首页> 外文期刊>Journal of clinical laboratory analysis. >Combined procalcitonin and hemogram parameters contribute to early differential diagnosis of Gram-negative/Gram-positive bloodstream infections
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Combined procalcitonin and hemogram parameters contribute to early differential diagnosis of Gram-negative/Gram-positive bloodstream infections

机译:综合的ProCalcitonin和六视参数有助于革兰氏阴性/革兰氏阳性血流感染的早期差异诊断

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Background Hemogram parameters and procalcitonin (PCT) play auxiliary roles in the diagnosis and outcome of sepsis. However, it is not clear whether these indicators can quickly distinguish bacterial classification or guide the choice of empirical antibiotics. Methods We retrospectively enrolled 381 patients with bloodstream infections (BSI), divided into Gram-positive bloodstream infections (GP-BSI) and Gram-negative bloodstream infections (GN-BSI). Demographic parameters, hemogram parameters, and PCT were recorded and compared between the two groups. Results The mean platelet volume (MPV), platelet distribution width (PDW), and PCT in the GN-BSI group were significantly higher than those in the GP-BSI group, while the platelet count (PLT), plateletcrit, platelet count-to-white blood cell count ratio (PWR), platelet count-to-neutrophil count ratio (PNR), platelet count-to-PCT ratio (PLT/PCT), and mean platelet volume-to-PCT ratio (MPV/PCT) were significantly lower in the GN-BSI group. Multivariate stepwise logistic regression analysis revealed that the independent predictors of GN-BSI were MPV, PWR, and PCT. The areas under the curve (AUC) for this prediction model was 0.79, with sensitivity =0.75 and specificity =0.71. Conclusions There were significant differences in terms of PCT, platelet parameters, and platelet-related index-PCT ratio between GN-BSI and GP-BSI. Combined PCT and hemogram parameters are more conducive to the early differential diagnosis of bacterial classification of BSI.
机译:背景技术六肢图参数和procalcitonin(PCT)在败血症的诊断和结果中发挥辅助作用。但是,目前尚不清楚这些指标是否可以快速区分细菌分类或指导经验抗生素的选择。方法我们回顾性地注册了381名血流感染患者(BSI),分为革兰氏阳性血流感染(GP-BSI)和革兰氏阴性血流感染(GN-BSI)。记录人口统计参数,血页参数和PCT,并在两组之间进行比较。结果GN-BSI组中的平均血小板体积(MPV),血小板分布宽度(PDW)和PCT显着高于GP-BSI组中的PCT,而血小板计数(PLT),血小板,血小板计数 - 当血细胞计数比(PWR),血小板计数到中性粒细胞计数比(PNR),血小板计数到PCT比(PLT / PCT),以及平均血小板体积 - PCT比(MPV / PCT)是GN-BSI组显着降低。多变量逐步逻辑回归分析显示,GN-BSI的独立预测因子是MPV,PWR和PCT。该预测模型的曲线(AUC)下的区域为0.79,灵敏度= 0.75,特异性= 0.71。结论GN-BSI和GP-BSI之间的PCT,血小板参数和血小板相关指数-PCT比具有显着差异。组合的PCT和血液图参数更有利于BSI细菌分类的早期差异诊断。

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