Persistent premature mortality gap in dermatomyositis and polymyositis: a United Kingdom general population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: DM and PM are associated with substantial morbidity and mortality. We aimed to examine recent trends. METHODS: Using The Health Improvement Network, we identified patients with incident DM/PM (defined by ≥1 Read diagnosis code) aged 18-89 years with ≥1 year of continuous enrolment prior to the cohort entry date and up to 10 comparators matched on age, sex and entry year. The cohort was divided in two based on the year of DM/PM diagnosis: the early cohort (1999-2006) and late cohort (2007-2014). We calculated multivariable hazard ratios (HR) for death using a Cox-proportional hazards model and multivariable rate differences (RD) using an additive hazard model. RESULTS: We identified 410 DM cases (mean age: 58 years, 66% female) and 407 PM cases (mean age: 59 years, 61% female). Both DM cohorts had excess mortality compared with the comparison cohorts (71.5 vs 12.9 deaths/1000 person-years [PY] in the early cohort and 49.1 vs 10.4 deaths/1000 PY in the late cohort). The multivariable HRs were 7.51 (95% CI: 4.20, 13.42) in the early cohort and 5.42 (95% CI: 3.11, 9.45) in the late cohort (P-value for interaction = 0.59), and multivariable RDs were 56.2 (95% CI: 31.8, 81.2) in the early cohort and 36.3 (95% CI: 19.6, 53.0) in the late cohort (P-value for interaction = 0.15). A similar trend existed in PM. CONCLUSION: The premature mortality gap in DM/PM has not considerably improved in recent years, highlighting an unmet need for therapeutic improvement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".