He Zhenshuo, Wang Haizhi, Wang Shan, Li Lu
Department of Laboratory Medicine, The Sixth People's Hospital of Hengshui City, Hengshui, 053099, People's Republic of China.
Department of Laboratory Medicine, The People's Hospital of Hengshui City, Hengshui, 053099, People's Republic of China.
Int J Gen Med. 2022 Nov 24;15:8315-8326. doi: 10.2147/IJGM.S389846. eCollection 2022.
We wanted to demonstrate whether the initial platelet-to-albumin ratio (PAR) had predictive value for cardiac surgery-associated acute kidney injury (CSA-AKI) and prognosis of critical care patients.
This is an observational and multi-center study from the MIMIC-IV database, the eICU-CRD database as well as CS patients at our institution. Logistic regression and Cox regression analyses were applied to determine the predictive value for CSA-AKI and in-hospital mortality. LASSO and SVM-RFE models were then employed to discover the coincident variables connected with CSA-AKI. The main objective of this research was the incidence of CSA-AKI, whereas the secondary endpoint was in-hospital death.
The higher PAR value (≥4.67) had a higher risk of CSA-AKI (adjusted OR = 4.02, 95% CI 3.41-4.75, P < 0.001) and in-hospital mortality (HR = 2.41 95% CI 1.44-4.03, P = 0.001) after adjusted for other confounding factors including patients with or without chronic kidney disease. The proposed nomogram based on PAR and others clinical factors selected by LASSO and SVM-RFE models for CSA-AKI had the C-index 0.821 (95% CI 0.807-0.834), 0.808 (95% CI 0.787-0.829), 0.745 (95% CI 0.728-0.762), and 0.826 (95% CI 0.753-0.899) in these cohorts, respectively. The nomogram exhibited both remarkable calibration capacity and therapeutic helpfulness in all groups.
PAR is a relative excellent measure for the event AKI and prognosis of ICU patients who undergone CS. The suggested nomogram based on PAR resulted in an accurate prediction for the detection of critical care patients with CSA-AKI.
我们想要证明初始血小板与白蛋白比值(PAR)对心脏手术相关急性肾损伤(CSA-AKI)及重症监护患者的预后是否具有预测价值。
这是一项来自MIMIC-IV数据库、eICU-CRD数据库以及我们机构的CS患者的观察性多中心研究。应用逻辑回归和Cox回归分析来确定对CSA-AKI和院内死亡率的预测价值。然后采用LASSO和支持向量机递归特征消除(SVM-RFE)模型来发现与CSA-AKI相关的一致变量。本研究的主要目标是CSA-AKI的发生率,次要终点是院内死亡。
在对包括有无慢性肾病患者等其他混杂因素进行校正后,较高的PAR值(≥4.67)发生CSA-AKI的风险更高(校正后的比值比=4.02,95%置信区间3.41-4.75,P<0.001)以及院内死亡率更高(风险比=2.41,95%置信区间1.44-4.03,P=0.001)。基于PAR以及由LASSO和SVM-RFE模型选择的其他临床因素所构建的用于预测CSA-AKI的列线图,在这些队列中的C指数分别为0.821(95%置信区间0.807-0.834)、0.808(95%置信区间0.787-0.829)、0.745(95%置信区间0.728-0.762)和0.826(95%置信区间0.753-0.899)。该列线图在所有组中均表现出显著的校准能力和治疗实用性。
PAR是接受心脏手术的ICU患者发生急性肾损伤事件及预后的相对优良指标。基于PAR的建议列线图对检测CSA-AKI的重症监护患者可做出准确预测。