Dawson Luke P, Andrew Emily, Nehme Ziad, Bloom Jason, Liew Danny, Cox Shelley, Anderson David, Stephenson Michael, Lefkovits Jeffrey, Taylor Andrew J, Kaye David, Cullen Louise, Smith Karen, Stub Dion
Department of Cardiology, The Alfred Hospital, Melbourne, Victoria, Australia.
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Int J Cardiol Heart Vasc. 2022 Apr 28;40:101043. doi: 10.1016/j.ijcha.2022.101043. eCollection 2022 Jun.
Existing risk scores for undifferentiated chest pain focus on excluding coronary events and do not represent a comprehensive risk assessment if an alternate serious diagnosis is present. This study aimed to develop and validate an all-inclusive risk prediction model among patients with undifferentiated chest pain.
We developed and validated a multivariable logistic regression model for a composite measure of early all-inclusive risk (defined as hospital admission excluding a discharge diagnosis of non-specific pain, 30-day all-cause mortality, or 30-day myocardial infarction [MI]) among adults assessed by emergency medical services (EMS) for non-traumatic chest pain using a large population-based cohort (January 2015 to June 2019). The cohort was randomly divided into development (146,507 patients [70%]) and validation (62,788 patients [30%]) cohorts.
The composite outcome occurred in 28.4%, comprising hospital admission in 27.7%, mortality within 30-days in 1.8%, and MI within 30-days in 0.4%. The Early Chest pain Admission, MI, and Mortality (ECAMM) risk model was developed, demonstrating good discrimination in the development (C-statistic 0.775, 95% CI 0.772-0.777) and validation cohorts (C-statistic 0.765, 95% CI 0.761-0.769) with excellent calibration. Discriminatory performance for the composite outcome and individual components was higher than existing scores commonly used in undifferentiated chest pain risk stratification.
The ECAMM risk score model can be used as an all-inclusive risk stratification assessment of patients with non-traumatic chest pain without the limitation of a single diagnostic outcome. This model could be clinically useful to help guide decisions surrounding the need for non-coronary investigations and safety of early discharge.
现有的未分化胸痛风险评分主要关注排除冠状动脉事件，如果存在其他严重诊断，则不能代表全面的风险评估。本研究旨在开发并验证一种针对未分化胸痛患者的综合风险预测模型。
我们开发并验证了一个多变量逻辑回归模型，用于评估通过紧急医疗服务（EMS）评估的非创伤性胸痛成年患者的早期综合风险（定义为住院但排除出院诊断为非特异性疼痛、30天全因死亡率或30天心肌梗死[MI]），使用的是基于大量人群的队列（2015年1月至2019年6月）。该队列被随机分为开发队列（146,507例患者[70%]）和验证队列（62,788例患者[30%]）。
综合结局发生率为28.4%，包括住院率27.7%、30天内死亡率1.8%和30天内心肌梗死率0.4%。开发了早期胸痛入院、心肌梗死和死亡率（ECAMM）风险模型，在开发队列（C统计量0.775，95%CI 0.772 - 0.777）和验证队列（C统计量0.765，95%CI 0.761 - 0.769）中显示出良好的区分度，且校准良好。综合结局和各个组成部分的鉴别性能高于未分化胸痛风险分层中常用的现有评分。
ECAMM风险评分模型可作为非创伤性胸痛患者的综合风险分层评估，不受单一诊断结局的限制。该模型在临床上可能有助于指导围绕非冠状动脉检查需求和早期出院安全性的决策。
