Shen Christine P, Bhavnani Sanjeev P, Rogers John D
Division of Cardiology, Scripps Clinic San Diego, CA.
US Cardiol. 2024 Jul 23;18:e09. doi: 10.15420/usc.2023.25. eCollection 2024.
Mortality from sudden cardiac arrest remains high despite increased awareness and advancements in emergency resuscitation efforts. Various gaps exist in bystander resuscitation, automated external defibrillators, and access. Significant racial, gender, and geographic disparities have also been found. A myriad of recent innovations in sudden cardiac arrest uses new machine learning algorithms with high levels of performance. These have been applied to a broad range of efforts to identify individuals at high risk, recognize emergencies, and diagnose high-risk cardiac arrhythmias. Such technological advancements must be coupled to novel public health approaches to best implement these innovations in an equitable way. The authors propose a data-driven, technology-enabled system of care within a public health system of care to ultimately improve sudden cardiac arrest outcomes.
尽管人们的意识有所提高，紧急复苏措施也有所进步，但心脏骤停导致的死亡率仍然很高。在旁观者复苏、自动体外除颤器以及获取途径方面存在各种差距。还发现了显著的种族、性别和地理差异。最近在心脏骤停方面有无数创新，采用了性能水平很高的新机器学习算法。这些算法已应用于广泛的工作中，以识别高危个体、识别紧急情况以及诊断高危心律失常。此类技术进步必须与新颖的公共卫生方法相结合，以便以公平的方式最佳地实施这些创新。作者提议在公共卫生护理系统内建立一个以数据为驱动、由技术支持的护理系统，以最终改善心脏骤停的治疗结果。
