BARICITINIB FOR THE TREATMENT OF RHUPUS SYNDROME
Bibliographic record
Abstract
PV258a / #409 Poster Topic: AS24 - SLE-Treatment Background/Purpose The “Rhupus syndrome” is a rarely described and underdiagnosed disease that exhibits characteristics of both rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) in the same patient, often presenting more frequently in a sequential manner. Since there is no validated therapeutic strategy, treatment is based on clinicians’ experience with approved treatments for either of the 2 entities, generally based on the predominant clinical manifestations. Methods We conducted a retrospective observational review of medical records from the Rheumatology Department at our hospital between 2019 and 2023, identifying patients diagnosed with Rhupus, who received baricitinib. The diagnosis of Rhupus was assigned to patients who met the diagnostic criteria for both Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE). The study involves a comprehensive analysis of clinical outcomes and medication safety profiles for these patients. Results A total of 8 patients diagnosed with Rhupus undergoing baricitinib treatment were included. 87.5% were female (median age of 60.5 years, and median follow-up of 12 years). The predominant clinical presentation was RA in 75% of the patients and SLE symptoms in 25%. All patients were ANA positive, while 75% had anti-citrullinated protein antibodies (ACPA) and 87.5% were rheumatoid factor (RF) positive. At the initiation of baricitinib treatment, 62.5% were also taking methotrexate, 37.5% were on hydroxychloroquine, and the median dose of prednisone was 8.75 mg/day. The median duration of baricitinib treatment was 2.5 years. Data on the evolution of activity parameters during the treatment are presented in Table 1. Table 1. Evolution of activity parameters during treatment. There were 3 reports of serious infections, 2 due to Herpes zoster infections, 1 of which required suspension of treatment. Conclusions Baricitinib, possibly in combination with other DMARDs, appears to be a promising option for the management of Rhupus, offering benefits in terms of reducing disease activity and improving patient quality of life. These preliminary findings warrant further investigation with larger sample sizes to confirm the efficacy and safety of baricitinib in Rhupus.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".