Prediction of sudden cardiac arrest in the general population: Review of traditional and emerging risk factors.
暂无分享,去创建一个
Douglas S. Lee | A. Ha | J. Tranmer | B. Doumouras | C. Wang
[1] Ritesh S. Patel,et al. Racial and Socioeconomic Disparities in Out-Of-Hospital Cardiac Arrest Outcomes: Artificial Intelligence-Augmented Propensity Score and Geospatial Cohort Analysis of 3,952 Patients , 2021, Cardiology research and practice.
[2] G. Collins,et al. Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review , 2021, BMJ.
[3] J. Schelling,et al. Ventricular arrhythmias in mouse models of diabetic kidney disease , 2021, Scientific Reports.
[4] J. Manson,et al. Healthy Sleep Patterns and Risk of Incident Arrhythmias. , 2021, Journal of the American College of Cardiology.
[5] N. Trayanova,et al. Artificial intelligence in the diagnosis and management of arrhythmias , 2021, European heart journal.
[6] K. Bailey,et al. Artificial Intelligence-Enabled Electrocardiography to Screen Patients with Dilated Cardiomyopathy. , 2021, The American journal of cardiology.
[7] T. Chan,et al. Socioeconomically equitable public defibrillator placement using mathematical optimization. , 2021, Resuscitation.
[8] K. Reinier,et al. Evaluation of Sudden Cardiac Arrest by Race/Ethnicity Among Residents of Ventura County, California, 2015-2020 , 2021, JAMA network open.
[9] J. Olgin,et al. Sudden Cardiac Death and Myocardial Fibrosis, Determined by Autopsy, in Persons with HIV. , 2021, The New England journal of medicine.
[10] V. Chinchilli,et al. Sudden death in individuals with obstructive sleep apnoea: a systematic review and meta-analysis , 2021, BMJ Open Respiratory Research.
[11] J. Holst,et al. Acute hypoglycemia and risk of cardiac arrhythmias in insulin-treated type 2 diabetes and controls , 2021, European journal of endocrinology.
[12] J. Newell,et al. Modelling the relationship between continuously measured glucose and electrocardiographic data in adults with type 1 diabetes mellitus , 2021, Endocrinology, diabetes & metabolism.
[13] Sanjiv J. Shah,et al. Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms , 2021, Nature communications.
[14] F. D’Ascenzi,et al. Novel Approaches in Cardiac Imaging for Non-invasive Assessment of Left Heart Myocardial Fibrosis , 2021, Frontiers in Cardiovascular Medicine.
[15] E. Nagel,et al. Myocardial Fibrosis and Inflammation by CMR Predict Cardiovascular Outcome in People Living With HIV. , 2021, JACC. Cardiovascular imaging.
[16] Yong-Yeon Jo,et al. Artificial intelligence for detecting electrolyte imbalance using electrocardiography , 2021, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.
[17] F. McAlister,et al. Machine-Learning, Predictive Analytics, and the Emperor's New Clothes: Why Artificial Intelligence hasn't yet Replaced Conventional Approaches. , 2021, The Canadian journal of cardiology.
[18] P. Austin,et al. MACHINE LEARNING COMPARED TO CONVENTIONAL STATISTICAL MODELS FOR PREDICTING MYOCARDIAL INFARCTION READMISSION AND MORTALITY: A SYSTEMATIC REVIEW. , 2021, The Canadian journal of cardiology.
[19] F. Gaita,et al. Left Posterior Fascicular Block and Increased Risk of Sudden Cardiac Death in Young People. , 2021, Journal of the American College of Cardiology.
[20] G. Adhikari,et al. Sudden Cardiac Death and Sudden Cardiac Arrest in Patients with Human Immunodeficiency Virus: A Systematic Review , 2021, Cureus.
[21] N. Trayanova,et al. Machine Learning in Arrhythmia and Electrophysiology. , 2021, Circulation research.
[22] Venkata A Narla. Sudden cardiac death in HIV‐infected patients: A contemporary review , 2021, Clinical cardiology.
[23] Fayzan F. Chaudhry,et al. Deep learning and the electrocardiogram: review of the current state-of-the-art , 2021, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.
[24] D. Bers,et al. Two-hit mechanism of cardiac arrhythmias in diabetic hyperglycemia: reduced repolarization reserve, neurohormonal stimulation and heart failure exacerbate susceptibility. , 2021, Cardiovascular research.
[25] S. Ozdemir,et al. Diabetes-induced changes in cardiac voltage-gated ion channels , 2021, World journal of diabetes.
