2025
Transforming Population Health Screening for Atherosclerotic Cardiovascular Disease with AI-Enhanced ECG Analytics: Opportunities and Challenges
Biswas D, Aminorroaya A, Croon P, Batinica B, Pedroso A, Khera R. Transforming Population Health Screening for Atherosclerotic Cardiovascular Disease with AI-Enhanced ECG Analytics: Opportunities and Challenges. Current Atherosclerosis Reports 2025, 27: 86. PMID: 40888973, DOI: 10.1007/s11883-025-01337-4.Peer-Reviewed Original ResearchConceptsAtherosclerotic cardiovascular diseasePopulation health screeningPopulation-level screeningCardiovascular diseaseLow riskHealth screeningStandard risk factorsHospital-basedCardiovascular healthSubclinical coronary artery diseaseWorkflow integrationSingle-lead ECGPersonalized interventionsPatient outcomesDiverse populationsTraditional risk modelsECG interpretationRisk factorsAscertainment biasImplementation challengesAdverse cardiovascular eventsProspective studyLogistical challengesRe-classifying patientsCoronary artery diseaseScientific Writing in the Era of Large Language Models: A Computational Analysis of AI- Versus Human-Created Content
Khera R, Pedroso A, Keloth V, Xu H, Silva G, Schwamm L. Scientific Writing in the Era of Large Language Models: A Computational Analysis of AI- Versus Human-Created Content. Stroke 2025, 56: 3078-3083. PMID: 40814778, DOI: 10.1161/strokeaha.125.051913.Peer-Reviewed Original ResearchConceptsLanguage modelArtificial intelligenceAI-generatedLinguistic featuresDetection toolsAI-generated contentHuman-written textLanguage perplexityHuman expertsPerformance of expertsLinguistic differencesScientific textsGrade levelWord countEssayLanguageScientific communicationScientific writingComputer synthesisHigher grade levelsTextScientific contentReadability scoresPerplexityFlesch-KincaidChanges in Cardiovascular Risk Factors and Health Care Expenditures Among Patients Prescribed Semaglutide
Lu Y, Liu Y, Totojani T, Kim C, Khera R, Xu H, Brush J, Krumholz H, Abaluck J. Changes in Cardiovascular Risk Factors and Health Care Expenditures Among Patients Prescribed Semaglutide. JAMA Network Open 2025, 8: e2526013. PMID: 40779264, PMCID: PMC12334959, DOI: 10.1001/jamanetworkopen.2025.26013.Peer-Reviewed Original ResearchConceptsHealth care expendituresCardiovascular risk factorsCare expendituresCohort studyRisk factorsYale New Haven Health SystemCohort study of adultsType 2 diabetes statusLong-term impactStudy of adultsHealth systemRetrospective cohort studyBlood pressureHemoglobin A1c reductionMain OutcomesTotal cholesterolSentara HealthcareInpatient staySecondary outcomesGlucagon-like peptide-1 receptor agonistsPrimary outcomeHealthPeptide-1 receptor agonistsAssociated with clinical outcomesAssociated with reductionsIdentification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning
Sangha V, Dhingra L, Aminorroaya A, Croon P, Sikand N, Sen S, Martinez M, Maron M, Krumholz H, Asselbergs F, Oikonomou E, Khera R. Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning. Nature Cardiovascular Research 2025, 4: 991-1000. PMID: 40696040, DOI: 10.1038/s44161-025-00685-3.Peer-Reviewed Original ResearchCardiac magnetic resonance markers of pre-clinical hypertrophic and dilated cardiomyopathy in genetic variant carriers
Croon P, van Vugt M, Allaart C, Ruijsink B, Elliott P, Asselbergs F, Khera R, Bezzina C, Winter M, Schmidt A. Cardiac magnetic resonance markers of pre-clinical hypertrophic and dilated cardiomyopathy in genetic variant carriers. BMC Medicine 2025, 23: 421. PMID: 40660250, PMCID: PMC12261545, DOI: 10.1186/s12916-025-04226-4.Peer-Reviewed Original ResearchConceptsCardiac magnetic resonance imagingCardiac magnetic resonance imaging measuresCardiac magnetic resonance markersDilated CardiomyopathyHypertrophic cardiomyopathyHeart failureUK Biobank participantsAtrial fibrillationLeft ventricular (LV) ejection fractionMitral annular plane systolic excursionAnnular plane systolic excursionLV) ejection fractionFunctional cardiac abnormalitiesEnd-systolic volumeCardiac risk factorsCardiomyopathy-associated variantsAssociated with incident AFAssociated with TTNIncident atrial fibrillationLV-ESVIMagnetic resonance imagingRV-ESVRV EFGenetic variant carriersSystolic excursionA Novel Sentence Transformer-based Natural Language Processing Approach for Schema Mapping of Electronic Health Records to the OMOP Common Data Model.
