Disease burden of myotonic dystrophy type 1
Bibliographic record
Abstract
OBJECTIVE: The objective of this cross-sectional, observational study was to investigate the disease burden of myotonic dystrophy type 1 (DM1), a disabling muscle disorder. METHODS: Adults with DM1 were recruited as part of the PhenoDM1 study from Newcastle University (Newcastle upon Tyne, UK). Disease burden data were recorded through the Individualized Neuromuscular Quality of Life (INQoL) questionnaire. Results were examined by sex and clinical variables [e.g. the six-minute walk test (6MWT), the Mini Mental State Examination, and estimated progenitor and modal allele CTG repeat length]. RESULTS: Our sample consisted of 60 patients with DM1 (mean age: 45 years; 45% female). Muscle weakness and fatigue constituted the two most common disease manifestations, reported by 93% and 90% of patients, respectively, followed by muscle locking (73%). Most patients (> 55%) reported feeling anxious/worried, depressed, frustrated, and/or having low confidence/self-esteem, 23% and 33% indicated substantial impairment of daily and leisure activities, respectively, and 47% did not work as a consequence of the disease. Estimated progenitor CTG length corrected by age correlated surprisingly well with INQoL scores. Differences by sex were generally minor. CONCLUSION: We show that DM1 is associated with a substantial disease burden resulting in impairment across many different domains of patients' lives, emphasizing the need for a holistic approach to medical management. Our results also show that the INQoL records relevant information about patients with DM1, but that further investigation of the psychometric properties of the scale is needed for meaningful interpretation of instrument scores.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".