215 Active arthritis is associated with 14–3–beta titre in patients with systemic lupus erythematosus
Bibliographic record
Abstract
<h3>Background and aims</h3> Non-erosive arthritis is common in systemic lupus erythematosus (SLE). 14-3-3 eta, a chaperone protein that activates pro-inflammatory pathways is emerging as a novel biomarker for erosive Rheumatoid Arthritis. We investigated clinical associations of serum 14-3-3 eta in SLE focusing on arthritis. <h3>Methods</h3> Sociodemographics, ACR criteria, and SLEDAI were recorded. Arthritis, assessed by the SLEDAI, was categorised as active (n=78), inactive (n=138) and never present (n=49). Serum 14-3-3 eta was measured by ELISA; titres above 0.19 ng/ml were considered positive. We report descriptive statistics and logistic regression models testing the association of 14-3-3eta with arthritis state. <h3>Results</h3> SLE patients (n=265) were mainly female (92%), Caucasian (67%) with a mean (SD) age of 51.7 (14) years, and median (25%,75%) disease duration of 8 (4,10) years, number ACR criteria of 6 (5,7), and SLEDAI of 4 (2,7). 241 (81%) had active or inactive arthritis. 14-3-3 eta positivity was similar across the three arthritis groups (active 22/78 (28%), inactive 27/138 (20%), never present 10/49 (20%) with a median (25%75%) titre of 0.6 ng/ml (0.34, 1.82). The highest quartile of 14-3-3eta associated with active arthritis (OR 3.6 (95% CI 1.33, 9.98) p-0.012) after adjusting for ethnicity and SLEDAI. There were no differences in 14-3-3 eta positivity for other lupus criteria nor correlation of 14-3-3 eta titer with number of ACR criteria or SLEDAI. <h3>Conclusions</h3> 14-3-3 eta titers are highest in lupus patients with active arthritis suggesting a higher risk for more severe arthritis. Further work will explore the associations of 14-3-3 eta in lupus with erosive arthritis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".