Porter Christine J, Juurlink Irene, Bisset Linda H, Bavakunji Riaz, Mehta Rajnikant L, Devonald Mark A J
Renal and Transplant Unit, Nottingham University Hospitals NHS Trust, Nottingham, UK.
Department of Information and Computer Technology, Nottingham University Hospitals NHS Trust, Nottingham, UK.
Nephrol Dial Transplant. 2014 Oct;29(10):1888-93. doi: 10.1093/ndt/gfu082. Epub 2014 Apr 16.
Acute kidney injury (AKI) is a common and serious problem in hospitalized patients. Early detection is critical for optimal management but in practice is currently inadequate. To improve outcomes in AKI, development of early detection tools is essential.
We developed an automated real-time electronic alert system employing algorithms which combined internationally recognized criteria for AKI [Risk, Injury, Failure, Loss, End-stage kidney disease (RIFLE) and Acute Kidney Injury Network (AKIN)]. All adult patients admitted to Nottingham University Hospitals were included. Where a patient's serum creatinine increased sufficiently to define AKI, an electronic alert was issued, with referral to an intranet-based AKI guideline. Incidence of AKI Stages 1-3, in-hospital mortality, length of stay and distribution between specialties is reported.
Between May 2011 and April 2013, 59,921 alerts resulted from 22,754 admission episodes, associated with 15,550 different patients. Overall incidence of AKI for inpatients was 10.7%. Highest AKI stage reached was: Stage 1 in 7.2%, Stage 2 in 2.2% and Stage 3 in 1.3%. In-hospital mortality for all AKI stages was 18.5% and increased with AKI stage (12.5, 28.4, 35.7% for Stages 1, 2 and 3 AKI, respectively). Median length of stay was 9 days for all AKI.
This is the first fully automated real time AKI e-alert system, using AKIN and RIFLE criteria, to be introduced to a large National Health Service hospital. It has provided one of the biggest single-centre AKI datasets in the UK revealing mortality rates which increase with AKI stage. It is likely to have improved detection and management of AKI. The methodology is transferable to other acute hospitals.
急性肾损伤（AKI）是住院患者中常见且严重的问题。早期检测对于优化治疗至关重要，但在实际操作中目前还不够充分。为改善AKI的治疗效果，开发早期检测工具至关重要。
我们开发了一种自动实时电子警报系统，该系统采用算法，结合了国际公认的AKI标准[风险、损伤、衰竭、丧失、终末期肾病（RIFLE）和急性肾损伤网络（AKIN）]。纳入了所有入住诺丁汉大学医院的成年患者。当患者的血清肌酐升高到足以定义AKI时，会发出电子警报，并参考基于内联网的AKI指南。报告了1-3期AKI的发生率、住院死亡率、住院时间以及各专科之间的分布情况。
2011年5月至2013年4月期间，22754次入院事件产生了59921次警报，涉及15550名不同患者。住院患者AKI的总体发生率为10.7%。达到的最高AKI分期为：1期占7.2%，2期占2.2%，3期占1.3%。所有AKI分期的住院死亡率为18.5%，并随AKI分期增加（1期、2期和3期AKI的住院死亡率分别为12.5%、28.4%和35.7%）。所有AKI患者的中位住院时间为9天。
这是首个引入大型国民保健服务医院的、使用AKIN和RIFLE标准的全自动实时AKI电子警报系统。它提供了英国最大的单中心AKI数据集之一，揭示了死亡率随AKI分期增加的情况。它可能改善了AKI的检测和管理。该方法可应用于其他急症医院。
