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Readily accessible risk model to predict in-hospital major adverse cardiac events in patients with acute myocardial infarction: a retrospective study of Chinese patients

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机构: [1]Capital Med Univ, Beijing Tongren Hosp, Cardiovasc Ctr, Beijing, Peoples R China [2]Capital Med Univ, Beijing AnZhen Hosp, Natl Clin Res Ctr Cardiovasc Dis, Dept Cardiol, Beijing, Peoples R China [3]Heart Hlth Res Ctr, Beijing, Peoples R China [4]Univ New South Wales, Fac Med, George Inst Global Hlth, Sydney, NSW, Australia [5]Zhengzhou Univ, Affiliated Hosp 1, Dept Cardiol, Zhengzhou, Peoples R China [6]Jilin Univ, Cardiovasc Dis Ctr, Hosp 1, Jilin, Jilin, Peoples R China [7]IBM Res China, Beijing, Peoples R China
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关键词: myocardial infarction risk management adverse events

摘要:
Objective 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. Design Retrospective review of deidentified medical records. Setting 38 urban and rural hospitals across diverse economic and geographic areas in China (Beijing, Henan Province and Jilin Province). Participants 15 009 patients discharged from hospital with a diagnosis of AMI. Main outcome measure 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. Results 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(9)/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). Conclusions The CHARM model provides an inexpensive, accurate and readily accessible tool for predicting in-hospital MACE in Chinese patients with AMI.

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出版当年[2020]版:
大类 | 3 区 医学
小类 | 3 区 医学:内科
最新[2025]版:
大类 | 4 区 医学
小类 | 4 区 医学:内科
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出版当年[2019]版:
Q2 MEDICINE, GENERAL & INTERNAL
最新[2023]版:
Q1 MEDICINE, GENERAL & INTERNAL

影响因子: 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版] 出版后一年[2020版]

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第一作者机构: [1]Capital Med Univ, Beijing Tongren Hosp, Cardiovasc Ctr, Beijing, Peoples R China
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