Body Richard
Division of Cardiovascular Sciences, The University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom.
Emergency Department, Manchester University Foundation NHS Trust, Oxford Road, Manchester, M13 9WL, United Kingdom.
Turk J Emerg Med. 2018 Jul 13;18(3):94-99. doi: 10.1016/j.tjem.2018.05.005. eCollection 2018 Sep.
Chest pain accounts for approximately 6% of Emergency Department (ED) attendances and is the most common reason for emergency hospital admission. For many years, our approach to diagnosis has required patients to stay in hospital for at least 6-12 h to undergo serial biomarker testing. As less than one fifth of the patients undergoing investigation actually has an acute coronary syndrome (ACS), there is tremendous potential to reduce unnecessary hospital admissions. Recent advances in diagnostic technology have improved the efficiency of care pathways. Decision aids such as the Thrombolysis in Myocardial Infarction (TIMI) risk score and the History, Electrocardiogram, Age, Risk factors and Troponin (HEART) score enable rapid 'rule out' of ACS within hours of patients arriving in the ED. With high sensitivity cardiac troponin (hs-cTn) assays, approximately one third of patients can have ACS 'ruled out' with a single blood test, and up to two thirds could have an acute myocardial infarction 'ruled out' with a second sample taken after as little as 1 h. Building on those recent advances, this paper presents an overview of the principles behind the development of the Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid. This clinical prediction model could be used to 'rule out' and 'rule in' ACS following a single blood test and to calculate the probability of ACS for every patient. The future potential of this approach is then addressed, including practical applications of artificial intelligence, shared decision making, near-patient testing and personalized medicine.
胸痛约占急诊科就诊人数的6%，是医院急诊入院最常见的原因。多年来，我们的诊断方法要求患者住院至少6 - 12小时，以便进行一系列生物标志物检测。由于接受检查的患者中实际患有急性冠状动脉综合征（ACS）的不到五分之一，因此减少不必要的住院治疗有巨大潜力。诊断技术的最新进展提高了护理路径的效率。诸如心肌梗死溶栓（TIMI）风险评分以及病史、心电图、年龄、危险因素和肌钙蛋白（HEART）评分等决策辅助工具，能够在患者抵达急诊科后的数小时内快速“排除”ACS。借助高敏心肌肌钙蛋白（hs - cTn）检测，约三分之一的患者通过单次血液检测即可“排除”ACS，而在仅1小时后采集的第二份样本检测后，高达三分之二的患者可“排除”急性心肌梗死。基于这些最新进展，本文概述了仅肌钙蛋白的曼彻斯特急性冠状动脉综合征（T - MACS）决策辅助工具开发背后的原理。这种临床预测模型可用于单次血液检测后对ACS进行“排除”和“纳入”诊断，并计算每位患者患ACS的概率。随后探讨了这种方法的未来潜力，包括人工智能的实际应用、共同决策、床旁检测和个性化医疗。
