Cardioavascular Science Research Group, Division of Cardiovascular Sciences, The University of Manchester.
Emergency Medical Services Department, College of Applied Medical Sciences, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Eur J Emerg Med. 2019 Oct;26(5):356-361. doi: 10.1097/MEJ.0000000000000575.
Several decision aids can 'rule in' and 'rule out' acute coronary syndromes (ACS) in the Emergency Department (ED) but all require measurement of blood biomarkers. A decision aid that does not require biomarker measurement could enhance risk stratification at triage and could be used in the prehospital environment. We aimed to derive and validate the History and ECG-only Manchester ACS (HE-MACS) decision aid using only the history, physical examination and ECG.
We undertook secondary analyses in three prospective diagnostic accuracy studies that included patients presenting to the ED with suspected cardiac chest pain. Clinicians recorded clinical features at the time of arrival using a bespoke form. Patients underwent serial troponin sampling and 30-day follow-up for the primary outcome of ACS. The model was derived by logistic regression in one cohort and validated in two similar prospective studies.
The HE-MACS model was derived in 796 patients and validated in cohorts of 474 and 659 patients. HE-MACS incorporated age, sex, systolic blood pressure plus five historical variables to stratify patients into four risk groups. On validation, 5.5 and 12.1% (pooled total 9.4%) patients were identified as 'very low risk' (potential immediate rule out) with a pooled sensitivity of 99.5% (95% confidence interval: 97.1-100.0%).
Using only the patient's history and ECG, HE-MACS could 'rule out' ACS in 9.4% of patients while effectively risk stratifying remaining patients. This is a very promising tool for triage in both the prehospital environment and ED. Its impact should be prospectively evaluated in those settings.
有几种决策辅助工具可以在急诊室（ED）中“确定”和“排除”急性冠状动脉综合征（ACS），但都需要测量血液生物标志物。一种不需要测量生物标志物的决策辅助工具可以在分诊时增强风险分层，并且可以在院前环境中使用。我们旨在仅使用病史、体格检查和心电图来推导和验证仅基于病史和心电图的曼彻斯特 ACS（HE-MACS）决策辅助工具。
我们对包括疑似心前区胸痛就诊于 ED 的患者的三项前瞻性诊断准确性研究进行了二次分析。临床医生使用专门的表格在到达时记录临床特征。患者接受了连续的肌钙蛋白采样和 30 天随访，以评估 ACS 的主要结局。该模型通过一个队列中的逻辑回归推导，并在两个类似的前瞻性研究中进行验证。
HE-MACS 模型在 796 例患者中推导，并在 474 例和 659 例患者的队列中验证。HE-MACS 将年龄、性别、收缩压加五个病史变量纳入模型，以将患者分为四个风险组。在验证中，5.5%和 12.1%（总合并率为 9.4%）的患者被确定为“极低风险”（潜在的立即排除），合并敏感性为 99.5%（95%置信区间：97.1-100.0%）。
仅使用患者的病史和心电图，HE-MACS 可以在 9.4%的患者中“排除”ACS，同时有效地对其余患者进行风险分层。这是一种非常有前途的分诊工具，可用于院前环境和 ED。应在这些环境中前瞻性评估其效果。
