Risk factors for damage in childhood‐onset systemic lupus erythematosus: Cumulative disease activity and medication use predict disease damage
Bibliographic record
Abstract
OBJECTIVE: The Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) Damage Index measures damage in adult patients with systemic lupus erythematosus (SLE), but its usefulness in patients with childhood-onset SLE has not been examined. This study was conducted to evaluate the sensibility of the SLICC/ACR Damage Index, to investigate how cumulative disease activity is related to damage in childhood-onset SLE, and to identify other risk factors for damage in childhood-onset SLE. METHODS: Disease activity and damage in 66 patients with newly diagnosed childhood-onset SLE were assessed retrospectively, and information on potential risk factors for damage (age, race, sex, medications, duration of disease, hypertension, body mass index, antiphospholipid antibodies, kidney disease, acute thrombocytopenia) was obtained. In addition, a group of physicians was surveyed to establish the sensibility of the SLICC/ACR Damage Index in childhood-onset SLE. RESULTS: The SLICC/ACR Damage Index was found to have face, content, and construct validity when used in children. The mean SLICC/ACR Damage Index score of the patients was 1.76 (mean followup 3.3 years). Cumulative disease activity over time was the single best predictor of damage (R(2) = 0.30). Other, possibly important risk factors for damage were corticosteroid treatment, the presence of antiphospholipid antibodies, and acute thrombocytopenia. It was determined that immunosuppressive agents may be protective. CONCLUSION: The SLICC/ACR Damage Index, though useful in childhood-onset SLE, may benefit from the introduction of weightings and redefinition of some of the items. Ongoing disease activity leads to disease damage, and treatment should be prompt. Prolonged use of high-dose corticosteroids may further increase damage, but use of immunosuppressive agents may protect against disease damage; this latter finding may have potential implications for the treatment of childhood-onset SLE and deserves further study. The relationship between disease activity and concomitant use of medication also requires further investigation.
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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 | 0.005 |
| 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 | 0.001 |
| 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".