Percutaneous Coronary Intervention
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Last Posted: Jun 20, 2024
- CYP2C19 Genotype Is Associated With Adverse Cardiovascular Outcomes in Black Patients Treated With Clopidogrel Undergoing Percutaneous Coronary Intervention.
Kayla R Tunehag et al. J Am Heart Assoc 2024 e033791 - Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.
Yanxu Liu et al. Sci Rep 2024 14(1) 13393 - Machine learning predictions of the adverse events of different treatments in patients with ischemic left ventricular systolic dysfunction.
Wenjie Chen et al. Intern Emerg Med 2024 - Machine learning prediction of one-year mortality after percutaneous coronary intervention in acute coronary syndrome patients.
Kaveh Hosseini et al. Int J Cardiol 2024 409132191 - Cardiovascular outcomes in patients with homozygous familial hypercholesterolaemia on lipoprotein apheresis initiated during childhood: long-term follow-up of an international cohort from two registries.
M Doortje Reijman et al. Lancet Child Adolesc Health 2024 - The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.
Blazej Michalski et al. Cardiol J 2024 - 1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction.
Seyed Reza Razavi et al. Medicina (Kaunas) 2024 60(4) - Using the Super Learner algorithm to predict risk of major adverse cardiovascular events after percutaneous coronary intervention in patients with myocardial infarction.
Xiang Zhu et al. BMC Med Res Methodol 2024 24(1) 59 - Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach.
Amir Hossein Behnoush et al. Eur J Med Res 2024 29(1) 76 - Machine Learning for Early Prediction of Major Adverse Cardiovascular Events After First Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Retrospective Cohort Study.
Pin Zhang et al. JMIR Form Res 2024 8e48487
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About HLBS-PopOmics
HLBS-PopOmics is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic and other precision health discoveries into improved health care and prevention related to Heart and Vascular Diseases(H), Lung Diseases(L), Blood Diseases(B), and Sleep Disorders(S)...more
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Site Citation:
Mensah GA, Yu W, Barfield WL, Clyne M, Engelgau MM, Khoury MJ. HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders. Genet Med. 2018 Sep 10. doi: 10.1038/s41436-018-0118-1
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by Public Health Genomics Branch to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
- Page last reviewed:Feb 1, 2024
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