Shen Yingchun, Li Gang
Pediatric Emergency and PICU, Northwest Women and Children's Hospital, Xi'an, 710061, China.
BMC Pediatr. 2025 Aug 25;25(1):649. doi: 10.1186/s12887-025-06017-5.
This study explores the potential of various biomarkers to facilitate the differential diagnosis of late-onset sepsis (LOS) from non-LOS infections in hospitalized pediatric patients.
We conducted a retrospective cohort study using electronic medical records from our hospital from January 2022 to December 2023, and divided the patients into LOS (n = 178) and non-LOS (n = 159) groups. Data collected included demographic information, levels of inflammatory and metabolic biomarkers. Descriptive statistics were used for demographic data, and multivariable logistic regression followed by ROC curve analysis was used to assess the diagnostic value of these biomarkers.
Significant differences were observed in the levels of PCT, CRP, Lac, HBP, TNF-α, IL-6, IL-1β, IL-10, and IL-12 between the LOS and non-LOS groups (all p < 0.001). Multivariate logistic regression identified PCT, CRP, IL-6, IL-1β, IL-12, and Lac as independent predictors of LOS. ROC curve analysis showed high diagnostic values for PCT, Lac, and IL-1β. A combined diagnostic model of CRP, Lac, and IL-1β achieved the highest performance with an AUC of 0.958, sensitivity of 97.8%, and specificity of 91.8%. Additionally, Gram-negative LOS was associated with higher levels of PCT, CRP, and IL-6 compared to Gram-positive LOS. PCT levels demonstrated moderate diagnostic performance in differentiating LOS caused by Gram-positive vs. Gram-negative bacteria (AUC = 0.626).
The combination of CRP, Lac, and IL-1β serves as a robust set of biomarkers for the differential diagnosis of LOS in pediatric ICU settings. Furthermore, PCT also serves as a critical biomarker for differentiating between Gram-negative and Gram-positive bacterial causes, aiding in more targeted clinical management.
本研究探讨多种生物标志物在促进住院儿科患者迟发性脓毒症(LOS)与非LOS感染鉴别诊断方面的潜力。
我们利用我院2022年1月至2023年12月的电子病历进行了一项回顾性队列研究,将患者分为LOS组(n = 178)和非LOS组(n = 159)。收集的数据包括人口统计学信息、炎症和代谢生物标志物水平。人口统计学数据采用描述性统计,多变量逻辑回归及随后的ROC曲线分析用于评估这些生物标志物的诊断价值。
LOS组和非LOS组之间在降钙素原(PCT)、C反应蛋白(CRP)、乳酸(Lac)、肝素结合蛋白(HBP)、肿瘤坏死因子-α(TNF-α)、白细胞介素-6(IL-6)、白细胞介素-1β(IL-1β)、白细胞介素-10(IL-10)和白细胞介素-12(IL-12)水平上观察到显著差异(所有p < 0.001)。多变量逻辑回归确定PCT、CRP、IL-6、IL-1β、IL-12和Lac为LOS的独立预测因子。ROC曲线分析显示PCT、Lac和IL-1β具有较高的诊断价值。CRP、Lac和IL-1β的联合诊断模型性能最佳,曲线下面积(AUC)为0.958,灵敏度为97.8% , 特异性为91.8%。此外,与革兰氏阳性LOS相比,革兰氏阴性LOS的PCT、CRP和IL-6水平更高。PCT水平在区分革兰氏阳性与革兰氏阴性细菌引起的LOS方面表现出中等诊断性能(AUC = 0.626)。
CRP、Lac和IL-1β的组合是儿科重症监护病房环境中LOS鉴别诊断有力的生物标志物组。此外,PCT也是区分革兰氏阴性和革兰氏阳性细菌病因的关键生物标志物,有助于更有针对性的临床管理。