Heterogeneous treatment effects of coronary artery bypass grafting in ischemic cardiomyopathy: A machine learning causal forest analysis

被引:2
|
作者
Zhou, Zhuoming [1 ]
Jian, Bohao [1 ]
Chen, Xuanyu [3 ]
Liu, Menghui [2 ]
Zhang, Shaozhao [2 ]
Fu, Guangguo [1 ]
Li, Gang [1 ]
Liang, Mengya [1 ]
Tian, Ting [3 ]
Wu, Zhongkai [1 ]
机构
[1] Sun Yat Sen Univ, Affiliated Hosp 1, Dept Cardiac Surg, 58 Zhongshan Rd 2, Guangzhou 510080, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 1, Dept Cardiol, Guangzhou, Peoples R China
[3] Sun Yat Sen Univ, Sch Math, 135 Xingang Xi Rd, Guangzhou 510275, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
causal forest; coronary artery bypass surgery; heterogeneous treatment effect; ischemic heart failure; ma- chine learning; STICH; TRIAL SURGICAL-TREATMENT; HEART-FAILURE; REVASCULARIZATION; INTERVENTIONS; DYSFUNCTION; OUTCOMES; SURGERY; DISEASE;
D O I
10.1016/j.jtcvs.2023.09.021
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objectives: We aim to evaluate the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy and to identify a group of patients to have greater benefits from coronary artery bypass grafting compared with medical therapy alone. Methods: Machine learning causal forest modeling was performed to identify the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy from the Surgical Treatment for Ischemic Heart Failure trial. The risks of death from any cause and death from cardiovascular causes between coronary artery bypass grafting and medical therapy alone were assessed in the identified subgroups. Results: Among 1212 patients enrolled in the Surgical Treatment for Ischemic Heart Failure trial, left ventricular end-systolic volume index, serum creatinine, and age were identified by the machine learning algorithm to distinguish patients with heterogeneous treatment effects. Among patients with left ventricular end-systolic volume index greater than 84 mL/m(2) and age 60.27 years or less, coronary artery bypass grafting was associated with a significantly lower risk of death from any cause (adjusted hazard ratio, 0.61; 95% CI, 0.45-0.84) and death from cardiovascular causes (adjusted hazard ratio, 0.63; 95% CI, 0.45-0.89). By contrast, the survival benefits of coronary artery bypass grafting no longer exist in patients with left ventricular end-systolic volume index 84 mL/m(2) or less and serum creatinine 1.04 mg/dL or less, or patients with left ventricular end-systolic volume index greater than 84 mL/m(2) and age more than 60.27 years. Conclusions: The current post hoc analysis of the Surgical Treatment for Ischemic Heart Failure trial identified heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy. Younger patients with severe left ventricular enlargement were more likely to derive greater survival benefits from coronary artery bypass grafting.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] Long-Term Outcomes in Patients With Ischemic Cardiomyopathy: Comparative Effectiveness of Coronary Artery Bypass Grafting versus Percutaneous Coronary Intervention
    Sun, Louise Y.
    Chen, Robert J.
    Tu, Jack, V
    Bader Eddeen, Anan
    Ruel, Marc
    CIRCULATION, 2018, 138
  • [22] Myocardial infarct size for predicting improvements in cardiac function in patients with ischemic cardiomyopathy following coronary artery bypass grafting
    Zhao, Yang
    Fu, Wei
    Hou, Xiaojie
    Zhang, Jianye
    Biekan, Jumatay
    Zhang, Hongkai
    Wang, Hui
    Dong, Ran
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2023, 13 (12) : 7814 - 7827
  • [23] Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms
    Arian, Fatemeh
    Amini, Mehdi
    Mostafaei, Shayan
    Kalantari, Kiara Rezaei
    Avval, Atlas Haddadi
    Shahbazi, Zahra
    Kasani, Kianosh
    Rajabi, Ahmad Bitarafan
    Chatterjee, Saikat
    Oveisi, Mehrdad
    Shiri, Isaac
    Zaidi, Habib
    JOURNAL OF DIGITAL IMAGING, 2022, 35 (06) : 1708 - 1718
  • [24] Coronary Artery Bypass Grafting Versus Combined Coronary Artery Bypass Grafting and Mitral Valve Repair in Treating Ischaemic Mitral Regurgitation: A Meta-analysis
    Yin, Liang
    Wang, Zhinong
    Shen, Hua
    Min, Jie
    Ling, Xinyu
    Xi, Wang
    HEART LUNG AND CIRCULATION, 2014, 23 (10) : 905 - 912
  • [25] Additional mitral valve procedure and coronary artery bypass grafting versus isolated coronary artery bypass grafting in the management of significant functional ischemic mitral regurgitation: a meta-analysis
    Teng, Zhitao
    Ma, Xiaochun
    Zhang, Qian
    Yun, Yan
    Ma, Chi
    Hu, Songtao
    Zou, Chengwei
    JOURNAL OF CARDIOVASCULAR SURGERY, 2017, 58 (01) : 121 - +
  • [26] Comparison of Coronary Artery Bypass Grafting Combined With Mitral Valve Repair Versus Coronary Artery Bypass Grafting Alone in Patients With Moderate Ischemic Mitral Regurgitation: A Meta-Analysis
    Sameer, Muhammad Ali
    Malik, Bilal Aziz
    Choudry, Muhammad Obaid Ullah
    Anwar, Muhammad Shoaib
    Nadeem, Muhammad A.
    Mahmood, Fizza
    Anwar, Muhammad Zohaib
    Palleti, Sujith K.
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2023, 15 (04)
  • [27] Machine learning in risk prediction of continuous renal replacement therapy after coronary artery bypass grafting surgery in patients
    Zhang, Qian
    Zheng, Peng
    Hong, Zhou
    Li, Luo
    Liu, Nannan
    Bian, Zhiping
    Chen, Xiangjian
    Wu, Hengfang
    Zhao, Sheng
    CLINICAL AND EXPERIMENTAL NEPHROLOGY, 2024, 28 (08) : 811 - 821
  • [28] Bilateral Versus Single Internal Mamma Artery Use in Coronary Artery Bypass Grafting: A Propensity Matched Analysis
    Zhu, Ying Yan
    Seco, Michael
    Harris, Stella R.
    Koullouros, Michalis
    Ramponi, Fabio
    Wilson, Michael
    Bannon, Paul G.
    Vallely, Michael P.
    HEART LUNG AND CIRCULATION, 2019, 28 (05) : 807 - 813
  • [29] Trimetazidine on Ischemic Injury and Reperfusion in Coronary Artery Bypass Grafting
    Martins, Gerez Fernandes
    de Siqueira Filho, Aristarco Goncalves
    de Figueiredo Santos, Joao Bosco
    Cavalcanti Assuncao, Claudio Roberto
    Bottino, Francisca
    de Carvalho, Kattia Gerundio
    Valencia, Alberto
    ARQUIVOS BRASILEIROS DE CARDIOLOGIA, 2011, 97 (03) : 209 - 216
  • [30] Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning
    Triana, Austin J.
    Vyas, Rushikesh
    Shah, Ashish S.
    Tiwari, Vikram
    JOURNAL OF SURGICAL RESEARCH, 2021, 264 : 68 - 75