Construction and Validation of a Dynamic Nomogram Using Lasso-logistic Regression for Predicting the Severity of Severe Fever with Thrombocytopenia Syndrome Patients at Admission

Overview

Journal BMC Infect Dis

Publisher Biomed Central

Specialty Infectious Diseases

Date 2024 Sep 18

PMID 39294596

Authors

Peng Xia

Yu Zhai

Xiaodi Yan

Haopeng Li

Hanwen Tong

Jun Wang

Yun Liu

Weihong Ge

Chenxiao Jiang

Affiliations

Soon will be listed here.

Abstract

Background: Severe fever with thrombocytopenia syndrome (SFTS) is a highly fatal infectious disease caused by the SFTS virus (SFTSV), posing a significant public health threat. This study aimed to construct a dynamic model for the early identification of SFTS patients at high risk of disease progression.

Methods: All eligible patients enrolled between April 2014 and July 2023 were divided into training and validation sets. Thirty-four clinical variables in the training set underwent analysis using least absolute shrinkage and selection operator (LASSO) logistic regression. Selected variables were then input into the multivariate logistic regression model to construct a dynamic nomogram. The model's performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) in both training and validation sets. Kaplan-Meier survival analysis was utilized to evaluate prognostic performance.

Results: 299 SFTS patients entered the final investigation, with 208 patients in the training set and 90 patients in the validation set. LASSO and the multivariate logistic regression identified six significant prediction factors: age (OR, 1.060; 95% CI, 1.017-1.109; P = 0.007), CREA (OR, 1.017; 95% CI, 1.003-1.031; P = 0.019), PT (OR, 1.765; 95% CI, 1.175-2.752; P = 0.008), D-dimer (OR, 1.039; 95% CI, 1.005-1.078; P = 0.032), nervous system symptoms (OR, 8.244; 95% CI, 3.035-26.858; P < 0.001) and hemorrhage symptoms (OR, 3.414; 95% CI, 1.096-10.974; P = 0.035). The AUC-ROC, C-index, calibration plots, and DCA demonstrated the robust performance of the nomogram in predicting severity at admission, and Kaplan-Meier survival analysis indicated its utility in predicting 28-day mortality among SFTS patients. The dynamic nomogram is accessible at https://sfts.shinyapps.io/SFTS_severity_nomogram/ .

Conclusion: This study provided a practical and readily applicable tool for the early identification of high-risk SFTS patients, enabling the timely initiation of intensified treatments and protocol adjustments to mitigate disease progression.

References

Zohaib A, Zhang J, Saqib M, Athar M, Hussain M, Chen J . Serologic Evidence of Severe Fever with Thrombocytopenia Syndrome Virus and Related Viruses in Pakistan. Emerg Infect Dis. 2020; 26(7):1513-1516. PMC: 7323538. DOI: 10.3201/eid2607.190611. View

Guo C, Wang H, Wang X, Tian S . High CRP/PNI levels predict an unfavorable prognosis in severe fever with thrombocytopenia syndrome: A propensity score matching study. Immun Inflamm Dis. 2024; 12(2):e1184. PMC: 10877553. DOI: 10.1002/iid3.1184. View

Zheng S, Lubin B, Au R, Murabito J, Benjamin E, Shwartz M . Advantages of Continuous-Valued Risk Scores for Predicting Long-Term Costs: The Framingham Coronary Heart Disease 10-Year Risk Score. Adv Geriatr Med Res. 2019; 1(1). PMC: 6707532. DOI: 10.20900/agmr20190004. View

Liu Y, Wu B, Paessler S, Walker D, Tesh R, Yu X . The pathogenesis of severe fever with thrombocytopenia syndrome virus infection in alpha/beta interferon knockout mice: insights into the pathologic mechanisms of a new viral hemorrhagic fever. J Virol. 2013; 88(3):1781-6. PMC: 3911604. DOI: 10.1128/JVI.02277-13. View

He F, Zheng X, Zhang Z . Clinical features of severe fever with thrombocytopenia syndrome and analysis of risk factors for mortality. BMC Infect Dis. 2021; 21(1):1253. PMC: 8669668. DOI: 10.1186/s12879-021-06946-3. View

Wang Y, Song Z, Xu X, Wei X, Yuan H, Liang H . Clinical symptoms associated with fatality of severe fever with thrombocytopenia syndrome: A systematic review and meta-analysis. Acta Trop. 2022; 232:106481. DOI: 10.1016/j.actatropica.2022.106481. View

