Factors associated with damage accrual in patients with systemic lupus erythematosus: results from the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND AIMS: We studied damage accrual and factors determining development and progression of damage in an international cohort of systemic lupus erythematosus (SLE) patients. METHODS: The Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort recruited patients within 15 months of developing four or more 1997 American College of Rheumatology (ACR) criteria for SLE; the SLICC/ACR damage index (SDI) was measured annually. We assessed relative rates of transition using maximum likelihood estimation in a multistate model. The Kaplan-Meier method estimated the probabilities for time to first increase in SDI score and Cox regression analysis was used to assess mortality. RESULTS: We recruited 1722 patients; mean (SD) age 35.0 (13.4) years at cohort entry. Patients with damage at enrolment were more likely to have further worsening of SDI (SDI 0 vs ≥1; p<0.001). Age, USA African race/ethnicity, SLEDAI-2K score, steroid use and hypertension were associated with transition from no damage to damage, and increase(s) in pre-existing damage. Male gender (relative transition rates (95% CI) 1.48 (1.06 to 2.08)) and USA Caucasian race/ethnicity (1.63 (1.08 to 2.47)) were associated with SDI 0 to ≥1 transitions; Asian race/ethnicity patients had lower rates of new damage (0.60 (0.39 to 0.93)). Antimalarial use was associated with lower rates of increases in pre-existing damage (0.63 (0.44 to 0.89)). Damage was associated with future mortality (HR (95% CI) 1.46 (1.18 to 1.81) per SDI point). CONCLUSIONS: Damage in SLE predicts future damage accrual and mortality. We identified several potentially modifiable risk factors for damage accrual; an integrated strategy to address these may improve long-term outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it