A Systematic Review and Meta-analysis on the Epidemiology of the Muscular Dystrophies
Bibliographic record
Abstract
BACKGROUND: The muscular dystrophies are a heterogeneous group of genetic muscle diseases with variable distribution of weakness and mode of inheritance. METHODS: We previously performed a systematic review of worldwide population-based studies on Duchenne and Becker muscular dystrophies; the current study focused on the epidemiology of other muscular dystrophies using Medline and EMBASE databases. Two reviewers independently reviewed all abstracts, full-text articles, and abstracted data from 1985 to 2011. Pooling of prevalence estimates was performed using random-effect models. RESULTS: A total of 1104 abstracts and 167 full-text articles were reviewed. Thirty-one studies met all eligibility criteria and were included in the final analysis. The overall pooled prevalence of combined muscular dystrophies was 16.14 (confidence interval [CI], 11.21-23.23) per 100,000. The prevalence estimates per 100,000 were 8.26 (CI, 4.99-13.68) for myotonic dystrophy, 3.95 (CI, 2.89-5.40) for facioscapulohumeral dystrophy, 1.63 (CI, 0.94-2.81) for limb girdle muscular dystrophy, and 0.99 (CI, 0.62-1.57) for congenital muscular dystrophies. CONCLUSIONS: The studies differed widely in their approaches to case ascertainment, and substantial gaps remain in the global estimates of many other types of muscular dystrophies. Additional epidemiological studies using standardized diagnostic criteria as well as multiple sources of case ascertainment will help address the economic impact and health care burden of muscular dystrophies worldwide.
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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 | 0.031 | 0.077 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".