Zhou X, Dhingra L, Aminorroaya A, Adejumo P, Khera R. A Novel Sentence Transformer-based Natural Language Processing Approach for Schema Mapping of Electronic Health Records to the OMOP Common Data Model. AMIA Annual Symposium Proceedings 2025, 2024: 1332-1339. PMID: 40417570.Peer-Reviewed Original ResearchConceptsCommon data modelElectronic health recordsOMOP Common Data ModelSchema mappingsMapping electronic health recordData modelTransformer-based deep learning modelsNatural language processing approachEnd-to-endDeep learning modelsHealth recordsEnhance interoperabilityTransformation pipelineLearning modelsOMOPProcessing approachSchemaStandard conceptsDiverse healthcare systemsInteroperabilityLarge-scaleStandard mapDatasetSoftwareHealthcare systemComputational Phenomapping of Randomized Clinical Trial Participants to Enable Assessment of Their Real-World Representativeness and Personalized Inference
Thangaraj P, Oikonomou E, Dhingra L, Aminorroaya A, Jayaram R, Suchard M, Khera R. Computational Phenomapping of Randomized Clinical Trial Participants to Enable Assessment of Their Real-World Representativeness and Personalized Inference. Circulation Cardiovascular Quality And Outcomes 2025, 18: e011306. PMID: 40261065, PMCID: PMC12203226, DOI: 10.1161/circoutcomes.124.011306.Peer-Reviewed Original ResearchConceptsElectronic health record patientElectronic health recordsDistance metricRandomized clinical trialsElectronic health record dataMachine learning methodsYale New Haven Health SystemElectronic health record cohortRandomized clinical trial participantsLearning methodsHeart failureClinical trial participationTOPCAT participantsReal worldMultidimensional metricRCT participantsHealth recordsTreatment effectsHealth systemCharacteristics of patientsRandomized clinical trial cohortsTrial participantsMetricsUnited StatesNovel statisticEnsemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images PRESENT SHD
Dhingra L, Aminorroaya A, Sangha V, Pedroso A, Shankar S, Coppi A, Foppa M, Brant L, Barreto S, Ribeiro A, Krumholz H, Oikonomou E, Khera R. Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images PRESENT SHD. Journal Of The American College Of Cardiology 2025, 85: 1302-1313. PMID: 40139886, PMCID: PMC12199746, DOI: 10.1016/j.jacc.2025.01.030.Peer-Reviewed Original ResearchConceptsStructural heart diseaseYale-New Haven HospitalTransthoracic echocardiogramRisk stratificationHeart failureLeft-sided valvular diseaseSevere left ventricular hypertrophyLeft ventricular ejection fractionReceiver-operating characteristic curveVentricular ejection fractionLeft ventricular hypertrophyHeart disease screeningELSA-BrasilEnsemble deep learning algorithmRisk of deathConvolutional neural network modelEjection fractionEnsemble deep learning approachVentricular hypertrophyDeep learning algorithmsNew Haven HospitalDeep learning approachValvular diseaseNeural network modelClinical cohortUso da Inteligência Artificial Aplicada ao Eletrocardiograma para Diagnóstico de Disfunção Sistólica Ventricular Esquerda
de Santana W, Pinto M, Barreto S, Foppa M, Giatti L, Khera R, Ribeiro A. Uso da Inteligência Artificial Aplicada ao Eletrocardiograma para Diagnóstico de Disfunção Sistólica Ventricular Esquerda. Arquivos Brasileiros De Cardiologia 2025, 122: e20240740. PMID: 40396866, PMCID: PMC12108124, DOI: 10.36660/abc.20240740.Peer-Reviewed Original ResearchConceptsLeft ventricular systolic dysfunctionLeft ventricular ejection fractionNegative predictive valueDiagnostic odds ratioPositive predictive valueHeart failureDetect left-ventricular systolic dysfunctionPredictive valueVentricular systolic dysfunctionVentricular ejection fractionNegative likelihood ratioPositive likelihood ratioDiagnostic accuracy cross-sectional studyLikelihood ratioCross-sectional studySystolic dysfunctionEjection fractionEvaluating HFAUC-ROCElectrocardiographic alterationsOdds ratioEchocardiogramROC curveScreening toolElectrocardiogramEffects of Tirzepatide in Type 2 Diabetes Individual Variation and Relationship to Cardiometabolic Outcomes
