脓毒症相关急性肾损伤风险预测的研究现状及进展

Research Status and Advances in Risk Prediction of Sepsis-Associated Acute Kidney Injury

摘要: 急性肾损伤(AKI)是脓毒症患者最常见且最严重的器官功能障碍之一，具有发生率高、病死率高、医疗费用昂贵等特点。脓毒症相关AKI (Sepsis-associated AKI, SA-AKI)占重症监护病房(ICU)中AKI病例的40%~50%，是导致患者死亡的独立危险因素。传统的AKI预测方法存在准确性不足、时效性差等局限性，难以在肾功能恶化早期进行有效识别。近年来，机器学习算法在SA-AKI风险预测中的应用日益广泛，显示出良好的预测性能和临床应用前景。本文综述了SA-AKI的流行病学特征、发病机制、诊断标准以及机器学习算法在脓毒症相关AKI预测中的研究进展，分析了当前研究的不足与挑战，并展望了未来的发展方向。

Abstract: Acute kidney injury (AKI) is one of the most common and serious organ dysfunction in patients with sepsis, which has the characteristics of high incidence, high mortality and expensive medical expenses. Sepsis-associated AKI (SA-AKI) accounts for 40%~50% of AKI cases in intensive care unit (ICU), and it is an independent risk factor for patients’ death. The traditional AKI prediction method has some limitations, such as insufficient accuracy and poor timeliness, and it is difficult to effectively identify the early deterioration of renal function. In recent years, machine learning algorithm has been widely used in SA-AKI risk prediction, showing good prediction performance and clinical application prospect. This paper summarizes the epidemiological characteristics, pathogenesis, diagnostic criteria and research progress of machine learning algorithm in the prediction of Sepsis-associated AKI, analyzes the shortcomings and challenges of current research, and looks forward to the future development direction.