降钙素原和血小板计数在血流感染中的临床意义-现代医学

降钙素原和血小板计数在血流感染中的临床意义

单位：广州军区广州总医院, 广东广州 510010

分类号：R515.3

出版年·卷·期（页码）：2018·46·第三期（305-309）

摘要：

目的：检测血浆降钙素原（PCT）、C反应蛋白（CRP）、白细胞（WBC）、中性粒细胞（NEU）、中性粒细胞比值（Neut%）、血小板（PLT）计数在不同病原菌感染时的水平，探讨这些炎症指标在血流感染中的临床价值。方法：回顾性分析2012年1月至2015年12月入住MICU血培养阳性患者178例，根据血培养结果分为革兰阴性菌组（G-组，101例）和革兰阳性菌组（G+组，77例），比较两组患者6种炎症指标的差异，同时根据多因素Logistic回归分析和受试者工作特征（receiver operating characteristic，ROC）曲线下面积评价差异指标的鉴别诊断性能。再根据预后将血流感染患者分为生存组（79例）和死亡组（99例），对其预后的影响因素进行单因素分析和多因素逻辑回归分析（Logistic回归分析）。结果：G-组PCT、Neut%水平明显高于G+组，PLT水平明显低于G+组（P<0.01），而CRP、WBC和NEU在两组间差异无统计学意义；进一步的多因素回归分析显示：革兰阴性菌血流感染与PCT、PLT水平相关（P<0.05），ROC曲线分析显示：PCT、PLT、Neut%区分革兰阴性菌和革兰阳性菌ROC曲线下面积分别为0.76、0.68、0.64，最佳截断值分别为1.22 ng·ml^-1、121×10⁹ L^-1、87.8%。生存组PCT、CRP水平明显低于死亡组，PLT水平明显高于死亡组（P<0.05）；WBC、NEU和Neut%在两组间差异无统计学意义。Logistic回归模型分析显示，急性生理与慢性健康评分（APACHE Ⅱ评分）与PLT计数是血流感染患者死亡的独立危险因素。结论：6种感染指标中同时检测PCT、PLT和Neut%有利于鉴别革兰阴性菌和革兰阳性菌血流感染，而APACHE Ⅱ评分和PLT可作为血流感染患者死亡的独立危险因素。

Objective: To investigate the expression of procalcitonin(PCT), C-reactive protein(CRP), white blood cell (WBC), neutrophil(NEU), neutrophil ratio(Neut%) and platelet(PLT) count in bloodstream infection with different bacterium, and assess the clinical value of these inflammatory cytokines in bloodstream infection.Methods: 178 positive patients with blood culture enrolled in Medical Intensive Care Unit(MICU) from January 2012 to December 2015 were analyzed retrospectively. The patients were divided into G-group (n=101) and G+group(n=77) according to the result of blood culture. The six inflammatory markers were compared between the two groups. In addition, the patients were divided into survival group (n=79) and non-survival group (n=99). Simple factor analysis and multivariate Logistic regression analysis were performed to assess the possible influence factors of prognosis. Results: The levels of PCT and Neut% in the G-group were significantly higher than those in the G+ group, while the level of PLT in the G+ group was significantly higher than that in the G-group. The expressions of CRP, WBC and NEU between the two groups had no significant differences. Multivariate regression analysis revealed that PCT and PLT were the relevant influence factors of G-bacterial bloodstream infection. The ROC curves showed that the area under ROC curve (AUC) of PCT,PLT and Neut% for distin guishing G-and G+ bacterial were 0.76,0.68,0.64 and the best cut-off value were 1.22 ng·ml^-1, 121×10⁹L^-1, 87.8%, respectively. The levels of PCT and CRP in the survival group were significantly lower than those in the non-survival group, while PLT showed conversely. There were no significant differences in WBC, NEU and Neut% between survival group and non-survival group. Multivariate regression analysis revealed that APACHE Ⅱscore and platelet count were the independent risk factors for the prognosis of the bloodstream infection patients.Conclusion: Among the six inflammation cytokines, the combination of PCT, PLT and Neut% can effectively diagnose G-and G+ bacterial bloodstream infections. APACHE Ⅱscore and platelet count are the independent risk factors of prognosis of bloodstream infection.

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