Risk factors analysis and risk assessment model construction of systemic lupus erythematosus patients with infection

Abstract

Objective To analyze the characteristics of peripheral blood lymphocyte subsets in systemic lupus erythematosus (SLE) patients with infection and non-infection group. Explore the risk factors of infection in SLE patients and establish a risk matrix model to predict the occurrence of co-infection. Methods total of 333 SLE patients without infection, 163 patients suffering from infection, and 132 healthy controls (HCs) were recruited. General clinical data and disease activity indicators were collected. The levels of total T, B, CD4+T, CD8+T, NK, Th1, Th2, Th17, and Treg cells in peripheral blood of HCs, SLE patients (including infected and non-infected group) were analyzed by flow cytometry. The risk assessment model was constructed, and the receiver operating characteristic curve was drawn. 39 SLE patients with infection and 20 patients without infection were randomly selected to evaluate the predictive power of the regression model. Results The levels of T, B, CD4+T, CD8+T, and NK cells in the infected patients were significantly decreased when compared with that of both non-infected patients and HCs ( p < .05). The non-infected patients had a higher level of Th17 than that of HCs ( p < . 05), but the absolute numbers of Th17 in infected patients was the lowest among the three groups ( p < .001). The number of Treg cells in SLE patients was significantly lower than that of HCs ( p < .01), and the infected patients had the fewest Treg cells among all these groups ( p < . 05). A risk assessment model for SLE with infection was established, p = 1/(1−e−y), Y = 1.763-0.004 × Absolute number of CD4 + T cells-0.005 × Absolute number of NK cells −0.005 × Platelet count(×1012/L) + 1.033 × Absolute number of lymphocytes (×109/L) + 0.023 × C-reactive protein (mg/dL), whose predictive sensitivity is 77.5%, and specificity is 78.3%. Conclusion The new risk assessment model exhibits good predictive ability to assess co-infection risk in SLE patients. T cells, NK cells, and CD4 + T cells along with other parameters help in differentiating Lupus with infection from Lupus alone.