摘要
目的早期评估发热伴血小板减少综合征患者(SFTS)入院时的病情危险程度,建立SFTS的风险预测模型及相关评分标准。方法回顾性收集安徽医科大学附属巢湖医院2020年6月-2022年6月91例SFTS患者临床资料,根据预后情况将其分为生存组与死亡组,比较两组入院时第一次血清学检验指标及相关生命体征参数,筛选与死亡相关的危险因素,采用二元Logistic回归分析建立风险预测模型,通过ROC曲线评估模型的拟合优度和预测准确度,最后根据模型中各危险因素权重系数构建死亡风险预测模型的评分标准。结果生存组与死亡组淋巴细胞计数(LYM)、肌酐(Cr)、年龄、中热、高热时间及热程比较,差异有统计学意义(P<0.05);两组其余血清学检验指标及相关生命体征参数比较,差异无统计学意义(P>0.05);最终将年龄、中热、高热时间纳入预测模型,回归方程:P=ea(1+ea),a=-13.427+1.083×高热(天)+0.514×中热(天)+年龄×0.180;风险预测模型的ROC曲线下面积为0.948,95%置信区间为0.891~1.000,模型的拟合优度和预测准确度均较好。结论年龄>60岁、中热、高热时间是SFTS患者入院后早期判断死亡的独立危险因素,依据模型指定的评分标准能够较好的预测患者在住院期间的死亡风险。
Objective To evaluate the risk of patients with severe fever with thrombocytopenia syndrome(SFTS)on admission,and to establish a risk prediction model and related scoring criteria for SFTS.Methods A total of 91 patients with SFTS in Chaohu Hospital of Anhui Medical University from June 2020 to June 2022 were retrospectively collected.According to the prognosis,they were divided into survival group and death group.The first serological test indexes and related vital signs parameters of the two groups at admission were compared,and the risk factors related to death were screened.The risk prediction model was established by binary logistic regression analysis.The goodness of fit and prediction accuracy of the model were evaluated by ROC curve.Finally,the scoring criteria of the death risk prediction model were constructed according to the weight coefficient of each risk factor in the model.Results There were significant differences in lymphocyte count(LYM),creatinine(Cr),age,moderate fever,high fever time and fever duration between the survival group and the death group(P<0.05).There was no significant difference in other serological test indexes and related vital signs between the two groups(P>0.05).Finally,age,moderate fever and high fever time were included in the prediction model,regression equation:P=ea(1+ea),a=-13.427+1.083×high fever(day)+0.514×moderate fever(day)+age×0.180;the area under the ROC curve of the risk prediction model was 0.948,and the 95% confidence interval was 0.891-1.000,the goodness of fit and prediction accuracy of the model were good.Conclusion Age>60 years old,moderate fever and high fever time are independent risk factors for early death of SFTS patients after admission.The scoring criteria specified by the model can better predict the risk of death during hospitalization.
作者
刘旗旗
张照如
LIU Qi-qi;ZHANG Zhao-ru(Department of Infectious Diseases,Chaohu Hospital of Anhui Medical University,Chaohu 238001,Anhui,China)
出处
《医学信息》
2023年第11期21-26,共6页
Journal of Medical Information
关键词
发热伴血小板减少综合征
血清学指标
死亡风险预测模型
Severe fever with thrombocytopenia syndrome
Serological indicators
Death risk prediction model
