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) - Prevalence of elevated lipoprotein(a) in cardiac rehabilitation patients - results from a large-scale multicentre registry in Germany.
Christoph Altmann et al. Clin Res Cardiol 2024 - Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease.
Alessandro Pingitore et al. Int J Cardiol 2024 131981 - 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 - Novel Polygenic Risk Score and Established Clinical Risk Factors for Risk Estimation of Aortic Stenosis.
Aeron M Small et al. JAMA Cardiol 2024 2 - Sex Differences in Diagnosis, Treatment, and Cardiovascular Outcomes in Homozygous Familial Hypercholesterolemia.
Janneke W C M Mulder et al. JAMA Cardiol 2024 - Digital Health for Myocardial Infarction: Research Topics and Trends.
Melissa Pelly et al. Stud Health Technol Inform 2024 310429-433 - 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 - Prevalent Variants in the LDLR Gene Impair Responsiveness to Rosuvastatin among Family Members of Patients with Premature Myocardial Infarction.
Nguyen Trung Kien et al. J Pers Med 2023 13(12) - Application of machine learning algorithms to construct and validate a prediction model for coronary heart disease risk in patients with periodontitis: a population-based study.
Yicheng Wang et al. Front Cardiovasc Med 2023 101296405 - Identification and risk stratification of coronary disease by artificial intelligence-enabled ECG.
Samir Awasthi et al. EClinicalMedicine 2023 65102259 - Familial risk of vasospastic angina: a nationwide family study in Sweden.
Fabrizio Ricci et al. Open Heart 2023 10(2) - Single-lead ECG AI model with risk factors detects Atrial Fibrillation during Sinus Rhythm.
Stijn Dupulthys et al. Europace 2023 - Machine learning for predicting intrahospital mortality in ST-elevation myocardial infarction patients with type 2 diabetes mellitus.
Panke Chen et al. BMC Cardiovasc Disord 2023 23(1) 585 - Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.
Meraj Neyazi et al. Clin Chem Lab Med 2023 - Familial hypercholesterolemia is related to cardiovascular disease, heart failure and atrial fibrillation. Results from a population-based study.
Hayato Tada et al. Eur J Clin Invest 2023 e14119 - Genetic and Nongenetic Components of Stroke Family History: A Population Study of Adopted and Nonadopted Individuals.
Ernst Mayerhofer et al. J Am Heart Assoc 2023 12(20) e031566 - Predicting Major Adverse Cardiovascular Events Following Carotid Endarterectomy Using Machine Learning.
Ben Li et al. J Am Heart Assoc 2023 e030508 - Predictive capacity of a genetic risk score for coronary artery disease in assessing recurrences and cardiovascular mortality among patients with myocardial infarction.
Luis Miguel Rincón et al. Front Cardiovasc Med 2023 101254066 - Comparison of machine-learning models for the prediction of 1-year adverse outcomes of patients undergoing primary percutaneous coronary intervention for acute ST-elevation myocardial infarction.
Saeed Tofighi et al. Clin Cardiol 2023 - A Systematic Review: Do the Use of Machine Learning, Deep Learning, and Artificial Intelligence Improve Patient Outcomes in Acute Myocardial Ischemia Compared to Clinician-Only Approaches?
Binay K Panjiyar et al. Cureus 2023 15(8) e43003 - Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study.
Yuhan Deng et al. JMIR Public Health Surveill 2023 9e47095 - A foundation model for generalizable disease detection from retinal images.
Yukun Zhou et al. Nature 2023 - Explainable SHAP-XGBoost models for in-hospital mortality after myocardial infarction.
Constantine Tarabanis et al. Cardiovasc Digit Health J 2023 4(4) 126-132 - Screening for Lipid Disorders in Children and Adolescents: US Preventive Services Task Force Recommendation Statement.
et al. JAMA 2023 330(3) 253-260 - Lipid Disorders in Children and Adolescents: Screening
USPSTF recommendation, July 18, 2023 - Acute Myocardial Infarction in Patients with Hereditary Thrombophilia-A Focus on Factor V Leiden and Prothrombin G20210A.
Minerva Codruta Badescu et al. Life (Basel) 2023 13(6) - Genetic and non-genetic components of family history of stroke and heart disease: a population-based study among adopted and non-adopted individuals.
Ernst Mayerhofer et al. medRxiv 2023 - Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction.
Salah S Al-Zaiti et al. Nat Med 2023 6 - Mendelian randomization evidence for the causal effects of socio-economic inequality on human longevity among Europeans.
Chao-Jie Ye et al. Nat Hum Behav 2023 - Assessing statins use in a real-world primary care digital strategy: a cross-sectional analysis of a population-wide digital health approach
MJM Carrion et al, Lancet Regional Health, June 22, 2023 - Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms.
Gregory Yoke Hong Lip et al. Intern Emerg Med 2023 1-11 - Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease.
Seong Huan Choi et al. BMC Cardiovasc Disord 2023 23(1) 287 - A novel breakthrough in wrist-worn transdermal troponin-I-sensor assessment for acute myocardial infarction.
Shantanu Sengupta et al. Eur Heart J Digit Health 2023 4(3) 145-154 - Coronary artery calcium among patients with heterozygous familial hypercholesterolaemia.
Hayato Tada et al. Eur Heart J Open 2023 3(3) oead046 - Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations.
Dimitrios Doudesis et al. Nat Med 2023 5 - Tumor Genomic Profile Is Associated With Arterial Thromboembolism Risk in Patients With Solid Cancer.
Stephanie Feldman et al. JACC CardioOncol 2023 5(2) 246-255 - Personalized diagnosis in suspected myocardial infarction.
Johannes Tobias Neumann et al. Clin Res Cardiol 2023 - Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program.
Jason L Vassy et al. JAMA Cardiol 2023 5 - Pompe disease ascertained through The Lantern Project, 2018-2021: Next-generation sequencing and enzymatic testing to overcome obstacles to diagnosis.
Lisa Sniderman King et al. Mol Genet Metab 139(1) 107565 - Machine learning prediction of mortality in Acute Myocardial Infarction.
Mariana Oliveira et al. BMC Med Inform Decis Mak 23(1) 70
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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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