Li Lulu, Zhang Xiling, Wang Yini, Yu Xi, Jia Haibo, Hou Jingbo, Li Chunjie, Zhang Wenjuan, Yang Wei, Liu Bin, Lu Lixin, Tan Ning, Yu Bo, Li Kang
Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, China.
Department of Cardiology, Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Front Cardiovasc Med. 2022 Apr 7;9:840485. doi: 10.3389/fcvm.2022.840485. eCollection 2022.
The aim of this study was to develop and validate a novel risk score to predict in-hospital mortality in patients with acute myocardial infarction (AMI) using the Heart Failure after Acute Myocardial Infarction with Optimal Treatment (HAMIOT) cohort in China.
The HAMIOT cohort was a multicenter, prospective, observational cohort of consecutive patients with AMI in China. All participants were enrolled between December 2017 and December 2019. The cohort was randomly assigned (at a proportion of 7:3) to the training and validation cohorts. Logistic regression model was used to develop and validate a predictive model of in-hospital mortality. The performance of discrimination and calibration was evaluated using the Harrell's c-statistic and the Hosmer-Lemeshow goodness-of-fit test, respectively. The new simplified risk score was validated in an external cohort that included independent patients with AMI between October 2019 and March 2021.
A total of 12,179 patients with AMI participated in the HAMIOT cohort, and 136 patients were excluded. In-hospital mortality was 166 (1.38%). Ten predictors were found to be independently associated with in-hospital mortality: age, sex, history of percutaneous coronary intervention (PCI), history of stroke, presentation with ST-segment elevation, heart rate, systolic blood pressure, initial serum creatinine level, initial N-terminal pro-B-type natriuretic peptide level, and PCI treatment. The c-statistic of the novel simplified HAMIOT risk score was 0.88, with good calibration (Hosmer-Lemeshow test: = 0.35). Compared with the Global Registry of Acute Coronary Events risk score, the HAMIOT score had better discrimination ability in the training (0.88 vs. 0.81) and validation (0.82 vs. 0.72) cohorts. The total simplified HAMIOT risk score ranged from 0 to 121. The observed mortality in the HAMIOT cohort increased across different risk groups, with 0.35% in the low risk group (score ≤ 50), 3.09% in the intermediate risk group (50 < score ≤ 74), and 14.29% in the high risk group (score > 74).
The novel HAMIOT risk score could predict in-hospital mortality and be a valid tool for prospective risk stratification of patients with AMI.
[https://clinicaltrials.gov], Identifier: [NCT03297164].
本研究旨在利用中国急性心肌梗死合并最佳治疗后心力衰竭（HAMIOT）队列开发并验证一种新型风险评分，以预测急性心肌梗死（AMI）患者的院内死亡率。
HAMIOT队列是中国一个多中心、前瞻性、观察性的连续AMI患者队列。所有参与者于2017年12月至2019年12月入组。该队列被随机分配（按7:3的比例）到训练队列和验证队列。采用逻辑回归模型开发并验证院内死亡率的预测模型。分别使用Harrell's c统计量和Hosmer-Lemeshow拟合优度检验评估区分度和校准性能。新的简化风险评分在一个外部队列中进行验证，该外部队列包括2019年10月至2021年3月期间独立的AMI患者。
共有12179例AMI患者参与了HAMIOT队列，136例患者被排除。院内死亡率为166例（1.38%）。发现10个预测因素与院内死亡率独立相关：年龄、性别、经皮冠状动脉介入治疗（PCI）史、中风史、ST段抬高表现、心率、收缩压、初始血清肌酐水平、初始N末端B型利钠肽原水平和PCI治疗。新型简化HAMIOT风险评分的c统计量为0.88，校准良好（Hosmer-Lemeshow检验：P = 0.35）。与全球急性冠状动脉事件注册风险评分相比，HAMIOT评分在训练队列（0.88对0.81）和验证队列（0.82对0.72）中具有更好的区分能力。简化后的HAMIOT总风险评分范围为0至121。HAMIOT队列中不同风险组的观察到的死亡率有所增加，低风险组（评分≤50）为0.35%，中风险组（50＜评分≤74）为3.09%，高风险组（评分＞74）为14.29%。
新型HAMIOT风险评分可以预测院内死亡率，是AMI患者前瞻性风险分层的有效工具。
