医学
胸痛
心肌梗塞
急诊科
内科学
接收机工作特性
经皮冠状动脉介入治疗
心脏病学
血运重建
切断
诊断试验中的似然比
曲线下面积
观察研究
急诊医学
物理
量子力学
精神科
作者
Braylee Grisel,Olanrewaju Adisa,Francis Sakita,Tumsifu G. Tarimo,Godfrey L. Kweka,Jerome J. Mlangi,Amedeus V. Maro,Marilyn Yamamoto,Lauren Coaxum,David Arthur,Alexander T. Limkakeng,Julian T. Hertz
摘要
Abstract Objective The HEART score successfully risk stratifies emergency department (ED) patients with chest pain in high‐income settings. However, this tool has not been validated in low‐income countries. Methods This is a secondary analysis of a prospective observational study that was conducted in a Tanzanian ED from January 2019 through January 2023. Adult patients with chest pain were consecutively enrolled, and their presenting symptoms and medical history were recorded. Electrocardiograms and point‐of‐care troponin assays were obtained for all participants. Thirty‐day follow‐up was conducted, assessing for major adverse cardiac events (MACEs), defined as death, myocardial infarction, or coronary revascularization (coronary artery bypass grafting or percutaneous coronary intervention). HEART scores were calculated for all participants. Likelihood ratios, sensitivity, specificity, and negative predictive values (NPVs) were calculated for each HEART cutoff score to predict 30‐day MACEs, and area under the curve (AUC) was calculated from the receiver operating characteristic curve. Results Of 927 participants with chest pain, the median (IQR) age was 61 (45.5–74.0) years. Of participants, 216 (23.3%) patients experienced 30‐day MACEs, including 163 (17.6%) who died, 48 (5.2%) with myocardial infarction, and 23 (2.5%) with coronary revascularization. The positive likelihood ratio for each cutoff score ranged from 1.023 (95% CI 1.004–1.042; cutoff ≥ 1) to 3.556 (95% CI 1.929–6.555; cutoff ≥ 7). The recommended cutoff of ≥4 to identify patients at high risk of MACEs yielded a sensitivity of 59.4%, specificity of 52.8%, and NPV of 74.7%. The AUC was 0.61. Conclusions Among patients with chest pain in a Tanzanian ED, the HEART score did not perform as well as in high‐income settings. Locally validated risk stratification tools are needed for ED patients with chest pain in low‐income countries.
科研通智能强力驱动
Strongly Powered by AbleSci AI