[26] P. van der Harst,et al. Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology , 2020, Arrhythmia & electrophysiology review.
[27] Kipp W. Johnson,et al. Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management , 2020, Nature Reviews Cardiology.
[28] Richard A. Field,et al. Incidence of sudden cardiac death in the young: a systematic review , 2020, BMJ Open.
[29] Paul J. Wang,et al. Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology , 2020, Circulation. Arrhythmia and electrophysiology.
[30] D. Greer,et al. Brain injury after cardiac arrest: from prognostication of comatose patients to rehabilitation , 2020, The Lancet Neurology.
[31] D. Roden,et al. Genetic susceptibility for COVID-19–associated sudden cardiac death in African Americans , 2020, Heart Rhythm.
[32] T. Vilsbøll,et al. Hypoglycaemia and cardiac arrhythmias in diabetes , 2020, Therapeutic advances in endocrinology and metabolism.
[33] Han-Jeong Hwang,et al. Application of a convolutional neural network for predicting the occurrence of ventricular tachyarrhythmia using heart rate variability features , 2020, Scientific Reports.
[34] Antonio Pescapè,et al. Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG , 2020, Scientific Reports.
[35] C. Torp-Pedersen,et al. Sudden cardiac death among persons with diabetes aged 1–49 years: a 10-year nationwide study of 14 294 deaths in Denmark , 2019, European heart journal.
[36] Shihua Zhao,et al. A Novel Risk Stratification Score for Sudden Cardiac Death Prediction in Middle-Aged, Nonischemic Dilated Cardiomyopathy Patients: The ESTIMATED Score. , 2019, The Canadian journal of cardiology.
[37] Katherine C. Wu,et al. HIV Infection Is Associated With Variability in Ventricular Repolarization , 2019, Circulation.
[38] R. Altman,et al. Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis. , 2019, Circulation. Cardiovascular quality and outcomes.
[39] Rickey E Carter,et al. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction , 2019, The Lancet.
[40] Pashupati P. Mishra,et al. Cardiorespiratory fitness and heart rate recovery predict sudden cardiac death independent of ejection fraction , 2019, Heart.
[41] H. Tan,et al. Socio-economic differences in incidence, bystander cardiopulmonary resuscitation and survival from out-of-hospital cardiac arrest: A systematic review. , 2019, Resuscitation.
[42] Michael J Ackerman,et al. Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram. , 2019, JAMA cardiology.
[43] N. Sotoodehnia,et al. Racial Differences in Sudden Cardiac Death: Atherosclerosis Risk in Communities Study (ARIC) , 2019, Circulation.
[44] É. Marijon,et al. Ambulance Density and Outcomes After Out-of-Hospital Cardiac Arrest: Insights From the Paris Sudden Death Expertise Center Registry , 2019, Circulation.
[45] H. Huikuri,et al. Sudden Cardiac Death in Women: Causes of Death, Autopsy Findings, and Electrocardiographic Risk Markers , 2019, Circulation.
[46] K. Reinier,et al. Race, ethnicity, and the risk of sudden death. , 2019, Trends in cardiovascular medicine.
[47] L. Morrison,et al. Unexpected High Prevalence of Cardiovascular Disease Risk Factors and Psychiatric Disease Among Young People With Sudden Cardiac Arrest , 2019, Journal of the American Heart Association.
[48] K. Hickey,et al. Clinical Overview of Obesity and Diabetes Mellitus as Risk Factors for Atrial Fibrillation and Sudden Cardiac Death , 2019, Front. Physiol..
[49] Paul J. Wang,et al. New Concepts in Sudden Cardiac Arrest to Address an Intractable Epidemic: JACC State-of-the-Art Review. , 2019, Journal of the American College of Cardiology.
[50] Masoumeh Haghpanahi,et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network , 2019, Nature Medicine.
[51] Rickey E. Carter,et al. Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram , 2019, Nature Medicine.
[52] Geoffrey H. Tison,et al. Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery , 2018, Circulation. Cardiovascular quality and outcomes.
[53] M. Pabon,et al. Linking Arrhythmias and Adipocytes: Insights, Mechanisms, and Future Directions , 2018, Front. Physiol..
[54] D. Terentyev,et al. Proarrhythmic Remodeling of Calcium Homeostasis in Cardiac Disease; Implications for Diabetes and Obesity , 2018, Front. Physiol..
