Mortality Trends and Causes of Death in Myotonic Dystrophy Type 1 Patients From the UK Clinical Practice Research Datalink
Bibliographic record
Abstract
INTRODUCTION/AIM: Patients with myotonic dystrophy type1 (DM1) have reduced lifespan. This study aimed to quantify mortality risks, and evaluate causes and time trends in DM1. METHODS: We identified 1021 DM1 patients and 15,104 matched DM1-free controls from the United Kingdom (UK) Clinical Practice Research Datalink. We used Cox proportional hazards regression models to assess differences in all-cause or cause-specific mortality between DM1 patients and matched controls, and computed standardized mortality ratios (SMRs) for comparisons of DM1 patients with the UK general population. RESULTS: DM1 patients were at higher risk of death compared with matched DM1-free controls (hazard ratio [HR] = 2.9, 95% confidence interval [CI] = 2.5-3.4) or the general UK population (SMR = 8.1, 95% CI = 7.3-9.1). The excess risk was primarily attributed to deaths from respiratory failure (HR = 26.7, p < 0.001), aspiration pneumonia (HR = 15.8, p < 0.001), arrythmia, and conduction defects (HR = 15.7, p < 0.001). No mortality risk difference between DM1 patients and matched DM1-free cohort was noted for all cancers combined (p = 0.52). No significant calendar time-related changes in overall survival were seen for DM1 patients (p trend = 0.19). In mortality cause-specific analysis, and compared with patients diagnosed before 1993, death from cancer was on the rise (HR = 2.35, and 5.82 for patients diagnosed 1993-2003, and 2004-2016). DISCUSSION: Most DM1 patients died of known disease complications. This highlights the need for integrated clinical approaches with more careful and frequent monitoring.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".