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Systemic Inflammatory Response Index, a Potential Inflammatory Biomarker in Disease Severity of Myasthenia Gravis: A Pilot Retrospective Study

Authors :
Huang S
Wang Y
Zhu J
Li S
Lin S
Xie W
Chen S
Wang L
Jin Q
Weng Y
Yang D
Source :
Journal of Inflammation Research, Vol Volume 17, Pp 2563-2574 (2024)
Publication Year :
2024
Publisher :
Dove Medical Press, 2024.

Abstract

Suwen Huang,1,* Yanchu Wang,1,2,* Jinrong Zhu,1,3,* Shengqi Li,1,2 Shenyi Lin,1,2 Wei Xie,1,2 Siyao Chen,1,2 Yukai Wang,1,3 Lingsheng Wang,1,2 Qiaoqiao Jin,1,2 Yiyun Weng,1 Dehao Yang4 1Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 2The First School of Medicine, School of Information and Engineering, Wenzhou Medical University, Wenzhou, People’s Republic of China; 3The Second School of Medicine, Wenzhou Medical University, Wenzhou, People’s Republic of China; 4Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yiyun Weng, Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang Street, Ouhai District, Wenzhou, Zhejiang, 325000, People’s Republic of China, Tel +86-0577-55579371, Fax +86-0577-55579318, Email wengyiyun2012@126.com Dehao Yang, Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, People’s Republic of China, Email dehao_yang@zju.edu.cnPurpose: Myasthenia gravis (MG) is a chronic autoimmune disease caused by neuromuscular junction (NMJ) dysfunction. Our current understanding of MG’s inflammatory component remains poor. The systemic inflammatory response index (SIRI) presents a promising yet unexplored biomarker for assessing MG severity. This study aimed to investigate the potential relationship between SIRI and MG disease severity.Patients and Methods: We conducted a retrospective analysis of clinical data from 171 MG patients admitted between January 2016 and June 2021. Patients with incomplete data, other autoimmune diseases, or comorbidities were excluded. Disease severity was evaluated using the Myasthenia Gravis Foundation of America (MGFA) classification and Myasthenia Gravis Activities of Daily Living (MG-ADL) on admission. The association between SIRI and disease severity was assessed through logistic regression analysis, along with receiver operating characteristic (ROC) curve and decision curve analysis (DCA) comparisons with established inflammation indicators.Results: After exclusion, 143 patients were analyzed in our study. SIRI levels significantly differed between patients with higher and lower disease severity (p < 0.001). Univariate logistic regression showed that SIRI had a significant effect on high disease severity (OR = 1.376, 95% CI 1.138– 1.664, p = 0.001). This association remained significant even after adjusting for age, sex, disease duration, history of MG medication and thymoma (OR = 1.308, 95% CI 1.072– 1.597, p = 0.008). Additionally, a positive correlation between SIRI and MG-ADL was observed (r = 0.232, p = 0.008). Significant interactions were observed between SIRI and immunosuppressor (p interaction = 0.001) and intravenous immunoglobulin (p interaction = 0.005). DCA demonstrated the superior net clinical benefit of SIRI compared to other markers when the threshold probability was around 0.2.Conclusion: Our findings indicate a strong independent association between SIRI and disease severity in MG, suggesting SIRI’s potential as a valuable biomarker for MG with superior clinical benefit to currently utilized markers.Keywords: inflammation, myasthenia gravis foundation of America, MGFA, blood cell count, correlation, systemic inflammatory response index

Details

Language :
English
ISSN :
11787031
Volume :
ume 17
Database :
Directory of Open Access Journals
Journal :
Journal of Inflammation Research
Publication Type :
Academic Journal
Accession number :
edsdoj.45c2f5e9b589473eab95c16e1f4e160f
Document Type :
article