Predictors of Remission and Low Disease Activity State in Systemic Lupus Erythematosus: Data from a Multiethnic, Multinational Latin American Cohort
Bibliographic record
Abstract
OBJECTIVE: To determine the predictors of remission and low disease activity state (LDAS) in patients with systemic lupus erythematosus (SLE). METHODS: Three disease activity states were defined: Remission = SLE Disease Activity Index (SLEDAI) = 0 and prednisone ≤ 5 mg/day and/or immunosuppressants (maintenance dose); LDAS = SLEDAI ≤ 4, prednisone ≤ 7.5 mg/day and/or immunosuppressants (maintenance dose); and non-optimally controlled state = SLEDAI > 4 and/or prednisone > 7.5 mg/day and/or immunosuppressants (induction dose). Antimalarials were allowed in all groups. Patients with at least 2 SLEDAI reported and not optimally controlled at entry were included in these analyses. Outcomes were remission and LDAS. Multivariable Cox regression models (stepwise selection procedure) were performed for remission and for LDAS. RESULTS: Of 1480 patients, 902 were non-optimally controlled at entry; among them, 196 patients achieved remission (21.7%) and 314 achieved LDAS (34.8%). Variables predictive of a higher probability of remission were the absence of mucocutaneous manifestations (HR 1.571, 95% CI 1.064-2.320), absence of renal involvement (HR 1.487, 95% CI 1.067-2.073), and absence of hematologic involvement (HR 1.354, 95% CI 1.005-1.825); the use of immunosuppressive drugs before the baseline visit (HR 1.468, 95% CI 1.025-2.105); and a lower SLEDAI score at entry (HR 1.028, 95% CI 1.006-1.051 per 1-unit decrease). These variables were predictive of LDAS: older age at entry, per 5-year increase (HR 1.050, 95% CI 1.004-1.098); absence of mucocutaneous manifestations (HR 1.401, 95% CI 1.016-1.930) and renal involvement (HR 1.344, 95% CI 1.049-1.721); and lower SLEDAI score at entry (HR 1.025, 95% CI 1.009-1.042). CONCLUSION: Absence of mucocutaneous, renal, and hematologic involvement, use of immunosuppressive drugs, and lower disease activity early in the course of the disease were predictive of remission in patients with SLE; older age was predictive of LDAS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".