Prehospital Prediction of Cardiogenic Shock Among Patients With ST-Segment-Elevation Myocardial Infarction: The EARLY SHOCK Score.

IF 5.3 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Journal of the American Heart Association Pub Date : 2025-10-07 Epub Date: 2025-08-12 DOI:10.1161/JAHA.124.040681
Cathevine Yang, Terry Lee, Andrew Kochan, Madeleine Barker, Thomas M Roston, John A Cairns, Joel Singer, Brian Grunau, Jennie Helmer, David D Berg, Graham C Wong, Christopher B Fordyce
{"title":"Prehospital Prediction of Cardiogenic Shock Among Patients With ST-Segment-Elevation Myocardial Infarction: The EARLY SHOCK Score.","authors":"Cathevine Yang, Terry Lee, Andrew Kochan, Madeleine Barker, Thomas M Roston, John A Cairns, Joel Singer, Brian Grunau, Jennie Helmer, David D Berg, Graham C Wong, Christopher B Fordyce","doi":"10.1161/JAHA.124.040681","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in-hospital CS among patients undergoing primary percutaneous coronary intervention for ST-segment-elevation myocardial infarction.</p><p><strong>Methods: </strong>The authors conducted a retrospective cohort study using prospective data from a dual hub-and-spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in-hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients.</p><p><strong>Results: </strong>From April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest.</p><p><strong>Conclusions: </strong>The authors identified 8 clinical variables that strongly predict CS among patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application.</p>","PeriodicalId":54370,"journal":{"name":"Journal of the American Heart Association","volume":" ","pages":"e040681"},"PeriodicalIF":5.3000,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Heart Association","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1161/JAHA.124.040681","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/12 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in-hospital CS among patients undergoing primary percutaneous coronary intervention for ST-segment-elevation myocardial infarction.

Methods: The authors conducted a retrospective cohort study using prospective data from a dual hub-and-spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in-hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients.

Results: From April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest.

Conclusions: The authors identified 8 clinical variables that strongly predict CS among patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application.

st段抬高型心肌梗死患者院前心源性休克的预测:早期休克评分
背景:心源性休克(CS)在高达10%的st段抬高型心肌梗死患者中发生,并与高死亡率和发病率相关。本研究的目的是建立一个易于院前应用的临床评分系统,以预测因st段抬高型心肌梗死而接受原发性经皮冠状动脉介入治疗的患者院内CS的发展。方法:作者进行了一项回顾性队列研究,使用来自双中心-辐卫生系统的前瞻性数据。采用Logistic回归评估预先设定的临床预测因素与院内CS发生的关系。对预测模型的C统计量和标定曲线进行了内部验证。通过对回归系数进行标度,将预测模型转换为风险评分。结果:2012年4月1日至2020年12月31日,连续2736例st段抬高型心肌梗死患者行经皮冠状动脉介入治疗。其中415例(15.2%)发生CS。通过多变量分析,8个强预测因子与CS独立相关,并用于建立预测模型。模型的C统计量为0.87。早期休克风险评分算法结合了紧急医疗服务心率和收缩压、年龄、肾脏替代、梗死位置、血糖(糖尿病)、心力衰竭和心脏骤停。结论:作者确定了8个临床变量,可以预测st段抬高型心肌梗死患者接受原发性经皮冠状动脉介入治疗时的CS。这已经发展成为早期休克评分,它可以很容易地应用于院前设置,以快速识别CS并激活休克小组。评分系统的外部验证正在等待更广泛的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of the American Heart Association
Journal of the American Heart Association CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
9.40
自引率
1.90%
发文量
1749
审稿时长
12 weeks
期刊介绍: As an Open Access journal, JAHA - Journal of the American Heart Association is rapidly and freely available, accelerating the translation of strong science into effective practice. JAHA is an authoritative, peer-reviewed Open Access journal focusing on cardiovascular and cerebrovascular disease. JAHA provides a global forum for basic and clinical research and timely reviews on cardiovascular disease and stroke. As an Open Access journal, its content is free on publication to read, download, and share, accelerating the translation of strong science into effective practice.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信