Effect of Disease Activity on Organ Damage Progression in Systemic Lupus Erythematosus: University of Toronto Lupus Clinic Cohort
Bibliographic record
Abstract
Objective. To examine the role of disease activity on organ damage over 5 years in patients with active systemic lupus erythematosus (SLE) despite standard of care. Methods. This analysis of the University of Toronto Lupus Clinic cohort assessed organ damage [measured by Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI)] in patients with active SLE [SLE Disease Activity Index 2000 (SLEDAI-2K) ≥ 6], using Cox proportional time-independent hazard models. Subgroup analyses were conducted in patients with SLEDAI-2K 6 or 7, 8 or 9, and ≥ 10 at baseline, and in the overall study population by steroid dose at study entry (< 7.5 vs ≥ 7.5 mg/day). Results. Among the overall study population (n = 649), SDI progression was observed in 209 (32.2%) patients over the 5-year follow-up period. Mean SDI change in patients with a score > 0 was generally consistent across all SLEDAI-2K subgroups. Multivariable analyses identified age at study start (HR 1.03, P < 0.0001), steroid dose (HR 2.03, P < 0.0001), immunosuppressants (HR 1.44, P = 0.021), and SLEDAI-2K (subgroup analyses HR 1.64–2.03, P = 0.0017 to < 0.0001) as the greatest risk factors for SDI progression, while a study start date after the year 2000 had a protective effect on SDI progression compared with a start date prior to the year 2000 (HR 0.65, P = 0.0004). Conclusion. Patients within the higher SLEDAI-2K subgroups at study entry or receiving high doses of steroids were more likely to have organ damage progression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".