Fecher A, Stimpson A, Ferrigno L, Pohlman T . The Pathophysiology and Management of Hemorrhagic Shock in the Polytrauma Patient. J Clin Med. 2021; 10(20). PMC: 8541346. DOI: 10.3390/jcm10204793. View

Win A, Nguyen Y, Kim Y, Ha N, Kang J, Kim H . Genotypic Heterogeneity of Orientia tsutsugamushi in Scrub Typhus Patients and Thrombocytopenia Syndrome Co-infection, Myanmar. Emerg Infect Dis. 2020; 26(8):1878-1881. PMC: 7392420. DOI: 10.3201/eid2608.200135. View

Yu X . Risk factors for death in severe fever with thrombocytopenia syndrome. Lancet Infect Dis. 2018; 18(10):1056-1057. DOI: 10.1016/S1473-3099(18)30312-8. View

10.

Ding S, Niu G, Xu X, Li J, Zhang X, Yin H . Age is a critical risk factor for severe fever with thrombocytopenia syndrome. PLoS One. 2014; 9(11):e111736. PMC: 4219771. DOI: 10.1371/journal.pone.0111736. View

11.

Wang X, Lin L, Zhao Z, Zhou W, Ge Z, Shen Y . The predictive effect of the platelet-to-lymphocyte ratio (PLR) and the neutrophil-to-lymphocyte ratio (NLR) on the risk of death in patients with severe fever with thrombocytopenia syndrome (SFTS): a multi-center study in China. Ann Transl Med. 2021; 9(3):208. PMC: 7940944. DOI: 10.21037/atm-20-4736. View

12.

Qian F, Zhou W, Liu Y, Ge Z, Lai J, Zhao Z . High C-reactive protein to lymphocyte ratio predicts mortality outcomes of patients with severe fever with thrombocytopenia syndrome: A multicenter study in China. J Med Virol. 2023; 95(2):e28546. DOI: 10.1002/jmv.28546. View

13.

Xia G, Sun S, Zhou S, Li L, Li X, Zou G . A new model for predicting the outcome and effectiveness of drug therapy in patients with severe fever with thrombocytopenia syndrome: A multicenter Chinese study. PLoS Negl Trop Dis. 2023; 17(3):e0011158. PMC: 10019728. DOI: 10.1371/journal.pntd.0011158. View

14.

Altman D, Royston P . The cost of dichotomising continuous variables. BMJ. 2006; 332(7549):1080. PMC: 1458573. DOI: 10.1136/bmj.332.7549.1080. View

15.

Wang G, Xu Y, Zhu Y, Yue M, Zhao J, Ge H . Clinical efficacy of low-dose glucocorticoid therapy for critically ill patients with severe fever with thrombocytopenia syndrome: A retrospective cohort study. Int J Infect Dis. 2023; 130:153-160. DOI: 10.1016/j.ijid.2023.03.015. View

16.

Rattanakomol P, Khongwichit S, Linsuwanon P, Lee K, Vongpunsawad S, Poovorawan Y . Severe Fever with Thrombocytopenia Syndrome Virus Infection, Thailand, 2019-2020. Emerg Infect Dis. 2022; 28(12):2572-2574. PMC: 9707585. DOI: 10.3201/eid2812.221183. View

17.

Cui N, Liu R, Lu Q, Wang L, Qin S, Yang Z . Severe fever with thrombocytopenia syndrome bunyavirus-related human encephalitis. J Infect. 2014; 70(1):52-9. DOI: 10.1016/j.jinf.2014.08.001. View

18.

Yu X, Liang M, Zhang S, Liu Y, Li J, Sun Y . Fever with thrombocytopenia associated with a novel bunyavirus in China. N Engl J Med. 2011; 364(16):1523-32. PMC: 3113718. DOI: 10.1056/NEJMoa1010095. View

19.

Li X, Zhang S, Xu W, Xing B, Lu Q, Zhang P . Vascular endothelial injury in severe fever with thrombocytopenia syndrome caused by the novel bunyavirus. Virology. 2018; 520:11-20. DOI: 10.1016/j.virol.2018.05.001. View

20.

Gai Z, Zhang Y, Liang M, Jin C, Zhang S, Zhu C . Clinical progress and risk factors for death in severe fever with thrombocytopenia syndrome patients. J Infect Dis. 2012; 206(7):1095-102. DOI: 10.1093/infdis/jis472. View