CHARACTERISTICS OF PATIENTS WITH INTERMITTENT AND PERSISTENT TYPE 2 SLE
Bibliographic record
Abstract
PV207 / #177 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose Our prior qualitative work demonstrated there are at least 2 distinct subgroups of Type 2 SLE; one is related to active inflammation (Intermittent Type 2 SLE) and another can be present regardless of inflammation (Persistent Type 2 SLE). The objective of this study was to utilize longitudinal measures of Type 1 and Type 2 SLE activity to characterize these Type 2 SLE subgroups. Methods SLE patients meeting SLICC or ACR criteria were enrolled in a university lupus registry. At each clinic visit, participants completed the Polysymptomatic Distress Scale (PSD), and rheumatologists completed disease activity measures, including the SLEDAI and Physician Global Assessments (PGA) for both Type 1 and Type 2 SLE activity. Patients seen between May 2023 and April 2024 were invited to participate in a substudy that included the FACIT-fatigue scale; PROMIS measures for pain intensity, pain interference, self-efficacy, and psychological stress; and the Trauma History Screen. Only patients who participated in the substudy and had ≥3 visits in the registry were included in the analysis. High Type 1 SLE activity was defined as clinical SLEDAI ≥4, SLEDAI ≥6, active lupus nephritis or PGA ≥1. High Type 2 SLE activity was defined as Type 2 PGA ≥1 or PSD ≥8. Patients who had high Type 1 SLE activity at <30% of visits and high Type 2 SLE activity at ≥50% of visits were classified as Persistent Type 2 SLE. Patients who had fluctuating Type 2 SLE activity were classified as Intermittent Type 2 SLE. Patients who never had high Type 2 SLE activity during follow-up (n=13) were excluded from the analysis. Differences in characteristics between the 2 groups were estimated by t-tests and Fisher’s exact tests. Results The analysis included 183 patients (mean age 45 years, 92% female, 60% Black); 26% of patients had Persistent Type 2 SLE. Demographics were similar between the 2 groups (Table 1). Patients with Persistent Type 2 SLE were more likely to have experienced abusive trauma. While patients with Intermittent Type 2 SLE had higher Type 1 SLE activity over time, approximately half of patients in each group had a history of lupus nephritis, and there were no differences between groups in historical use of prednisone, DMARDs, or biologics. Patients in the Persistent Type 2 SLE group were more likely to have been prescribed a Type 2 SLE medication and to have been prescribed more Type 2 SLE medications over time. By definition, patients with Persistent Type 2 SLE had higher PSD scores during follow-up, yet patients with Intermittent Type 2 SLE still had mild to moderate PSD scores, on average, during follow-up. There were similar self-efficacy scores for managing medications between groups, yet patients with Persistent Type 2 SLE had lower self-efficacy for managing symptoms; they also had worse scores for FACIT-fatigue, PROMIS pain intensity, and pain interference. Table 1. Cohort characteristics. Conclusions One in 4 patients met our study definition for Persistent Type 2 SLE. Despite having taken on average 4 different medications to treat Type 2 SLE symptoms, patients with Persistent Type 2 SLE continued to have a high burden of pain, fatigue, depression, and brain fog, demonstrating a need for better treatment approaches. Several psychosocial stressors could predispose or perpetuate Persistent Type 2, and future work will evaluate these triggers to better understand the etiology and target solutions for these symptoms.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".