International collaboration to improve knowledge on myotonic dystrophy type 2
Bibliographic record
Abstract
BACKGROUND: The TREAT-NMD Global Registry Network is a global collaboration of neuromuscular disease registries, including myotonic dystrophy type 2 (DM2), which aims to facilitate collaborative research and clinical trials. OBJECTIVES: This study aimed to assess DM2 patients included in the network, and to analyse their socio-demographic and clinical features. METHODS: Data were collected through email surveys sent to 16 TREAT-NMD myotonic dystrophy core member registries. 10 registries enrolled DM2 patients. RESULTS: The total number of DM2 cases was 1,720, with the Czech, German, and USA registries enrolling the most patients (445, 430, and 339 cases, respectively). The highest rates were seen in Czechia and Serbia (4.2 and 2.0 registered per 100,000 population, respectively). High DM2:DM1 ratios were seen in Central Europe. The median age at registry entry was 51 years. Symptom onset occurred before age 20 in 14% of cases. One fifth of patients used an assistive device to walk, and 4% were non-ambulatory. Insertion of a pacemaker or implantable cardioverter-defibrillator was reported in 4% of subjects, while 7% used non-invasive ventilation. CONCLUSIONS: This represents the largest DM2 cohort assembled to date, providing demographic and clinical data for future research and trial recruitment, illustrating TREAT-NMD's international reach and the importance of capturing DM2 data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".