[55] Ruzena Bajcsy,et al. Fully Automated Echocardiogram Interpretation in Clinical Practice , 2018, Circulation.
[56] S. Rajagopalan,et al. Global Burden of Atherosclerotic Cardiovascular Disease in People Living With HIV: Systematic Review and Meta-Analysis , 2018, Circulation.
[57] H. K. Fong,et al. A QS pattern in leads V1 and V2 is associated with septal scarring independent of scar etiology - A cardiac magnetic resonance imaging study. , 2018, Journal of electrocardiology.
[58] J. Olgin,et al. Prospective Countywide Surveillance and Autopsy Characterization of Sudden Cardiac Death: POST SCD Study , 2018, Circulation.
[59] E. Riboli,et al. Diabetes mellitus and the risk of sudden cardiac death: A systematic review and meta-analysis of prospective studies. , 2018, Nutrition, metabolism, and cardiovascular diseases : NMCD.
[60] P. Sengupta,et al. Prediction of Abnormal Myocardial Relaxation From Signal Processed Surface ECG. , 2018, Journal of the American College of Cardiology.
[61] Aung Myat,et al. Out-of-hospital cardiac arrest: current concepts , 2018, The Lancet.
[62] K. Reinier,et al. Risk Factors of Sudden Cardiac Death in the Young: Multiple-Year Community-Wide Assessment , 2017, Circulation.
[63] R. Myerburg. Sudden Cardiac Death: Interface Between Pathophysiology and Epidemiology. , 2017, Cardiac electrophysiology clinics.
[64] K. Reinier,et al. Electrical risk score beyond the left ventricular ejection fraction: prediction of sudden cardiac death in the Oregon Sudden Unexpected Death Study and the Atherosclerosis Risk in Communities Study , 2017, European heart journal.
[65] D. Bluemke,et al. Electrocardiographic Strain Pattern Is Associated With Left Ventricular Concentric Remodeling, Scar, and Mortality Over 10 Years: The Multi‐Ethnic Study of Atherosclerosis , 2017, Journal of the American Heart Association.
[66] Xue-qin Wang,et al. The association of long-term glycaemic variability versus sustained chronic hyperglycaemia with heart rate-corrected QT interval in patients with type 2 diabetes , 2017, PloS one.
[67] D. Mark,et al. The Metabolic Syndrome and Risk of Sudden Cardiac Death: The Atherosclerosis Risk in Communities Study , 2017, Journal of the American Heart Association.
[68] Timothy C. Y. Chan,et al. Optimizing a Drone Network to Deliver Automated External Defibrillators , 2017, Circulation.
[69] J. Goldberger,et al. Sudden Cardiac Arrest Risk Assessment: Population Science and the Individual Risk Mandate , 2017, JAMA cardiology.
[70] Michela Masè,et al. Myocardial Fibrosis Assessment by LGE Is a Powerful Predictor of Ventricular Tachyarrhythmias in Ischemic and Nonischemic LV Dysfunction: A Meta-Analysis. , 2016, JACC. Cardiovascular imaging.
[71] Segyeong Joo,et al. Prediction of Ventricular Tachycardia One Hour before Occurrence Using Artificial Neural Networks , 2016, Scientific Reports.
[72] J. Skinner,et al. A Prospective Study of Sudden Cardiac Death among Children and Young Adults. , 2016, The New England journal of medicine.
[73] Rik Willems,et al. Which QT Correction Formulae to Use for QT Monitoring? , 2016, Journal of the American Heart Association.
[74] B. Firwana,et al. Effect of obesity and weight loss on ventricular repolarization: a systematic review and meta‐analysis , 2016, Obesity reviews : an official journal of the International Association for the Study of Obesity.
[75] K. Reinier,et al. Occupation and risk of sudden death in a United States community: a case–control analysis , 2015, BMJ Open.
[76] C. Albert,et al. Sudden cardiac death in young adults with previous hospital-based psychiatric inpatient and outpatient treatment: a nationwide cohort study from Denmark. , 2015, The Journal of clinical psychiatry.
[77] K. Reinier,et al. Clinical Perspective on P 387 Methods Study Population , 2022 .
[78] P. Austin,et al. Clinical Risk Stratification for Primary Prevention Implantable Cardioverter Defibrillators , 2015, Circulation. Heart failure.
[79] L. Chen,et al. Obesity related risk of sudden cardiac death in the atherosclerosis risk in communities study , 2014, Heart.
