Differences between Male and Female Systemic Lupus Erythematosus in a Multiethnic Population
Bibliographic record
Abstract
OBJECTIVE: Male patients with systemic lupus erythematosus (SLE) are thought to be similar to female patients with SLE, but key clinical characteristics may differ. Comparisons were made between male and female patients with SLE in the Hopkins Lupus Cohort. METHODS: A total of 1979 patients in the Hopkins Lupus Cohort were included in the analysis. RESULTS: The cohort consisted of 157 men (66.2% white, 33.8% African American) and 1822 women (59.8% white, 40.2% African American). The mean followup was 6.02 years (range 0-23.73). Men were more likely than women to have disability, hypertension, thrombosis, and renal, hematological, and serological manifestations. Men were more likely to be diagnosed at an older age and to have a lower education level. Women were more likely to have malar rash, photosensitivity, oral ulcers, alopecia, Raynaud's phenomenon, or arthralgia. Men were more likely than women to have experienced end organ damage including neuropsychiatric, renal, cardiovascular, peripheral vascular disease, and myocardial infarction, and to have died. In general, differences between males and females were more numerous and striking in whites, especially with respect to lupus nephritis, abnormal serologies, and thrombosis. CONCLUSION: Our study suggests that there are major clinical differences between male and female patients with SLE. Differences between male and female patients also depend on ethnicity. Future SLE studies will need to consider both ethnicity and gender to understand these differences.
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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 | 0.002 |
| 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 | 0.000 |
| 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".