Department of Transfusion Medicine, Weihai Municipal Hospital, No. 70 of Heping Road, WeihaiShandong, 264200, China.
Sci Rep. 2024 May 9;14(1):10627. doi: 10.1038/s41598-024-60923-9.
Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by a novel Bunyavirus infection with low population immunity and high mortality rate. Lacking specific therapies, the treatment measures vary with the severity of the disease, therefore, a case control study involved 394 SFTS patients was taken to determine risk factors for mortality. Comparative clinical data from the first 24 h after admission was collected through the electronic medical record system. Independent risk factors for death of SFTS were identified through univariate and multivariate binary logistic regression analyses. The results of the logistic regression were visualized using a nomogram which was created by downloading RMS package in the R program. In our study, four independent mortality risk factors were identified: advanced age(mean 70.45 ± 7.76 years), MODS, elevated APTT, and D-dimer. The AUC of the nomogram was 0.873 (0.832, 0.915), and the model passes the calibration test namely Unreliability test with P = 0.958, showing that the model's predictive ability is excellent. The nomogram to determine the risk of death in SFTS efficiently provide a basis for clinical decision-making for treatment.
严重发热伴血小板减少综合征（SFTS）是一种由新型布尼亚病毒感染引起的急性传染病，人群免疫力低，死亡率高。由于缺乏特效治疗方法，治疗措施随疾病严重程度而异，因此对 394 例 SFTS 患者进行了病例对照研究，以确定死亡率的危险因素。通过电子病历系统收集入院后 24 小时内的比较临床数据。通过单因素和多因素二元逻辑回归分析确定 SFTS 死亡的独立危险因素。逻辑回归的结果使用通过 R 程序下载 RMS 包创建的列线图可视化。在我们的研究中，确定了四个独立的死亡风险因素：高龄（平均 70.45±7.76 岁）、MODS、APTT 升高和 D-二聚体。列线图的 AUC 为 0.873（0.832，0.915），模型通过校准测试，即不可靠性测试，P=0.958，表明模型的预测能力优异。该列线图可有效确定 SFTS 患者死亡风险，为临床治疗决策提供依据。
