2024
A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression
Oikonomou E, Holste G, Yuan N, Coppi A, McNamara R, Haynes N, Vora A, Velazquez E, Li F, Menon V, Kapadia S, Gill T, Nadkarni G, Krumholz H, Wang Z, Ouyang D, Khera R. A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression. JAMA Cardiology 2024, 9: 534-544. PMID: 38581644, PMCID: PMC10999005, DOI: 10.1001/jamacardio.2024.0595.Peer-Reviewed Original ResearchCardiac magnetic resonanceAortic valve replacementCardiac magnetic resonance imagingAV VmaxSevere ASAortic stenosisCohort studyPeak aortic valve velocityCohort study of patientsAortic valve velocityCohort of patientsTraditional cardiovascular risk factorsAssociated with faster progressionStudy of patientsCedars-Sinai Medical CenterAssociated with AS developmentCardiovascular risk factorsCardiovascular imaging modalitiesIndependent of ageModerate ASEjection fractionEchocardiographic studiesValve replacementRisk stratificationCardiac structureReal-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study
Oikonomou E, Aminorroaya A, Dhingra L, Partridge C, Velazquez E, Desai N, Krumholz H, Miller E, Khera R. Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study. European Heart Journal - Digital Health 2024, 5: 303-313. PMID: 38774380, PMCID: PMC11104476, DOI: 10.1093/ehjdh/ztae023.Peer-Reviewed Original ResearchRisk of acute myocardial infarctionAssociated with lower oddsHospital health systemCoronary artery diseaseCardiac testingRisk of adverse outcomesUK BiobankHealth systemProvider-drivenLower oddsAssociated with better outcomesAcute myocardial infarctionBlack raceStable chest painFemale sexReal world evaluationDiabetes historyMulticohort studyFunction testsSuspected coronary artery diseaseYounger ageRisk profileAdverse outcomesMultinational cohortPost hoc analysis
2023
Predicting aortic stenosis progression using a video-based deep learning model of aortic stenosis built for single-view two-dimensional echocardiography
Oikonomou E, Holste G, Mcnamara R, Velazquez E, Nadkarni G, Ouyang D, Krumholz H, Wang Z, Khera R. Predicting aortic stenosis progression using a video-based deep learning model of aortic stenosis built for single-view two-dimensional echocardiography. European Heart Journal 2023, 44: ehad655.040. DOI: 10.1093/eurheartj/ehad655.040.Peer-Reviewed Original ResearchLeft ventricular ejection fractionSevere aortic stenosisAortic stenosisAS progressionAV VmaxTransthoracic echocardiographyYale New Haven Health SystemBaseline left ventricular ejection fractionAortic stenosis progressionModerate aortic stenosisRetrospective cohort studyVentricular ejection fractionTwo-dimensional echocardiographyMean rateModerate ASAS severityCohort studyEjection fractionPatient sexStenosis progressionTTE studiesEligible participantsSerial monitoringSpecialized centersTimely diagnosisDetection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images
Sangha V, Nargesi A, Dhingra L, Khunte A, Mortazavi B, Ribeiro A, Banina E, Adeola O, Garg N, Brandt C, Miller E, Ribeiro A, Velazquez E, Giatti L, Barreto S, Foppa M, Yuan N, Ouyang D, Krumholz H, Khera R. Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images. Circulation 2023, 148: 765-777. PMID: 37489538, PMCID: PMC10982757, DOI: 10.1161/circulationaha.122.062646.Peer-Reviewed Original ResearchConceptsLV systolic dysfunctionYale-New Haven HospitalVentricular systolic dysfunctionSystolic dysfunctionLV ejection fractionBrazilian Longitudinal StudyNew Haven HospitalEjection fractionCardiology clinicRegional hospitalLeft ventricular systolic dysfunctionCedars-Sinai Medical CenterAdult Health (ELSA-Brasil) cohortMECHANISTIC EVALUATION OF AN AI-DRIVEN CLINICAL DECISION SUPPORT TOOL TO PERSONALIZE THE USE OF ANATOMICAL TESTING IN SUSPECTED CORONARY ARTERY DISEASE
Oikonomou E, Suchard M, Miller E, Velazquez E, Khera R. MECHANISTIC EVALUATION OF AN AI-DRIVEN CLINICAL DECISION SUPPORT TOOL TO PERSONALIZE THE USE OF ANATOMICAL TESTING IN SUSPECTED CORONARY ARTERY DISEASE. Journal Of The American College Of Cardiology 2023, 81: 1360. DOI: 10.1016/s0735-1097(23)01804-1.Peer-Reviewed Original Research