Cardiovascular Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Department of Cardiology, Beijing AnZhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Beijing, China.
BMJ Open. 2021 Jul 1;11(7):e044518. doi: 10.1136/bmjopen-2020-044518.
Rapid, accurate identification of patients with acute myocardial infarction (AMI) at high risk of in-hospital major adverse cardiac events (MACE) is critical for risk stratification and prompt management. This study aimed to develop a simple, accessible tool for predicting in-hospital MACE in Chinese patients with AMI.
Retrospective review of deidentified medical records.
38 urban and rural hospitals across diverse economic and geographic areas in China (Beijing, Henan Province and Jilin Province).
15 009 patients discharged from hospital with a diagnosis of AMI.
The primary outcome was MACE occurrence during index hospitalisation. A multivariate logistic regression model (China AMI Risk Model, CHARM) derived using patient data from Beijing (n=7329) and validated with data from Henan (n=4247) and Jilin (n=3433) was constructed to predict the primary outcome using variables of age, white cell count (WCC) and Killip class. C-statistics evaluated discrimination in the derivation and validation cohorts, with goodness-of-fit assessed using Hosmer-Lemeshow statistics.
The CHARM model included age (OR: 1.06 per 1-year increment, 95% CI 1.05 to 1.07, p<0.001), WCC (OR per 10/L increment: 1.10 (95% CI 1.07 to 1.13), p<0.001) and Killip class (class II vs class I: OR 1.34 (95% CI 0.99 to 1.83), p=0.06; class III vs class I: OR 2.74 (95% CI 1.86 to 3.97), p<0.001; class IV vs class I: OR 14.12 (95% CI 10.35 to 19.29), p<0.001). C-statistics were similar between the derivation and validation datasets. CHARM had a higher true positive rate than the Thrombolysis In Myocardial Infarction score and similar to the Global Registry of Acute Coronary Events (GRACE). Hosmer-Lemeshow statistics were 5.5 (p=0.703) for derivation, 41.1 (p<0.001) for Henan, and 103.2 for Jilin (p<0.001) validation sets with CHARM, compared with 119.6, 34.0 and 459.1 with GRACE (all p<0.001).
The CHARM model provides an inexpensive, accurate and readily accessible tool for predicting in-hospital MACE in Chinese patients with AMI.
快速准确地识别发生院内主要不良心脏事件（MACE）风险较高的急性心肌梗死（AMI）患者，对于风险分层和及时管理至关重要。本研究旨在开发一种简单、易于使用的工具，用于预测中国 AMI 患者的院内 MACE。
回顾性分析匿名病历。
中国 38 家城市和农村医院，分布在不同经济和地理区域（北京、河南省和吉林省）。
15009 名出院时诊断为 AMI 的患者。
主要结局为指数住院期间发生 MACE。使用来自北京（n=7329）的数据构建并使用来自河南（n=4247）和吉林（n=3433）的数据进行验证的多变量逻辑回归模型（中国 AMI 风险模型，CHARM），使用年龄、白细胞计数（WCC）和 Killip 分级等变量预测主要结局。C 统计量评估了推导和验证队列中的判别能力，通过 Hosmer-Lemeshow 统计量评估拟合优度。
CHARM 模型包括年龄（每增加 1 岁，OR：1.06，95%CI 1.05 至 1.07，p<0.001）、WCC（每增加 10/L，OR：1.10，95%CI 1.07 至 1.13，p<0.001）和 Killip 分级（Ⅱ级与Ⅰ级，OR：1.34，95%CI 0.99 至 1.83，p=0.06；Ⅲ级与Ⅰ级，OR：2.74，95%CI 1.86 至 3.97，p<0.001；Ⅳ级与Ⅰ级，OR：14.12，95%CI 10.35 至 19.29，p<0.001）。推导和验证数据集之间的 C 统计量相似。CHARM 的真阳性率高于溶栓治疗心肌梗死评分，与全球急性冠状动脉事件登记处（GRACE）相似。CHARM 的 Hosmer-Lemeshow 统计量为 5.5（p=0.703），用于推导，41.1（p<0.001）用于河南，103.2 用于吉林，与 GRACE 相比分别为 119.6、34.0 和 459.1（均 p<0.001）。
CHARM 模型为预测中国 AMI 患者院内 MACE 提供了一种廉价、准确、易于获取的工具。
