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ArticleClinical rheumatology2026

Seizures as a marker of severe multi-organ involvement in neuropsychiatric systemic lupus erythematosus: a diagnostic risk stratification study.

Xiaoli Zhang, Muyao Guo, Zhiqin Wang, Xiujiao Wang, Qiang Wang, Xiaoxia Zuo, Qian Gao, Jiaxin Wang

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Article in Clinical rheumatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Xiaoli ZhangDepartment of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, China.
Muyao GuoDepartment of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, China.
Zhiqin WangDepartment of Geriatric Neurology, Xiangya Hospital of Central South University, Changsha, China.
Xiujiao WangDepartment of Rheumatology, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China.
Qiang WangDepartment of Rheumatology, The First Affiliated Hospital With Nanjing Medical University, Nanjing, Jiangsu, China.
Xiaoxia ZuoDepartment of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, China.
Qian GaoDepartment of Clinical Laboratory, Xiangya Hospital of Central South University, Changsha, China. gaoqian@csu.edu.cn.
Jiaxin WangDepartment of Clinical Laboratory, Xiangya Hospital of Central South University, Changsha, China. wangjiaxin_0502@163.com.ORCID http://orcid.org/0009-0004-0351-854X

Funding

National Natural Science Foundation of China 81901662
6 · The paper itself

Abstract

objectiveThis study aimed to identify independent predictors of seizure occurrence in patients with neuropsychiatric systemic lupus erythematosus (NPSLE), develop a diagnostic model, and evaluate whether seizures are associated with adverse renal outcomes.

methodsA retrospective cohort of 169 patients with NPSLE from Xiangya Hospital was analyzed. Among 70 pre-specified clinical, laboratory, and imaging variables, 20 variables associated with seizure occurrence (p < 0.05 in univariable logistic regression) were retained after multicollinearity screening (VIF < 5.0). Multivariable logistic regression was then performed to identify independent predictors of SE-NPSLE. Machine learning algorithms with fivefold cross-validation were then employed to develop and optimize the diagnostic model. Model performance was evaluated using sensitivity, specificity, accuracy, and AUC metrics. External validation was performed using an independent cohort (n = 46) from Jiangsu Provincial People's Hospital. Renal survival rates were assessed by Kaplan-Meier analysis with log-rank tests.

resultsIndependent predictors of SE-NPSLE included anti-Rib-P antibody (OR = 0.315, 95% CI: 0.121-0.819), erythrocyte sedimentation rate (ESR) (OR = 0.973 per mm/h, 95% CI: 0.954-0.992), and presence of psychosis (OR = 0.194, 95% CI: 0.057-0.659). A logistic regression-based nomogram (AUC: 0.818 training, 0.800 validation) demonstrated robust performance. External validation (n = 46) yielded an AUC of 0.706. What is more, NPSLE patients with seizures (SE-NPSLE) demonstrated significantly worse renal outcomes compared to NPSLE patients without seizures (non-SE-NPSLE).

conclusionSeizures in NPSLE are associated with poor renal prognosis. Our diagnostic model was developed to facilitate early risk assessment and may aid personalized seizure management; however, its clinical utility requires validation in larger, prospective cohorts. Key Points • A validated diagnostic model indentifies high-risk NPSLE patients for seizures. • 3 independent predictors of SE-NPSLE included anti-Rib-P antibodies, ESR and psychosis. • SE-NPSLE patients were youner, had higher SLEDAI, and exhibited more severe renal dysfunction than non-SE-NPSLE patients.

Indexed as

ESKDLupus nephritisNPSLESLE

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