Zhang Sheng, Zhang Xian, Yu Wenbo, Lin Zhaofen, Chen Dechang
Department of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Emergency Medicine, Changzheng Hospital, Naval Medical University (Second Military Medical University), Shanghai, China.
Ann Transl Med. 2020 Dec;8(23):1581. doi: 10.21037/atm-20-3425.
This study aimed to evaluate whether inexpensive and quickly available infection biomarkers including procalcitonin (PCT), C-reactive protein (CRP), white blood cell (WBC) count, and percentage of neutrophils (N%) are helpful in assisting the judgement of blood culture results and patient prognosis.
This retrospective study included patients who were admitted to the intensive care unit (ICU) of Changzheng Hospital from July 2015 to June 2017 and had at least one episode of blood culture with matched infection biomarkers (PCT, CRP, WBC, and N%). Primary infection biomarkers were transformed into newly derived components using the principal component analysis (PCA) method. Each observation was plotted as a point on the component map using factor scores as coordinates. The distribution characteristics of patients with different blood culture results and prognosis were explored. The diagnostic performance of the components and infection biomarkers in the discrimination of blood culture results and patient prognosis were compared using receiver operating characteristic (ROC) curves.
A total of 768 episodes of blood cultures from 436 patients were analyzed. Patients with positive blood cultures were associated with higher ICU mortality, in-hospital mortality, longer ICU stay and hospital stay (P<0.001 for all). In PCA, the 4 sets of primary infection biomarkers (PCT, CRP, WBC, and N%) were transformed into components 1 and 2. On the component map, observations of positive blood cultures were more likely to be distributed in the first and second quadrants than those of negative blood cultures (OR, 6.28, 95% CI, 4.14-9.64, P<0.001). Compared to patients with negative blood cultures, non-survivors with positive blood cultures were more likely to be distributed in the first and second quadrants (OR, 6.90, 95% CI, 2.67-20.98, P<0.001), followed by survivors with positive blood cultures (OR, 3.44, 95% CI, 1.97-6.13, P<0.001). PCT- and CRP-derived component had the largest area under curves (AUCs) in the discrimination of blood culture results (0.81) and patient prognosis (0.69).
PCT- and CRP-derived component was more strongly associated with blood culture results and patient prognosis than WBC- and N%-derived component and primary biomarkers.
本研究旨在评估降钙素原(PCT)、C反应蛋白(CRP)、白细胞(WBC)计数及中性粒细胞百分比(N%)等价格低廉且可快速获取的感染生物标志物是否有助于辅助判断血培养结果及患者预后。
本回顾性研究纳入了2015年7月至2017年6月入住长征医院重症监护病房(ICU)且至少有一次血培养及匹配感染生物标志物(PCT、CRP、WBC和N%)的患者。采用主成分分析(PCA)方法将主要感染生物标志物转化为新的衍生成分。以因子得分作为坐标,将每个观察值绘制在成分图上的一个点上。探索不同血培养结果及预后患者的分布特征。使用受试者工作特征(ROC)曲线比较成分和感染生物标志物在鉴别血培养结果及患者预后方面的诊断性能。
共分析了436例患者的768次血培养。血培养阳性患者的ICU死亡率、住院死亡率、ICU住院时间和住院时间均较高(所有P<0.001)。在PCA中,4组主要感染生物标志物(PCT、CRP、WBC和N%)转化为成分1和成分2。在成分图上,血培养阳性的观察值比血培养阴性的观察值更有可能分布在第一和第二象限(比值比,6.28,95%可信区间,4.14 - 9.64,P<0.001)。与血培养阴性患者相比,血培养阳性的非幸存者更有可能分布在第一和第二象限(比值比,6.90,95%可信区间,2.67 - 20.98,P<0.001),其次是血培养阳性的幸存者(比值比,3.44,95%可信区间,1.97 - 6.13,P<0.001)。源自PCT和CRP的成分在鉴别血培养结果(曲线下面积[AUC]为0.81)和患者预后(AUC为0.69)方面具有最大的曲线下面积。
与源自WBC和N%的成分及主要生物标志物相比,源自PCT和CRP的成分与血培养结果及患者预后的关联更强。