Findings from the Longitudinal CINRG Becker Natural History Study
Bibliographic record
Abstract
BACKGROUND: Becker muscular dystrophy is an X-linked, genetic disorder causing progressive degeneration of skeletal and cardiac muscle, with a widely variable phenotype. OBJECTIVE: A 3-year, longitudinal, prospective dataset contributed by patients with confirmed Becker muscular dystrophy was analyzed to characterize the natural history of this disorder. A better understanding of the natural history is crucial to rigorous therapeutic trials. METHODS: A cohort of 83 patients with Becker muscular dystrophy (5-75 years at baseline) were followed for up to 3 years with annual assessments. Muscle and pulmonary function outcomes were analyzed herein. Age-stratified statistical analysis and modeling were conducted to analyze cross-sectional data, time-to-event data, and longitudinal data to characterize these clinical outcomes. RESULTS: Deletion mutations of dystrophin exons 45-47 or 45-48 were most common. Subgroup analysis showed greater pairwise association between motor outcomes at baseline than association between these outcomes and age. Stronger correlations between outcomes for adults than for those under 18 years were also observed. Using cross-sectional binning analysis, a ceiling effect was seen for North Star Ambulatory Assessment but not for other functional outcomes. Longitudinal analysis showed a decline in percentage predicted forced vital capacity over the life span. There was relative stability or improved median function for motor functional outcomes through childhood and adolescence and decreasing function with age thereafter. CONCLUSIONS: There is variable progression of outcomes resulting in significant heterogeneity of the clinical phenotype of Becker muscular dystrophy. Disease progression is largely manifest in adulthood. There are implications for clinical trial design revealed by this longitudinal analysis of a Becker natural history dataset.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".