Association between depression and anxiety with skin and musculoskeletal clinical phenotypes in systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVES: To study the clinical phenotypes, determined based on cumulative disease activity manifestations, and sociodemographic factors associated with depression and anxiety in SLE. METHODS: Patients attending a single centre were assessed for depression and anxiety. SLE clinical phenotypes were based on the organ systems of cumulative 10-year SLE Disease Activity Index 2000 (SLEDAI-2K), prior to visit. Multivariable logistic regression analyses for depression, anxiety, and coexisting anxiety and depression were performed to study associated SLE clinical phenotypes and other factors. RESULTS: Among 341 patients, the prevalence of anxiety and depression was 34% and 27%, respectively, while 21% had coexisting anxiety and depression. Patients with skin involvement had significantly higher likelihood of anxiety compared with patients with no skin involvement [adjusted odds ratio (aOR) = 1.8; 95% CI: 1.1, 3.0]. Patients with skin involvement also had higher likelihood of having coexisting anxiety and depression (aOR = 2.0, 95% CI: 1.2, 3.9). Patients with musculoskeletal (MSK) (aOR = 1.9; 95% CI: 1.1, 3.5) and skin system (aOR = 1.8; 95% CI: 1.04, 3.2) involvement had higher likelihood of depression compared with patients without skin or musculoskeletal involvement. Employment status and fibromyalgia at the time of the visit, and inception status were significantly associated with anxiety, depression, and coexisting anxiety and depression, respectively. CONCLUSION: SLE clinical phenotypes, specifically skin or MSK systems, along with fibromyalgia, employment and shorter disease duration were associated with anxiety or depression. Routine patient screening, especially among patients with shorter disease duration, for these associations may facilitate the diagnosis of these mental health disorders, and allow for more timely diagnosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".