[80] G. Steinbeck,et al. Incidence of sudden cardiac death in Germany: results from an emergency medical service registry in Lower Saxony , 2014, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.
[81] É. Marijon,et al. Public Health Burden of Sudden Cardiac Death in the United States , 2014, Circulation. Arrhythmia and electrophysiology.
[82] E. Behr,et al. Burden of Sudden Cardiac Death in Persons Aged 1 to 49 Years: Nationwide Study in Denmark , 2014, Circulation. Arrhythmia and electrophysiology.
[83] N. McCartney,et al. Scope and nature of sudden cardiac death before age 40 in Ontario: a report from the cardiac death advisory committee of the office of the chief coroner. , 2013, Heart rhythm.
[84] Elsayed Z Soliman,et al. Atrial fibrillation and the risk of sudden cardiac death: the atherosclerosis risk in communities study and cardiovascular health study. , 2013, JAMA internal medicine.
[85] Lewis H Kuller,et al. Risk factors for sudden cardiac death in post-menopausal women. , 2012, Journal of the American College of Cardiology.
[86] K. Maeda,et al. Trends in sudden cardiac death and its risk factors in Japan from 1981 to 2005: the Circulatory Risk in Communities Study (CIRCS) , 2012, BMJ Open.
[87] E. Vittinghoff,et al. Characteristics of sudden arrhythmic death in a diverse, urban community. , 2012, American heart journal.
[88] E. Vittinghoff,et al. Risk factor and prediction modeling for sudden cardiac death in women with coronary artery disease. , 2011, Archives of internal medicine.
[89] Eric A. Shry,et al. Sudden death in young adults: an autopsy-based series of a population undergoing active surveillance. , 2011, Journal of the American College of Cardiology.
[90] Yiyi Zhang,et al. Electrocardiographic QT Interval and Mortality: A Meta-analysis , 2011, Epidemiology.
[91] Yibo Wang,et al. Patients with Metabolic Syndrome Have Prolonged Corrected QT Interval (QTc) , 2009, Clinical cardiology.
[92] K. Reinier,et al. Women have a lower prevalence of structural heart disease as a precursor to sudden cardiac arrest: The Ore-SUDS (Oregon Sudden Unexpected Death Study). , 2009, Journal of the American College of Cardiology.
[93] Shu Zhang,et al. Incidence of sudden cardiac death in China: analysis of 4 regional populations. , 2009, Journal of the American College of Cardiology.
[94] J. Struijk,et al. A Physiological Model of the Effect of Hypoglycemia on Plasma Potassium , 2009, Journal of diabetes science and technology.
[95] J. Tu,et al. Ecological Studies and Cardiovascular Outcomes Research , 2008, Circulation.
[96] A. Hofman,et al. Prolonged QTc interval and risk of sudden cardiac death in a population of older adults. , 2006, Journal of the American College of Cardiology.
[97] Renu Virmani,et al. Role of SCN5A Y1102 Polymorphism in Sudden Cardiac Death in Blacks , 2005, Circulation.
[98] Peter W Macfarlane,et al. A comparison of commonly used QT correction formulae: the effect of heart rate on the QTc of normal ECGs. , 2004, Journal of electrocardiology.
[99] J van der Lei,et al. The incidence of sudden cardiac death in the general population. , 2004, Journal of clinical epidemiology.
[100] K. Greenlund,et al. Impaired Fasting Glucose, Diabetes Mellitus, and Cardiovascular Disease Risk Factors are Associated with Prolonged QTc Duration. Results from the Third National Health and Nutrition Examination Survey , 2001, Journal of cardiovascular risk.
[101] C Guérot,et al. Resting heart rate as a predictive risk factor for sudden death in middle-aged men. , 2001, Cardiovascular research.
[102] R. D'Agostino,et al. Sudden coronary death in women. , 1998, American heart journal.
[103] Sawicki,et al. The value of QT interval dispersion for identification of total mortality risk in non‐insulin‐dependent diabetes mellitus , 1998, Journal of internal medicine.
[104] K M Kessler,et al. Frequency of sudden cardiac death and profiles of risk. , 1997, The American journal of cardiology.
[105] E. Gilat,et al. Delayed Afterdepolarizations and Triggered Activit in Ventricular Muscle from Rats with Streptozotocin‐Induced Diabetes , 1985, Circulation research.
[106] Manning Feinleib,et al. Obesity as an Independent Risk Factor for Cardiovascular Disease: A 26‐year Follow‐up of Participants in the Framingham Heart Study , 1983, Circulation.