Foshan Hospital of Traditional Chinese Medicine, Foshan, China.
Department of Critical Care Medicine, The First Affiliated Hospital of GuangZhou University of Chinese Medicine, Guangzhou, China.
BMC Infect Dis. 2022 Jul 30;22(1):662. doi: 10.1186/s12879-022-07650-6.
We aimed to explore the prognostic utilities of C-reactive protein (CRP), procalcitonin (PCT), neutrophil CD64 (nCD64) index, in combination or alone, in septic patients.
We retrospectively included 349 septic patients (based on Sepsis 3.0 definition). The primary outcome was 28-day all-cause mortality. Cox regression model, receiver-operating characteristic (ROC) curve, reclassification analysis, Kaplan-Meier survival curves were performed to evaluate the predictive efficacy of the above parameters.
CRP, nCD64 index were independent predictors of 28-day mortality for sepsis in the Cox regression model [CRP, HR 1.004 (95% CI 1.002-1.006), P < 0.001; nCD64 index, HR 1.263 (95% CI 1.187-1.345, P < 0.001]. Area under the ROC curve (AUC) of CRP, PCT, nCD64 index, nCD64 index plus PCT, nCD64 index plus CRP, were 0.798 (95% CI 0.752-0.839), 0.833 (95% CI 0.790-0.871), 0.906 (95% CI 0.870-0.935), 0.910 (95% CI 0.875-0.938), 0.916 (95% CI 0.881-0.943), respectively. nCD64 plus CRP performed best in prediction, discrimination, and reclassification of the 28-day mortality risk in sepsis. The risk of 28-day mortality increased stepwise as the number of data exceeding optimal cut-off values increased.
nCD64 index combined with CRP was superior to CRP, PCT, nCD64 index and nCD64 index plus PCT in predicting 28-day mortality in sepsis. Multi-marker approach could improve the predictive accuracy and be beneficial for septic patients.
本研究旨在探讨 C 反应蛋白(CRP)、降钙素原(PCT)、中性粒细胞 CD64(nCD64)指数单独及联合检测对脓毒症患者预后的预测价值。
回顾性纳入 2018 年 1 月至 2020 年 12 月间 349 例脓毒症患者(根据 Sepsis 3.0 定义)。主要终点为 28 天全因死亡率。采用 Cox 回归模型、受试者工作特征(ROC)曲线、再分类分析、Kaplan-Meier 生存曲线评估上述参数的预测效能。
在 Cox 回归模型中,CRP、nCD64 指数是 28 天死亡率的独立预测因素[CRP,HR 1.004(95%CI 1.002-1.006),P<0.001;nCD64 指数,HR 1.263(95%CI 1.187-1.345,P<0.001]。CRP、PCT、nCD64 指数、nCD64 指数+PCT、nCD64 指数+CRP 的 ROC 曲线下面积(AUC)分别为 0.798(95%CI 0.752-0.839)、0.833(95%CI 0.790-0.871)、0.906(95%CI 0.870-0.935)、0.910(95%CI 0.875-0.938)、0.916(95%CI 0.881-0.943)。nCD64+CRP 在预测、鉴别和重新分类脓毒症 28 天死亡率风险方面表现最佳。随着超过最佳截断值的数据数量的增加,28 天死亡率的风险呈阶梯式增加。
nCD64 指数联合 CRP 预测脓毒症 28 天死亡率优于 CRP、PCT、nCD64 指数和 nCD64 指数+PCT。多标志物方法可提高预测准确性,有利于脓毒症患者。