Objective To investigate the influencing factors for secondary fungal infections in patients with systemic lupus erythematosus (SLE).
Methods A total of 310 SLE patients admitted to our hospital between June 2021 and January 2025 were retrospectively enrolled. They were divided into an infection group and a non-infection group based on the presence or absence of secondary fungal infections. After 5:1 matching using propensity score matching (PSM), 230 patients in the non-infection group and 46 patients in the infection group were included in the final analysis. The characteristics of secondary fungal infections in patients with SLE were analyzed. Logistic regression analysis was performed to identify factors associated with secondary fungal infections, and receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the model. A nomogram model for predicting secondary fungal infections in SLE patients was subsequently established.
Results Among the 310 SLE patients enrolled, fungal infection occurred in 46 cases (14.84%), predominantly involving the lung (50.0%) and the gastrointestinal tract (23.9%). After PSM, binary logistic regression analysis revealed that lupus disease activity (odds ratio OR = 10.734, 95% CI: 2.015-57.184), duration of antibiotic use (OR = 13.826, 95% CI: 2.995-63.822), C-reactive protein (CRP) (OR = 9.927, 95% CI: 1.024-96.188), white blood cell (WBC) count (OR = 11.784, 95% CI: 1.568-88.553), complement C4 (OR = 16.392, 95% CI: 3.899-68.909), and 24-hour urine protein (24 h Pro) (OR = 9.391, 95% CI: 1.195-73.813) were independent risk factors for secondary fungal infections in SLE patients (all P < 0.05). ROC curve analysis demonstrated that lupus disease activity, duration of antibiotic use, CRP, WBC count, complement C4, and 24 h Pro all demonstrated predictive value for secondary fungal infections. The combined model incorporating all 6 indicators achieved an area under the ROC curve (AUC) of 0.821 (95% CI: 0.720-0.922), outperforming any individual indicator (AUC range: 0.593-0.672). A nomogram prediction model was subsequently established based on these 6 indicators.
Conclusion Lupus activity, duration of antibiotic use, CRP, WBC, complement C4, and 24 h Pro are the influencing factors of secondary fungal infection in SLE patients.