Predicting the Risk of Fundus Lesions in Systemic Lupus Erythematosus: A Nomogram Model

Objectives. This study aimed to use laboratory and clinical data of systemic lupus erythematosus (SLE) patients to construct prediction models for fundus complications in SLE. Methods. Routine blood test data and clinical information of 277 SLE patients were collected retrospectively. Based on their fundus examination, they were divided into two groups, with or without fundus lesions, defined as retinopathy and choroidopathy in this study. The data of the two groups were compared, and the prediction model was established using binary logistic regression analysis. Results. There were 85 patients in the fundus lesions’ group and 192 patients in the control group. Between the two groups, age, SLEDAI, serositis, hypertension, diabetes, anticardiolipin antibody (ACA), anti-Sm antibody, C-reactive protein (CRP), hemoglobin (Hb), platelet count (PLT), albumin (Alb), serum creatinine(Scr), urea, uric acid(UA), and immunoglobulin G(IgG) were significantly different (p < 0.05). Besides, age, SLEDAI, serositis, hypertension, diabetes, anti-SSB, CRP, Hb, PLT, FIB, Alb, Scr, urea, UA, GLU, and IgG were significantly correlated with SLE-related fundus lesions. PLT, fibrinogen (FIB), IgG, and urea were independent risk factors of SLE-related fundus lesions. The area under the curve (AUC) was 0.830 (p < 0.001; 95% CI = 0.762–0.898), and the nomogram was established with great evaluation efficiency demonstrated by the calibration curve and the Hosmer–Lemeshow test. The result of k-fold cross-validation also showed high prediction accuracy. Conclusions. We have found the independent risk factors of SLE-related fundus lesions and developed a model to improve the prediction of fundus lesions in SLE.