Retrospective Analysis of Severe Fever With Thrombocytopenia Syndrome and Construction of a Nomogram Prediction Model for Mortality Risk Factors.

IF 3.8 4区医学 Q2 IMMUNOLOGY

Open Forum Infectious Diseases Pub Date : 2025-06-02 eCollection Date: 2025-07-01 DOI:10.1093/ofid/ofaf318

Gang Chen, Yuchen Du, Xiuchang Ma, Yaowen Liang, Apeng Chen, Jie Wei, Jinhuan Wu, Wenxian Qian, Shuqin Xie, Yi Yan, Zheng Hu, Yishan Zheng, Man Tian, Changhua Yi

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引用次数: 0

Abstract

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging zoonotic infectious disease caused by the SFTS virus and is characterized by a high mortality rate. The primary objective of this study was to investigate high-mortality risk factors in SFTS and to create a nomogram model for personalized prediction.

Methods: A total of 523 patients with SFTS who were admitted to the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, between January 2020 and December 2023 were retrospectively analyzed: 75 cases were classified in the death group and 448 cases in the survival group. Development of a predictive nomogram model was based on the independent risk factors that were stepwise screened through univariate analysis, LASSO analysis (least absolute shrinkage and selection operator), and multivariate logistic regression analysis.

Results: Based on stepwise variable screening by univariate analysis, LASSO analysis, and multivariate logistic regression, the following were independent mortality risk factors in patients with SFTS: age (odds ratio [OR], 1.06; 95% CI, 1.03-1.10; P < .001), hemorrhagic symptoms (OR, 3.39; 95% CI, 1.31-8.78; P = .012), neurologic symptoms (OR, 4.89; 95% CI, 2.72-8.77; P < .001), platelet count (OR, 0.99; 95% CI, .98-.99; P = .045), prothrombin time (OR, 1.32; 95% CI, 1.11-1.56; P = .001), activated partial thromboplastin time (OR, 1.02; 95% CI, 1.01-1.03; P = .007), and viral load ≥10⁷copies/mL (OR, 2.66; 95% CI, 1.36-5.20; P = .004). The area under the curve (0.87; 95% CI, .832-.909) showed excellent predictive power. Calibration curves showed the accuracy of the assessed nomograms. Decision curve analysis results showed a greater net benefit when the threshold probability of patient death was between 0.02 and 0.75.

Conclusions: A nomogram model consisting of 7 risk factors was successfully constructed, which can be used to predict SFTS mortality risk factors early.

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发热伴血小板减少综合征的回顾性分析及死亡危险因素Nomogram预测模型的建立。

背景：发热伴血小板减少综合征（SFTS）是由SFTS病毒引起的一种新出现的人畜共患传染病，其特点是死亡率高。本研究的主要目的是调查SFTS的高死亡率危险因素，并建立一个个性化预测的nomogram模型。方法：回顾性分析南京中医药大学附属南京第二医院2020年1月至2023年12月收治的SFTS患者523例，其中死亡组75例，生存组448例。通过单因素分析、LASSO分析（最小绝对收缩和选择算子）和多因素logistic回归分析逐步筛选独立风险因素，建立预测nomogram模型。结果：通过单因素分析、LASSO分析和多因素logistic回归逐步筛选，SFTS患者的独立死亡危险因素为：年龄(优势比[OR]， 1.06；95% ci, 1.03-1.10；P < 0.001)，出血性症状(OR, 3.39；95% ci, 1.31-8.78；P = 0.012)，神经症状(OR, 4.89；95% ci, 2.72-8.77；P < 0.001)，血小板计数(OR, 0.99；95% ci, 0.98 - 0.99；P = 0.045)，凝血酶原时间(OR, 1.32；95% ci, 1.11-1.56；P = .001)，激活部分凝血活素时间(OR, 1.02；95% ci, 1.01-1.03；P = .007)，病毒载量≥107拷贝/mL (OR, 2.66；95% ci, 1.36-5.20；P = .004)。曲线下面积(0.87；95% CI（0.832 - 0.909）显示了极好的预测能力。校准曲线显示了所评估的图的准确性。决策曲线分析结果显示，当患者死亡的阈值概率在0.02 ~ 0.75之间时，净收益更大。结论：成功构建了由7个危险因素组成的nomogram模型，可用于早期预测SFTS死亡危险因素。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Open Forum Infectious Diseases Medicine-Neurology (clinical)

CiteScore

6.70

自引率

4.80%

发文量

630

审稿时长

9 weeks

期刊介绍： Open Forum Infectious Diseases provides a global forum for the publication of clinical, translational, and basic research findings in a fully open access, online journal environment. The journal reflects the broad diversity of the field of infectious diseases, and focuses on the intersection of biomedical science and clinical practice, with a particular emphasis on knowledge that holds the potential to improve patient care in populations around the world. Fully peer-reviewed, OFID supports the international community of infectious diseases experts by providing a venue for articles that further the understanding of all aspects of infectious diseases.