Early Abnormal Nailfold Capillary Changes Are Predictive of Calcinosis Development in Juvenile Dermatomyositis
Bibliographic record
Abstract
Objective The long-term outcomes of juvenile dermatomyositis (JDM) are more favorable in recent years. However, calcinosis is still among the complications that can cause serious functional impairment. Little is known about the pathogenesis and risk factors of calcinosis. The aim of this study is to determine risk factors for the development of calcinosis in JDM. Methods This was a single-center, retrospective cohort study. All patients were diagnosed and followed at the multidisciplinary JDM clinic of The Hospital for Sick Children, from January 1, 1989, until May 31, 2018. To investigate predictors of incident calcinosis, Cox regression analysis was performed. Results A total of 172 patients met inclusion criteria, with a median age at diagnosis of 7.7 years (IQR 4.9-12.1), and a median follow-up of 8.5 years (IQR 3.4-12.6, range 0.1-28.3). The only risk factor significantly associated with the development of calcinosis in the univariate analysis was nailfold abnormality at baseline (hazard ratio [HR] 4.86, P = 0.03). In multivariable analysis, including nailfold abnormality, age of diagnosis, sex, and duration from onset to diagnosis, the only statistically significant risk factor for calcinosis was the presence of nailfold abnormalities (HR 4.98, P = 0.03). Further, calcinosis was significantly increased in patients with a chronic course (chi-square 25.8, P < 0.001). Conclusion The presence of abnormal nailfold capillary changes at baseline is predictive for the development of calcinosis in children with idiopathic inflammatory myopathies.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".