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Updated: Aug 30, 2025

The bm12 Inducible Model of Systemic Lupus Erythematosus SLE in C57BL/6 Mice
Published on: November 1, 2015
Major infections in newly diagnosed systemic lupus erythematosus: an inception cohort study
Haiting Wang1, Yuhong Zhou2, Liqin Yu3
1Department of Rheumatology, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, Huangpu, China.
Objective:
To evaluate the risk of major infections and the relationship between major infections and mortality in patients with newly diagnosed SLE.
Methods:
A newly diagnosed (<3 months) hospitalised Systemic Lupus Inception Cohort (hSLIC) in our centre during 1 January 2013 and 1 November 2020 was established. All patients were followed up for at least 1 year or until death. Patient baseline characteristics were collected. Major infection events were recorded during follow-up, which were defined as microbiological/clinical-based diagnosis treated with intravenous antimicrobials. The cohort was further divided into a training set and a testing set. Independent predictors of major infections were identified using multivariable logistic regression analysis. Kaplan-Meier survival analyses were conducted.
Results:
Among the 494 patients enrolled in the hSLIC cohort, there were 69 documented episodes of major infections during the first year of follow-up in 67 (14%) patients. The major infection events predominantly occurred within the first 4 months since enrolment (94%, 65/69) and were associated with all-cause mortality. After adjustments for glucocorticoid and immunosuppressant exposure, a prediction model based on SLE Disease Activity Index >10, peripheral lymphocyte count <0.8×109/L and serum creatinine >104 µmol/L was established to identify patients at low risk (3%-5%) or high risk (37%-39%) of major infections within the first 4 months.
Conclusions:
Newly onset active SLE is susceptible to major infections, which is probably due to underlying profound immune disturbance. Identifying high-risk patients using an appropriate prediction tool might lead to better tailored management and better outcome.
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