyopathy. CONCLUSIONS: We found that echocardiograms were underutilized, and cardiomyopathy was undertreated in this DMD natural history cohort.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".