Gender as a Modifying Factor Influencing Myotonic Dystrophy Type 1 Phenotype Severity and Mortality: A Nationwide Multiple Databases Cross-Sectional Observational Study
Bibliographic record
Abstract
BACKGROUND: Myotonic Dystrophy type 1 (DM1) is one of the most heterogeneous hereditary disease in terms of age of onset, clinical manifestations, and severity, challenging both medical management and clinical trials. The CTG expansion size is the main factor determining the age of onset although no factor can finely predict phenotype and prognosis. Differences between males and females have not been specifically reported. Our aim is to study gender impact on DM1 phenotype and severity. METHODS: We first performed cross-sectional analysis of main multiorgan clinical parameters in 1409 adult DM1 patients (>18 y) from the DM-Scope nationwide registry and observed different patterns in males and females. Then, we assessed gender impact on social and economic domains using the AFM-Téléthon DM1 survey (n = 970), and morbidity and mortality using the French National Health Service Database (n = 3301). RESULTS: Men more frequently had (1) severe muscular disability with marked myotonia, muscle weakness, cardiac, and respiratory involvement; (2) developmental abnormalities with facial dysmorphism and cognitive impairment inferred from low educational levels and work in specialized environments; and (3) lonely life. Alternatively, women more frequently had cataracts, dysphagia, digestive tract dysfunction, incontinence, thyroid disorder and obesity. Most differences were out of proportion to those observed in the general population. Compared to women, males were more affected in their social and economic life. In addition, they were more frequently hospitalized for cardiac problems, and had a higher mortality rate. CONCLUSION: Gender is a previously unrecognized factor influencing DM1 clinical profile and severity of the disease, with worse socio-economic consequences of the disease and higher morbidity and mortality in males. Gender should be considered in the design of both stratified medical management and clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".