DERMATOLOGIC INDICATORS OF RHEUMATIC DISEASES: INSIGHTS FROM ANTINUCLEAR ANTIBODY TESTING IN OUTPATIENT SETTINGS
Bibliographic record
Abstract
PV026 / #271 Poster Topic: AS04 - Biomarkers Background/Purpose Cutaneous symptoms frequently signal rheumatic diseases, sometimes presenting early in their course. This study assesses the prevalence of antinuclear antibody (ANA) positivity in dermatology patients, the frequency of rheumatic disease diagnoses made via ANA testing, and the associated dermatological presentations and antibody patterns in a single-center tertiary care setting. Methods Data were collected retrospectively from dermatology outpatient visits between January 1, 2013, and December 31, 2023, at a national tertiary hospital. ANA titers and patterns were analyzed for patients with positive ANA results, excluding those with prior rheumatology visits or known rheumatic diseases. Patients with positive ANA were further examined for rheumatologic and dermatologic diagnoses. Results Of 8,347 dermatology patients who underwent ANA testing, 1,054 (12.7%) had positive results and were referred to rheumatology. Positive ANA titers included 1:80 in 332 patients (31.5%), 1:160 in 167 patients (15.8%), and 1:1280 or higher in 33 patients (3.1%). Among those referred, 59 patients (5.6%) were diagnosed with rheumatic diseases: 32 patients (55.9%) with Sjögren’s syndrome, 24 (39.0%) with systemic lupus erythematosus (SLE), 2 (3.4%) with systemic sclerosis, and 1 (1.7%) with mixed connective tissue disease. Dermatologic diagnoses in Sjögren’s syndrome patients included dermatitis (24.2%), urticaria (15.1%), benign skin tumors (15.1%), pruritus (15.1%), and alopecia (9.0%). ANA titers were 1:1280 in 24.2% and 1:160 or higher in 72.6% of Sjögren’s syndrome cases. For SLE patients, dermatologic conditions included dermatitis (25.0%), benign skin tumors (20.8%), rosacea (12.5%), and alopecia (8.3%), with ANA titers of 1:1280 in 25.0% and 1:160 or higher in 83.3% (Figure 1). Figure 1. Conclusions This study underscores the value of ANA testing in dermatologic settings, revealing a noteworthy prevalence of rheumatic diseases in patients presenting with ANA positivity. Sjögren’s syndrome and SLE were the most frequent diagnoses, with distinct dermatologic manifestations and ANA titer patterns. Positive antinuclear antibody results, along with certain skin presentations, may prompt dermatologists to consider possible underlying rheumatic diseases.
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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 | 0.004 |
| 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 | 0.000 |
| 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".