机构地区:[1]江南大学附属医院急诊科,无锡214000 [2]江南大学医学院临床医学,无锡214000
出 处:《中国医师进修杂志》2025年第3期256-262,共7页Chinese Journal of Postgraduates of Medicine
摘 要:目的基于决策曲线探讨血小板聚集功能对脓毒症患者并发急性肾损伤(AKI)的预测价值。方法采用回顾性研究的方法,收集并分析2021年1月至2023年12月江南大学附属医院收治的120例脓毒症患者的临床资料,根据住院期间AKI发生情况分为发生AKI组(37例)与未发生AKI组(83例)。收集并比较两组一般资料、血小板聚集功能指标(血小板聚集率)及其他实验室指标。采用Logistic回归模型分析脓毒症患者并发AKI与血小板聚集功能及主要指标的关系。绘制受试者工作特征(ROC)曲线得到曲线下面积(AUC),分析血小板聚集功能对脓毒症患者并发AKI的预测价值。利用R语言软件构建血小板聚集功能联合其他主要指标预测脓毒症患者并发AKI的列线图模型,基于决策曲线,分析模型对脓毒症患者并发AKI的预测效能。结果发生AKI组血小板聚集率低于未发生AKI组[(56.23±7.86)%比(68.79±8.54)%],凝血酶时间长于未发生AKI组[17.00(16.50,18.00)s比16.00(15.00,17.00)s],D-二聚体、C反应蛋白、降钙素原水平高于未发生AKI组[(1.55±0.45)mg/L比(1.32±0.41)mg/L、(107.53±18.41)mg/L比(99.86±17.25)mg/L、(3.10±0.46)μg/L比(2.88±0.42)μg/L],差异有统计学意义(P<0.05)。Logistic回归分析结果显示,脓毒症患者并发AKI可能与血小板聚集率、凝血酶时间、C反应蛋白及降钙素原水平异常有关(P<0.05)。绘制ROC曲线得到对应AUC:血小板聚集率预测脓毒症并发AKI的AUC为0.860(95%CI 0.789~0.931),有一定预测价值,当血小板聚集率取62.84%时,可获得最佳预测价值,其灵敏度、特异度、约登指数分别为83.80%、80.70%、0.645。血小板聚集功能辅助其他主要指标预测脓毒症患者并发AKI的列线图模型一致性指数为0.904(95%CI 0.851~0.957),提示模型辨别度良好;通过决策曲线分析模型临床净受益情况,结果显示模型临床净受益较血小板聚集率及其他主要指标单独应用均较高,当风险阈值�Objective To explore the predictive value of platelet aggregation function for acute kidney injury(AKI)in sepsis patients based on decision curve.Methods A retrospective study was conducted to collect and analyze the clinical data of 120 sepsis patients admitted to the Affiliated Hospital of Jiangnan University from January 2021 to December 2023.According to the incidence of AKI during hospitalization,they were divided into AKI group(37 cases)and non-AKI group(83 cases).The general data,platelet aggregation function index(platelet aggregation rate)and other laboratory indexes of the two groups were collected and compared.Logistic regression model was used to analyze the relationship between AKI and main indexes of platelet aggregation function in patients with sepsis.The area under the curve(AUC)was obtained by drawing the receiver operating characteristic(ROC)curve,and the predictive value of platelet aggregation function on AKI in patients with sepsis was analyzed.R language software was used to construct a nomogram model of platelet aggregation function combined with other main indicators to predict AKI in patients with sepsis.Based on the decision curve,the predictive efficacy of the model on AKI in patients with sepsis was analyzed.Results The platelet aggregation rate in the AKI group was lower than that in the non-AKI group:(56.23±7.86)%vs.(68.79±8.54)%,and the thrombin time was longer than that in the non-AKI group:17.00(16.50,18.00)s vs.16.00(15.00,17.00)s.The levels of D-dimer,C-reactive protein and procalcitonin were higher than those in the non-AKI group:(1.55±0.45)mg/L vs.(1.32±0.41)mg/L,(107.53±18.41)mg/L vs.(99.86±17.25)mg/L,(3.10±0.46)μg/L vs.(2.88±0.42)μg/L,and the differences were statistically significant(P<0.05).The results of constructing a Logistic regression model showed that AKI in sepsis patients may be related to abnormal levels of platelet aggregation rate,thrombin time,C-reactive protein and procalcitonin(P<0.05).The ROC curve was drawn to obtain the corresponding AUC:the AUC
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