Wang Haonan, Li Jiaqing, Li Xian, Li Han, He Yinglang, Tan Rui, Mei Xuejian, Zha Haoyu, Fan Mingxing, Peng Shuangshuang, Hou Nan, Li Zhe, Wang Yue, Ji Chen, Liu Yao, Miao Hongjun
Department of Emergency and Pediatric Intensive Care Unit, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Department of Anesthesiology, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Front Pediatr. 2024 Nov 25;12:1433417. doi: 10.3389/fped.2024.1433417. eCollection 2024.
To investigate the epidemiological characteristics of Augmented Renal Clearance (ARC) in severe sepsis children with MRSA infection and find risk factors to establish a model predicting ARC onset in PICU.
Retrospective study, in which ARC was defined by estimated glomerular filtration rate (eGFR) measured by the modified Schwartz formula above 130 ml/min/1.73 m. Univariable and multivariable logistic regression analyses were performed to find the predictor for ARC. Multi-strategy modeling was used to form an early prediction model for ARC, which was evaluated by the area under the ROC curve (AUC), accuracy (ACC) and other indicators.
One China PICU.
Severe sepsis children with MRSA infection admitted to PICU from May 2017 to June 2022 at Children's Hospital of Nanjing Medical University.
None.
125 of 167 (74.9%) patients with severe sepsis with MRSA infection have occurred ARC during the hospitalization of PICU, of which 44% have an absolute decrease in vancomycin trough level (VTL), patients with ARC have a longer length of stay in both hospital and PICU, lower VTL and require longer anti-infective treatment. 20 different models were established for the early recognition of ARC. Among them, the best performer had an AUC of 0.746 and a high application prospect.
ARC is a phenomenon significantly underestimated in pediatric patients with severe sepsis associated with MRSA infection, which can affect 74.9% of these patients and affects the process of anti-infection treatment and clinical outcomes. To achieve early prediction only by specific risk factors is unreliable, a model based on Multivariate Logistic Regression in this study was chosen to be used clinically.
探讨耐甲氧西林金黄色葡萄球菌(MRSA)感染的重症脓毒症患儿强化肾清除率(ARC)的流行病学特征,并寻找危险因素以建立预测儿科重症监护病房(PICU)中ARC发生的模型。
回顾性研究,其中ARC通过改良的Schwartz公式测量的估计肾小球滤过率(eGFR)高于130 ml/min/1.73 m²来定义。进行单变量和多变量逻辑回归分析以寻找ARC的预测因素。采用多策略建模形成ARC的早期预测模型,并通过ROC曲线下面积(AUC)、准确性(ACC)等指标进行评估。
中国一家PICU。
2017年5月至2022年6月在南京医科大学附属儿童医院PICU收治的MRSA感染的重症脓毒症患儿。
无。
167例MRSA感染的重症脓毒症患者中有125例(74.9%)在PICU住院期间发生了ARC,其中44%的患者万古霉素谷浓度(VTL)绝对下降,发生ARC的患者在医院和PICU的住院时间更长,VTL更低,且需要更长时间的抗感染治疗。建立了20种不同的模型用于ARC的早期识别。其中,表现最佳的模型AUC为0.746,具有较高的应用前景。
ARC是在与MRSA感染相关的儿科重症脓毒症患者中被显著低估的一种现象,可影响74.9%的此类患者,并影响抗感染治疗过程和临床结局。仅通过特定危险因素实现早期预测并不可靠,本研究中基于多变量逻辑回归的模型被选择用于临床。