The prevalence of primary dystonia: A systematic review and meta‐analysis
Bibliographic record
Abstract
Dystonia is a hyperkinetic movement disorder characterized by sustained muscle contractions that produce repetitive movements and abnormal postures. Specific information on the prevalence of dystonia has been difficult to establish because the existing epidemiological studies of the condition have adopted different methodologies for case ascertainment, resulting in widely differing reported prevalence. Medline and Embase databases were searched using terms specific to dystonia for studies of incidence, prevalence, and epidemiology. All population-based studies reporting an incidence and/or prevalence of primary dystonia were included. Sixteen original studies were included in our systematic review. Fifteen studies reported the prevalence of dystonia, including 12 service-based and three population-based studies. We performed a meta-analysis on the results of the service-based studies, and were able to combine data on the prevalence of several dystonia subtypes. From these studies, we calculated an overall prevalence of primary dystonia of 16.43 per 100,000 (95% confidence interval [CI]: 12.09-22.32). The prevalence of dystonia reported in the three population-based studies appears higher than that reported in the service-based studies. Only 1 of the 16 studies reported an incidence of cervical dystonia. This corresponded to a corrected incidence estimate of 1.07 per 100,000 person-years (95% CI: 0.86-1.32). Despite numerous studies on the epidemiology of dystonia, attempting to determine an accurate prevalence of the condition for health services planning remains a significant challenge. Given the methodological limitations of the existing studies, our own prevalence estimate of primary dystonia likely underestimates the true prevalence of the condition.
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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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.009 | 0.011 |
| 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) | 0.004 | 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".