GUO Ji, LYU Yong. Clinical value of novel bunyavirus load combined with platelet count and thrombin time on prognosis of fever patients complicating with thrombocytopenia syndrome[J]. Journal of Clinical Medicine in Practice, 2024, 28(15): 9-13. DOI: 10.7619/jcmp.20240907
Citation: GUO Ji, LYU Yong. Clinical value of novel bunyavirus load combined with platelet count and thrombin time on prognosis of fever patients complicating with thrombocytopenia syndrome[J]. Journal of Clinical Medicine in Practice, 2024, 28(15): 9-13. DOI: 10.7619/jcmp.20240907

Clinical value of novel bunyavirus load combined with platelet count and thrombin time on prognosis of fever patients complicating with thrombocytopenia syndrome

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  • Received Date: March 04, 2024
  • Revised Date: June 06, 2024
  • Objective 

    To investigate the clinical significance of severe fever with thrombocytopenia syndrome virus (SFTSV) load combined with platelet count (PLT) and thrombin time (TT) in predicting the prognosis of fever patients with thrombocytopenia syndrome (SFTS).

    Methods 

    A total of 100 patients with SFTS were selected and divided into survival group (n=77) and death group (n=23) based on their prognosis. Clinical general information, symptoms, PLT, coagulation indexes, and SFTSV load were compared between the survival and death groups, and their impacts on prognosis of patients were analyzed.

    Results 

    The duration of fever in the death group was longer than that in the survival group (P < 0.05). The proportion of patients with gastrointestinal bleeding, altered mental status, renal impairment, cardiac impairment, and disseminated intravascular coagulation (DIC) was higher in the death group than in the survival group (P < 0.05). PLT was lower in the death group than in the survival group, while TT and activated partial thromboplastin time (APTT) were longer in the death group(P < 0.05). The proportion of patients with logarithm of copy number for SFTSV load ≥5 was higher in the death group than in the survival group (P < 0.05). Logistic regression analysis showed that gastrointestinal bleeding, renal impairment, cardiac impairment, DIC, PLT, TT, and SFTSV load were factors influencing patients' mortality (P < 0.05). The area under the receiver operating characteristic (ROC) curve of the equation predicting patients'mortality was 0.919 (95%CI, 0.860 to 0.977), with sensitivity and specificity of 95.70% and 81.80%, respectively.

    Conclusion 

    The prognosis of SFTS patients is influenced by factors such asgastrointestinal bleeding, renal impairment, cardiac impairment, DIC, PLT, TT, and virus load. The equation constructed based on these influencing factors has certain value in predicting patients' prognosis.

  • [1]
    杨鑫, 武永祥, 冷昱, 等. 两起发热伴血小板减少综合征聚集性疫情流行病学及病原学分析[J]. 遗传, 2023, 45(11): 1062-1073. https://www.cnki.com.cn/Article/CJFDTOTAL-YCZZ202311012.htm
    [2]
    王晗, 赵立凡, 孙刚, 等. 2012—2021年常州市发热伴血小板减少综合征流行特征及聚集性疫情分析[J]. 寄生虫与医学昆虫学报, 2023, 30(1): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-JSCY202301001.htm
    [3]
    霍雪平, 刘贞君, 谢琴秀. 重症发热伴血小板减少综合征预警指标分析[J]. 新发传染病电子杂志, 2023, 8(5): 41-45. https://www.cnki.com.cn/Article/CJFDTOTAL-XFCR202305008.htm
    [4]
    OTSUKA Y, SHIRAKABE A, ASAYAMA T, et al. Successful treatment of thrombocytopenia, anasarca, fever, reticulin myelofibrosis/renal insufficiency, and organomegaly syndrome using plasma exchange followed by rituximab in the intensive care unit[J]. J Med Cases, 2021, 12(12): 474-480. doi: 10.14740/jmc3784
    [5]
    SUZUKI T, SATO Y, SANO K, et al. Severe fever with thrombocytopenia syndrome virus targets B cells in lethal human infections[J]. J Clin Investig, 2020, 130(2): 799-812. doi: 10.1172/JCI129171
    [6]
    RYU S, CHOI J K, ACHANGWA C, et al. Temporal dynamics of serum perforin and granzymes in three different clinical stages of virus-induced severe fever with thrombocytopenia syndrome[J]. Am J Trop Med Hyg, 2023, 109(3): 554-558. doi: 10.4269/ajtmh.23-0269
    [7]
    中华人民共和国卫生部. 发热伴血小板减少综合征防治指南(2010版)[J]. 中华临床感染病杂志, 2011, 4(4): 193-194. https://www.cnki.com.cn/Article/CJFDTOTAL-ZYSW201006008.htm
    [8]
    黄晓霞, 杜珊珊, 李阿茜, 等. 2018—2021年中国发热伴血小板减少综合征流行特征分析[J]. 中华流行病学杂志, 2024, 45(1): 112-116. https://www.cnki.com.cn/Article/CJFDTOTAL-JSCY202301001.htm
    [9]
    WILLIAMS H M, THORKELSSON S R, VOGEL D, et al. Structural insights into viral genome replication by the severe fever with thrombocytopenia syndrome virus L protein[J]. Nucleic Acids Res, 2023, 51(3): 1424-1442. doi: 10.1093/nar/gkac1249
    [10]
    KIM C M, KIM D M, YUN N R. Clinical usefulness of nested reverse-transcription polymerase chain reaction for the diagnosis of severe fever with thrombocytopenia syndrome[J]. Am J Trop Med Hyg, 2021, 105(4): 999-1003. doi: 10.4269/ajtmh.21-0183
    [11]
    YUN M R, RYOU J, CHOI W, et al. Genetic diversity and evolutionary history of Korean isolates of severe fever with thrombocytopenia syndrome virus from 2013-2016[J]. Arch Virol, 2020, 165(11): 2599-2603. doi: 10.1007/s00705-020-04733-0
    [12]
    周诗君, 夏国美, 贺腾飞, 等. 新型布尼亚病毒感染患者临床特征及其预后因素分析[J]. 安徽医科大学学报, 2021, 56(6): 942-947. https://www.cnki.com.cn/Article/CJFDTOTAL-YIKE202106020.htm
    [13]
    周麟玲, 贾荣娟, 董崇林, 等. 高新型布尼亚病毒载量发热伴血小板减少综合征患者141例的临床特征及预后影响因素分析[J]. 中华传染病杂志, 2020, 38(9): 578-583.
    [14]
    朱立雨, 张春, 张炜, 等. 重症新型布尼亚病毒感染的临床特征及死亡危险因素探讨[J]. 中国临床医生杂志, 2022, 50(10): 1172-1175. https://www.cnki.com.cn/Article/CJFDTOTAL-ZLYS202210011.htm
    [15]
    马于琪, 梁明明, 尹华发. 新型布尼亚病毒感染的临床特征及预后影响因素分析[J]. 实用医学杂志, 2020, 36(23): 3231-3236. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYZ202023013.htm
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