2025
Phenotypic Selectivity of Artificial Intelligence-enhanced Electrocardiography in Cardiovascular Diagnosis and Risk Prediction.
Croon P, Dhingra L, Biswas D, Oikonomou E, Khera R. Phenotypic Selectivity of Artificial Intelligence-enhanced Electrocardiography in Cardiovascular Diagnosis and Risk Prediction. Circulation 2025 PMID: 40888124, DOI: 10.1161/circulationaha.125.076279.Peer-Reviewed Original ResearchElectronic health recordsNon-cardiovascular conditionsPhenome-wide association studyCross-sectional phenotypingNew-onset cardiovascular diseaseCardiovascular diseaseProspective cohort studyPhenotypic associationsHealth recordsLeft ventricular hypertrophyStructural heart diseaseAI-ECGAssociated with cardiovascular phenotypesPearson correlation coefficientDiagnosis codesCohort studyCardiovascular risk markersLogistic regressionAssociation studiesCardiovascular diagnosisMitral regurgitationAortic stenosisCardiovascular conditionsStudy populationDetection of LVSDPredictors of Right Ventricular Pacing in Patients Undergoing Implantable Defibrillator Placement
Hummel J, Lan Z, Jones P, Khera R, Stein K, Curtis J, Akar J. Predictors of Right Ventricular Pacing in Patients Undergoing Implantable Defibrillator Placement. Journal Of Cardiovascular Electrophysiology 2025, 36: 807-812. PMID: 39930894, DOI: 10.1111/jce.16570.Peer-Reviewed Original ResearchRV pacingICD implantationCardiac arrestRight ventricular (RV) pacingICD recipientsHistory of syncopeHistory of VTHistory of AFRight ventricular pacingPacing indicationsDefibrillator placementQRS durationValidation cohortICD RegistryVentricular tachycardiaBUN levelsPacing needsClinical indicationsVentricular pacingPatientsStudy populationTransvenous defibrillationDual chamberLogistic regressionSubcutaneous devices
2021
A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST)
Oikonomou EK, Van Dijk D, Parise H, Suchard MA, de Lemos J, Antoniades C, Velazquez EJ, Miller EJ, Khera R. A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST). European Heart Journal 2021, 42: 2536-2548. PMID: 33881513, PMCID: PMC8488385, DOI: 10.1093/eurheartj/ehab223.Peer-Reviewed Original ResearchConceptsStable chest painChest painPrimary endpointMajor adverse cardiovascular eventsNon-fatal myocardial infarctionAdverse cardiovascular eventsStudy's primary endpointCoronary artery diseaseClinical trial populationsCox regression modelParticipant-level dataSCOT-HEARTCardiovascular eventsCause mortalityHazard ratioPatients 5Artery diseaseFunctional testingPROMISE trialTrial populationMyocardial infarctionLower incidenceStudy populationPainCollected variables
2020
Association Between Sociodemographic Determinants and Disparities in Stroke Symptom Awareness Among US Young Adults
Mszar R, Mahajan S, Valero-Elizondo J, Yahya T, Sharma R, Grandhi GR, Khera R, Virani SS, Lichtman J, Khan SU, Cainzos-Achirica M, Vahidy FS, Krumholz HM, Nasir K. Association Between Sociodemographic Determinants and Disparities in Stroke Symptom Awareness Among US Young Adults. Stroke 2020, 51: 3552-3561. PMID: 33100188, DOI: 10.1161/strokeaha.120.031137.Peer-Reviewed Original ResearchConceptsNational Health Interview SurveyCommon stroke symptomsStroke symptomsHealth Interview SurveyYoung adultsUS young adultsSymptom awarenessFocused public health interventionsInterview SurveyStroke symptom awarenessHigh-risk characteristicsPublic health interventionsArms/legsCertain sociodemographic subgroupsLow education levelStroke incidenceSevere headacheSingle symptomStudy populationTimely diagnosisHigher oddsStroke rateHispanic ethnicityGeneral populationSociodemographic determinantsAssociation of cardiovascular risk factor profile and financial hardship from medical bills among non-elderly adults in the United States
Grandhi GR, Valero-Elizondo J, Mszar R, Brandt EJ, Annapureddy A, Khera R, Saxena A, Virani SS, Blankstein R, Desai NR, Blaha MJ, Cheema FH, Vahidy FS, Nasir K. Association of cardiovascular risk factor profile and financial hardship from medical bills among non-elderly adults in the United States. American Journal Of Preventive Cardiology 2020, 2: 100034. PMID: 34327457, PMCID: PMC8315456, DOI: 10.1016/j.ajpc.2020.100034.Peer-Reviewed Original ResearchAtherosclerotic cardiovascular diseaseCardiovascular risk factor profileCost-related barriersRisk factor profileNon-elderly adultsCRF profileLow prevalenceMedical billsFactor profileNational Health Interview SurveyHealth Interview SurveyLack of insuranceFinancial hardshipLogistic regression modelsLow incomeASCVD statusRisk factorsCardiovascular diseaseStudy populationLower oddsLower mortalityUninsured individualsLow burdenHealthcare expendituresPrevalenceCumulative Burden of Financial Hardship From Medical Bills Across the Spectrum of Diabetes Mellitus and Atherosclerotic Cardiovascular Disease Among Non‐Elderly Adults in the United States
Mszar R, Grandhi GR, Valero‐Elizondo J, Caraballo C, Khera R, Desai N, Virani SS, Blankstein R, Blaha MJ, Nasir K. Cumulative Burden of Financial Hardship From Medical Bills Across the Spectrum of Diabetes Mellitus and Atherosclerotic Cardiovascular Disease Among Non‐Elderly Adults in the United States. Journal Of The American Heart Association 2020, 9: e015523. PMID: 32394783, PMCID: PMC7660844, DOI: 10.1161/jaha.119.015523.Peer-Reviewed Original ResearchConceptsAtherosclerotic cardiovascular diseaseDiabetes mellitusNon-elderly adultsMedical billsCardiovascular diseaseBackground Atherosclerotic cardiovascular diseaseNational Health Interview SurveyEffective public health policiesThird of deathsTreatment-related expensesHealth Interview SurveyHigher relative oddsLogistic regression analysisFinancial hardshipPublic health policyASCVD statusPatient populationStudy populationHigh riskRelative oddsWeighted populationCumulative burdenHealth policyInterview SurveyStrong association
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