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严重发热伴血小板减少综合征的致死危险因素及糖皮质激素治疗的疗效:一项多中心回顾性队列研究

Fatal risk factors and the efficacy of glucocorticoid therapy in severe fever with thrombocytopenia syndrome: a multicenter retrospective cohort study.

作者信息

Zhong Fang, Zhang Shiyu, Zheng Chengxi, Zhayier Dilihumaer, Liu Shuting, You Qinyu, Huang Hongming, Zhu Bin, Tian Jin, Hu Zhiliang, Zheng Xin, Wang Baoju, Peng Zhihang

机构信息

School of Public Health, Nanjing Medical University, Nanjing, China.

Department of Infectious Disease, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Front Cell Infect Microbiol. 2025 May 8;15:1531880. doi: 10.3389/fcimb.2025.1531880. eCollection 2025.

DOI:10.3389/fcimb.2025.1531880
PMID:40406526
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12095230/
Abstract

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease characterized by rapid progression and high mortality. Glucocorticoids (GCs) can be used as anti-inflammatory agents for SFTS, but no standardized protocols have been proposed.

METHODS

A total of 901 patients with SFTS diagnosed at two hospitals between July 2017 and October 2023 were included in this retrospective cohort study. Univariate and multivariate logistic regression were performed along with LASSO regression to identify independent risk factors of fatal outcomes and further develop mortality prediction model. A nomogram was used to visualize the predictive model. ROC curves, calibration curves, and DCA curves were conducted to assess model accuracy and clinical applicability. The efficacy of GC was assessed using survival analyses, and further subgroup analyses of the effects of different GC regimens on fatal outcomes and hospital-acquired infections (HAI) were performed. Propensity score matching (PSM) analyses were conducted to control confounding factors.

RESULTS

Older age (age > 69 years), consciousness disturbance, decreased monocyte counts, prolonged activated partial thromboplastin time (APTT), and high viral load were identified as strong predictors of fatal outcomes in patients with SFTS. Patients were classified into mild and severe groups according to risk scores calculated by the nomogram (cut-off value = 121.43). Survival analyses showed that GCs treatment may reduce the mortality in severe patients (p = 0.004). Further subgroup analyses indicated that relatively high doses and early treatment with GCs may increase mortality in SFTS patients [OR = 2.292 (1.071, 5.066); OR = 3.693 (1.710, 8.345) respectively]. GCs treatment was associated with an elevated risk of HAI in patients both with mild and severe SFTS (p = 0.024; p = 0.015, respectively). Initiation of GCs therapy at a low level of aspartate aminotransferase (AST < 189.75 U/L) reduced the mortality before and after PSM (p<0.001; p = 0.004, respectively).

CONCLUSIONS

A new nomogram based on five independent risk factors effectively predicts the prognosis of SFTS. Severe patients and those with low AST levels might benefit from GCs therapy while early and relatively high doses of GCs therapy should be used with caution.

摘要

背景

发热伴血小板减少综合征(SFTS)是一种新出现的蜱传传染病,其特点是进展迅速且死亡率高。糖皮质激素(GCs)可作为SFTS的抗炎药物,但尚未提出标准化方案。

方法

本回顾性队列研究纳入了2017年7月至2023年10月期间在两家医院诊断为SFTS的901例患者。进行单因素和多因素逻辑回归以及LASSO回归,以确定死亡结局的独立危险因素,并进一步建立死亡率预测模型。使用列线图来可视化预测模型。绘制受试者工作特征曲线(ROC曲线)、校准曲线和决策曲线分析(DCA曲线)以评估模型准确性和临床适用性。使用生存分析评估GCs的疗效,并对不同GCs方案对死亡结局和医院获得性感染(HAI)的影响进行进一步亚组分析。进行倾向评分匹配(PSM)分析以控制混杂因素。

结果

年龄较大(年龄>69岁)、意识障碍、单核细胞计数降低、活化部分凝血活酶时间(APTT)延长和病毒载量高被确定为SFTS患者死亡结局的强预测因素。根据列线图计算的风险评分(临界值 = 121.43)将患者分为轻度和重度组。生存分析表明,GCs治疗可能降低重症患者的死亡率(p = 0.004)。进一步亚组分析表明,相对高剂量和早期使用GCs可能增加SFTS患者的死亡率[OR分别为2.292(1.071,5.066);OR为3.693(1.710,8.345)]。GCs治疗与轻度和重度SFTS患者发生HAI的风险升高相关(分别为p = 0.024;p = 0.015)。在天冬氨酸转氨酶水平较低(AST < 189.75 U/L)时开始GCs治疗可降低PSM前后的死亡率(分别为p<0.001;p = 0.004)。

结论

基于五个独立危险因素的新列线图可有效预测SFTS的预后。重症患者和AST水平较低的患者可能从GCs治疗中获益,而早期和相对高剂量的GCs治疗应谨慎使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/214df7ce1277/fcimb-15-1531880-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/66ee23c43605/fcimb-15-1531880-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/4717dbbbc03e/fcimb-15-1531880-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/474bab43c40a/fcimb-15-1531880-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/91445f82e910/fcimb-15-1531880-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/214df7ce1277/fcimb-15-1531880-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/66ee23c43605/fcimb-15-1531880-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/4717dbbbc03e/fcimb-15-1531880-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/474bab43c40a/fcimb-15-1531880-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/91445f82e910/fcimb-15-1531880-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8f8/12095230/214df7ce1277/fcimb-15-1531880-g005.jpg

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