EVALUATION OF ACCRUAL DAMAGE IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: COMPARISON OF DATA FROM THE NATIONAL CROSS-SECTIONAL AND PROSPECTIVE LUPUS REGISTRY
Bibliographic record
Abstract
PV229 / #359 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose Adequate control of disease activity and early therapeutic interventions can minimize damage in Systemic Lupus Erythematosus (SLE). The objective of this study was to describe and compare damage in patients with SLE from the national cross-sectional (CS) and prospective (P) registries of the Argentine Society of Rheumatology (RELESSAR) and to assess associated factors. Methods A cross-sectional study was performing using 2 national lupus registries: the cross-sectional (RELESSAR-CS) and the prospective (RELESSAR-P) ones. Data from 1648 patients across 67 centers were analyzed, with 9-year difference between both initiatives. Sociodemographic data, clinical manifestations, hospitalizations, activity and damage scores in patients with less than 5 years of SLE evolution were analyzed. Statistical analysis: Descriptive statistics, Chi2, Fisher, Student’s t, or Wilcoxon tests as appropriate. Univariate/multivariate logistic regression identified factors associated with accrual damage. Results Data were collected from RELESSAR-CS (n=1515) and the baseline visit of RELESSAR-P (n=133). Cumulative damage was assessed by domain, with the musculoskeletal and renal domains being the most affected, the first in RELESSAR-CS and the second in RELESSAR-P. Patients with disease duration of less than 5 years from both registries were compared. It was observed that patients in RELESSAR-CS were younger (p=0.002), had a longer diagnostic delay (p<0.001), and had lower use of rituximab (p<0.001). No differences were found in cumulative damage. Comparisons were made between patients with (n=311) and without cumulative damage (n=428) from both registries. Patients with a SLICC/SDI score ≥1 were older (36 [26-47] vs 31 [25-41], p<0.001) and had a higher frequency of male sex (14% vs 9%, p=0.046), mestizos (58% vs 44%, p<0.001), and lower educational level (12 [10-15] vs 12 [11-15], p=0.019). Additionally, they exhibited higher SLEDAI disease activity (2 [0-6] vs 1 [0-4], p=0.008) and greater use of methotrexate (26% vs 18%, p=0.021), cyclophosphamide (38% vs 21%, p<0.001), and mycophenolate mofetil (27% vs 19%, p=0.021). They also had higher rates of hospitalizations (64% vs 44%, p<0.001) and infections (18% vs 9%, p<0.001). Age, mestizo ethnicity, SLEDAI score, and the use of methotrexate and cyclophosphamide were independently associated with cumulative damage. Conclusions Musculoskeletal domain was affected less frequently in the prospective registry, which could be associated with lower frequency of avascular necrosis and lower use of corticosteroids. Age, mestizo ethnicity, SLEDAI, and the use of methotrexate and cyclophosphamide were significantly associated with damage.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".