A cross-sectional study of nemaline myopathy supplementary figures
Bibliographic record
Abstract
Objective: Nemaline myopathy (NM) is a rare neuromuscular condition with clinical and genetic heterogeneity. To establish disease natural history, we performed a cross-sectional study of NM, complemented by longitudinal assessment and exploration of pilot outcome measures. Methods: Fifty-seven individuals with NM were recruited at two family workshops, including 16 examined at both time points. Subjects were evaluated by clinical history and physical examination. Functional outcome measures included the Motor Function Measure (MFM), pulmonary function tests (PFTs), myometry, goniometry, and bulbar assessments. Results: The most common clinical classification was “typical congenital” (54%), whereas 42% had more severe presentations. 58% of individuals needed mechanical support, with 26% requiring wheelchair, tracheostomy, and feeding tube. The MFM scale was performed in 44/57 participants and showed reduced scores in most with little floor/ceiling effect. Of the 27 individuals completing PFTs, abnormal values were observed in 65%. Lastly, bulbar function was abnormal in all patients examined, as determined using a novel outcome measure. Genotypes included mutations in ACTA1 (18), NEB (20), and TPM2 (2). Seventeen individuals were genetically unresolved. Patients with pathogenic ACTA1 and NEB variants were largely similar in clinical phenotype. Patients without genetic resolution had more severe disease. Conclusion: In all, we present a comprehensive cross-sectional study of NM. Our data identify significant disabilities and support a relatively stable disease course. We identify a need for further diagnostic investigation for the genetically unresolved group. Lastly, MFM, pulmonary function tests, and the slurp test were identified as promising outcome measures for future clinical trials.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.011 | 0.002 |
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".