Bihorac Azra
Department of Anesthesiology, University of Florida, Gainesville, Fla., USA.
Nephron. 2015;131(2):118-22. doi: 10.1159/000439387. Epub 2015 Sep 8.
Postoperative acute kidney injury (AKI) is not only one of the most common postoperative complications but is also associated with increased in-hospital mortality, decreased survival for up to 10 years after surgery and an increased risk for progression to chronic kidney disease and hemodialysis. Most of the studies that have developed clinically applicable risk models for prediction of AKI have focused on the most severe stages of AKI and rarely on less severe stages defined by consensus definitions. Furthermore, although multiple physiological signals are continuously recorded as a part of intraoperative management, their use for the development of risk models for AKI has been limited. Accurate risk stratification of patients in real time would enable the selection of optimal therapy in a timely fashion to prevent AKI altogether, or to mitigate the effects of the complication even before symptoms arise and can be tailored to a patients' personal clinical profile.
术后急性肾损伤(AKI)不仅是最常见的术后并发症之一,还与住院死亡率增加、术后长达10年的生存率降低以及进展为慢性肾脏病和接受血液透析的风险增加有关。大多数已开发出用于预测AKI的临床适用风险模型的研究都集中在AKI的最严重阶段,很少关注由共识定义所界定的较轻阶段。此外,尽管作为术中管理的一部分会持续记录多种生理信号,但它们在AKI风险模型开发中的应用一直有限。对患者进行实时准确的风险分层将能够及时选择最佳治疗方法,以完全预防AKI,或者甚至在症状出现之前减轻并发症的影响,并可根据患者的个人临床特征进行调整。