Sex Differences in Clinical Manifestations of Hospitalized Patients With Eosinophilic Granulomatosis With Polyangiitis: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of sex on the clinical characteristics, prognoses, and therapeutic selection of eosinophilic granulomatosis with polyangiitis (EGPA). METHODS: We retrospectively enrolled 170 hospitalized patients with EGPA who were managed at our hospital between 2007 and 2020. Detailed clinical data were reviewed. Manifestations, prognoses, treatments, and outcomes were compared between female and male patients. Cumulative survival rates were calculated using Kaplan-Meier curves. RESULTS: In this cohort, the male to female ratio was 1.4:1. Renal involvement was more frequent in male patients, including serum creatinine elevation, and proteinuria > 1 g/24 h. Severe gastrointestinal (GI) involvement occurred more commonly in male patients. Female patients had longer allergy duration and higher ratios of allergic rhinitis and asthma. Sex differences in proteinuria > 1 g/24 h, serum creatinine > 150 mmol/L, severe GI involvement, and weight loss were more significant in patients aged ≤ 55 years than those in patients aged > 55 years. Overall, male patients had a higher Birmingham Vasculitis Activity Score and a worse prognosis assessed at diagnosis, with a lower proportion of 1996 Five Factor Score = 0 than females. Regarding treatment selection, methylprednisolone pulse and cyclophosphamide were administered more frequently to male patients. All-cause mortality and cumulative survival rates were comparable between the sexes. CONCLUSION: In this Chinese EGPA cohort, male and female patients showed distinct disease phenotypes. Male patients with EGPA had a higher disease activity at diagnosis and required more aggressive treatment for remission induction.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".