Prevalence of Lifestyle Risk Factors in Myotonic Dystrophy Type 1
Bibliographic record
Abstract
BACKGROUND: The prevalence of unhealthy lifestyle habits such as smoking has seldom been described in neuromuscular disorders, including myotonic dystrophy type 1 (DM1). However, it is essential to document the unhealthy lifestyle habits as they can exacerbate existing impairments and disabilities. The objectives are: 1) To determine the prevalence of risk factors among individuals with DM1; 2) To compare the prevalence among classic and mild phenotypes. METHOD: A survey was done on a sample of two-hundred (200) patients with DM1 as part of a larger study. Lifestyle risk factors included being overweight or obese, tobacco smoking, illicit drug use, excessive alcohol consumption and physical inactivity. A registered nurse administered the validated public health survey. Categorization of risk factors were based on national standards and compared with provincial and regional prevalences. RESULTS: 50% of DM1 patients were overweight or obese, 23.6% were regular smokers, and 76% were physically inactive. Except for overweight and obesity, significant differences were observed between patients with classic and mild phenotypes for all the other lifestyle risk factors: those with the classic phenotype being more often regular smokers, consuming more often illicit drugs and being less physically active. CONCLUSIONS: The results of this study will provide guidance for the development of better adapted and focussed health promotion interventions in the future.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".