Early Illness Features Associated With Mortality in the Juvenile Idiopathic Inflammatory Myopathies
Bibliographic record
Abstract
OBJECTIVE: Because juvenile idiopathic inflammatory myopathies (IIMs) are potentially life-threatening systemic autoimmune diseases, we examined risk factors for juvenile IIM mortality. METHODS: Mortality status was available for 405 patients (329 with juvenile dermatomyositis [DM], 30 with juvenile polymyositis [PM], and 46 with juvenile connective tissue disease-associated myositis [CTM]) enrolled in nationwide protocols. Standardized mortality ratios (SMRs) were calculated using US population statistics. Cox regression analysis was used to assess univariable associations with mortality, and random survival forest (RSF) classification and Cox regression analysis were used for multivariable associations. RESULTS: Of 17 deaths (4.2% overall mortality), 8 (2.4%) were in juvenile DM patients. Death was related to the pulmonary system (primarily interstitial lung disease [ILD]) in 7 patients, gastrointestinal system in 3, and multisystem in 3, and of unknown etiology in 4 patients. The SMR for juvenile IIMs overall was 14.4 (95% confidence interval [95% CI] 12.2-16.5) and was 8.3 (95% CI 6.4-10.3) for juvenile DM. The top mortality risk factors in the univariable analysis included clinical subgroup (juvenile CTM, juvenile PM), antisynthetase autoantibodies, older age at diagnosis, ILD, and Raynaud's phenomenon at diagnosis. In multivariable analyses, clinical subgroup, illness severity at onset, age at diagnosis, weight loss, and delay to diagnosis were the most important predictors from RSF; clinical subgroup and illness severity at onset were confirmed by multivariable Cox regression analysis. CONCLUSION: Overall mortality was higher in juvenile IIM patients, and several early illness features were identified as risk factors. Clinical subgroup, antisynthetase autoantibodies, older age at diagnosis, and ILD are also recognized as mortality risk factors in adult myositis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".