Myocardial Infarction
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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 - Polygenic risk score adds to a clinical risk score in the prediction of cardiovascular disease in a clinical setting.
Nilesh J Samani et al. Eur Heart J 2024 - The potential of virtual triage AI to improve early detection, care acuity alignment, and emergent care referral of life-threatening conditions.
George A Gellert et al. Front Public Health 2024 121362246 - Development and validation of risk prediction model for recurrent cardiovascular events among Chinese: the Personalized CARdiovascular DIsease risk Assessment for Chinese model.
Yekai Zhou et al. Eur Heart J Digit Health 2024 5(3) 363-370 - 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 - Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.
Alberto Montesanto et al. Front Endocrinol (Lausanne) 2024 151359482 - The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.
Blazej Michalski et al. Cardiol J 2024 - Genome-wide association studies reveal differences in genetic susceptibility between single events vs. recurrent events of atrial fibrillation and myocardial infarction: the HUNT study.
Martina Hall et al. Front Cardiovasc Med 2024 111372107 - 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)
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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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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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