Secondary Sjögren’s Syndrome in Systemic Lupus Erythematosus Defines a Distinct Disease Subset
Bibliographic record
Abstract
OBJECTIVE: Sjögren's syndrome (SS) may occur in patients with systemic lupus erythematosus (SLE). We sought to determine whether the presence of SS in a large cohort of patients with SLE defines a subset with distinctive sociodemographic, clinical, and laboratory features. METHODS: The Johns Hopkins Lupus Cohort was divided into 2 groups, based on the presence or absence of SS, defined by the presence of an objective measure of sicca or an abnormal minor salivary gland biopsy in a patient with sicca symptoms. These groups were compared with regard to sociodemographic, clinical, and laboratory features. Multivariable logistic regression was then performed to adjust the findings for potential sociodemographic, clinical, and laboratory confounders. RESULTS: The 259 patients with SS (14% of the cohort), when compared with the 1531 patients without SS, were older at the time of SLE diagnosis and were more commonly women and white. Photosensitivity, oral ulcers, Raynaud's phenomenon, anti-Ro antibodies, and anti-La antibodies had a significant positive association while renal disease, anti-ribonucleoprotein (RNP) antibodies, and anti-dsDNA antibodies had a negative association with the presence of SS after adjustment for age (at last cohort visit), gender, ethnicity, and anti-Ro antibodies. The older age at diagnosis of SLE among the patients with SS did not remain a significant finding after adjustment for the age of the patient at last cohort visit. CONCLUSION: The subset of patients with SLE and SS has a distinct clinical and laboratory phenotype, with a higher frequency of older white women with photosensitivity, oral ulcers, Raynaud's phenomenon, anti-Ro antibodies, and anti-La antibodies and a lower frequency of renal disease, anti-dsDNA antibodies, and anti-RNP antibodies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".