Aminorroaya A, Oikonomou E, Biswas D, Jastreboff A, Khera R. Effects of Tirzepatide in Type 2 Diabetes Individual Variation and Relationship to Cardiometabolic Outcomes. Journal Of The American College Of Cardiology 2025, 85: 1858-1872. PMID: 40368575, PMCID: PMC12186526, DOI: 10.1016/j.jacc.2025.03.516.Peer-Reviewed Original ResearchConceptsElevated body mass indexCardiometabolic abnormalitiesBody mass indexOdds of elevated body mass indexType 2 diabetesIndividual Participant Data Meta-AnalysisMass indexParticipant data meta-analysisOdds of MetSCardiometabolic risk factorsComponents of metabolic syndromeData Meta-AnalysisHigh-density lipoprotein cholesterolCardiometabolic healthStudy design differencesMixed-effects modelsBaseline usePhase 3 randomized clinical trialSodium-glucose cotransporter 2 inhibitorsOddsStudy outcomesEffects of tirzepatideMeta-analysisRisk factorsClinical subpopulationsControversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management
Armoundas A, Ahmad F, Attia Z, Doudesis D, Khera R, Kyriakoulis K, Stergiou G, Tang W. Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management. Hypertension 2025, 82: 929-944. PMID: 40091745, PMCID: PMC12094096, DOI: 10.1161/hypertensionaha.124.22349.Peer-Reviewed Original ResearchConceptsArtificial intelligenceHypertension diagnosisBlood pressure elevationRelationship to cardiovascular diseaseManagement of hypertensionLong-term managementArtificial intelligence-based solutionsPressure elevationPublic health challengeHypertensionArtificial intelligence scienceComplex pathogenesisClinical implementationCardiovascular diseaseState-of-artDiagnosisData-driven approachHypertension managementIntelligence scienceClinical adoptionArtificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association
Khera R, Asnani A, Krive J, Addison D, Zhu H, Vasbinder A, Fleming M, Arnaout R, Razavi P, Okwuosa T, Nursing O. Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association. Circulation Genomic And Precision Medicine 2025, 18: e000097. PMID: 39989357, PMCID: PMC12316026, DOI: 10.1161/hcg.0000000000000097.Peer-Reviewed Original ResearchConceptsCardiovascular riskLong-term cardiovascular riskImmune checkpoint inhibitorsRisk of cardiovascular diseaseBiomarkers of riskCardio-oncology careHeightened risk of cardiovascular diseasePrevalence of cancerCheckpoint inhibitorsAmerican Heart AssociationCardiovascular risk managementTargeted therapyTherapeutic optionsCancer groupNovel therapiesHeightened riskHeart AssociationCardio-OncologyEnhancing precision medicineAdvanced imagingCardiovascular diseaseCancerDiagnostic testsTherapyPatientsArtificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study
Oikonomou E, Vaid A, Holste G, Coppi A, McNamara R, Baloescu C, Krumholz H, Wang Z, Apakama D, Nadkarni G, Khera R. Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study. The Lancet Digital Health 2025, 7: e113-e123. PMID: 39890242, PMCID: PMC12084816, DOI: 10.1016/s2589-7500(24)00249-8.Peer-Reviewed Original ResearchConceptsYale New Haven Health SystemPoint-of-care ultrasonographyMount Sinai Health SystemTransthyretin amyloid cardiomyopathyArtificial intelligenceHealth systemAmyloid cardiomyopathyHypertrophic cardiomyopathyRetrospective cohort of individualsCardiomyopathy casesTesting artificial intelligenceConvolutional neural networkSinai Health SystemCohort of individualsOpportunistic screeningHypertrophic cardiomyopathy casesMulti-labelPositive screenAI frameworkEmergency departmentMortality riskNeural networkLoss functionCardiac ultrasonographyAugmentation approachEvaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems
Aminorroaya A, Dhingra L, Oikonomou E, Khera R. Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems. Circulation Genomic And Precision Medicine 2025, 18: e004632. PMID: 39846171, PMCID: PMC11835527, DOI: 10.1161/circgen.124.004632.Peer-Reviewed Original ResearchConceptsYale New Haven Health SystemHealth systemVanderbilt University Medical CenterHealth system electronic health recordUniversity Medical CenterCoronary Artery Risk DevelopmentMulti-Ethnic Study of AtherosclerosisElectronic health recordsMedical CenterUS health systemHealth system patientsAssociated with significantly higher oddsMulti-Ethnic StudyUS-based cohortStudy of atherosclerosisSignificantly higher oddsHealth recordsUK BiobankAtherosclerosis RiskRisk DevelopmentHigher oddsElevated Lp(aUniversal screeningSystem patientsStudy cohort
2024
Impact of the COVID-19 pandemic on hospital-based heart failure care in New South Wales, Australia: a linked data cohort study
McIntyre D, Quintans D, Kazi S, Min H, He W, Marschner S, Khera R, Nassar N, Chow C. Impact of the COVID-19 pandemic on hospital-based heart failure care in New South Wales, Australia: a linked data cohort study. BMC Health Services Research 2024, 24: 1364. PMID: 39516863, PMCID: PMC11545568, DOI: 10.1186/s12913-024-11840-0.Peer-Reviewed Original ResearchConceptsHeart failure careNew South WalesHospital admissionHealth service utilisationAdministrative health recordsPrimary diagnosis of heart failureData cohort studyRate of admissionPre-pandemicHealth of patientsSouth WalesCOVID-19 pandemicHospital utilisationService utilisationHealth recordsED presentationsMortality dataDiagnosis of heart failureCOVID-19 burdenEmergency departmentCohort studyPrimary diagnosisData collectionCareAustralian dataNatural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure
Adejumo P, Thangaraj P, Dhingra L, Aminorroaya A, Zhou X, Brandt C, Xu H, Krumholz H, Khera R. Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure. JAMA Network Open 2024, 7: e2443925. PMID: 39509128, PMCID: PMC11544492, DOI: 10.1001/jamanetworkopen.2024.43925.Peer-Reviewed Original ResearchConceptsFunctional status assessmentArea under the receiver operating characteristic curveClinical documentationElectronic health record dataHF symptomsOptimal care deliveryHealth record dataAssess functional statusStatus assessmentClinical trial participationProcessing of clinical documentsFunctional status groupCare deliveryOutpatient careMain OutcomesMedical notesTrial participantsNew York Heart AssociationFunctional statusQuality improvementRecord dataHeart failureClinical notesDiagnostic studiesStatus groupsRacial and Ethnic Disparities in Age-Specific All-Cause Mortality During the COVID-19 Pandemic
Faust J, Renton B, Bongiovanni T, Chen A, Sheares K, Du C, Essien U, Fuentes-Afflick E, Haywood T, Khera R, King T, Li S, Lin Z, Lu Y, Marshall A, Ndumele C, Opara I, Loarte-Rodriguez T, Sawano M, Taparra K, Taylor H, Watson K, Yancy C, Krumholz H. Racial and Ethnic Disparities in Age-Specific All-Cause Mortality During the COVID-19 Pandemic. JAMA Network Open 2024, 7: e2438918. PMID: 39392630, PMCID: PMC11581672, DOI: 10.1001/jamanetworkopen.2024.38918.Peer-Reviewed Original ResearchConceptsCOVID-19 public health emergencyNon-HispanicPublic health emergencyOther Pacific IslanderExcess mortalityAlaska NativesUS populationExcess deathsRates of excess mortalityCross-sectional study analyzed dataYears of potential lifeMortality relative riskNon-Hispanic whitesCross-sectional studyPacific IslandersStudy analyzed dataAll-Cause MortalityEthnic groupsMortality disparitiesMortality ratioTotal populationDeath certificatesEthnic disparitiesMain OutcomesDecedent ageReviewer Experience Detecting and Judging Human Versus Artificial Intelligence Content: The Stroke Journal Essay Contest
Silva G, Khera R, Schwamm L, Acampa M, Adelman E, Boltze J, Broderick J, Brodtmann A, Christensen H, Dalli L, Duncan K, Elgendy I, Ergul A, Goldstein L, Hinkle J, Johansen M, Jood K, Kasner S, Levine S, Li Z, Lip G, Marsh E, Muir K, Ospel J, Pera J, Quinn T, Räty S, Ranta A, Richards L, Romero J, Willey J, Hillis A, Veerbeek J. Reviewer Experience Detecting and Judging Human Versus Artificial Intelligence Content: The Stroke Journal Essay Contest. Stroke 2024, 55: 2573-2578. PMID: 39224979, PMCID: PMC11529699, DOI: 10.1161/strokeaha.124.045012.Peer-Reviewed Original ResearchConceptsArtificial intelligenceEditorial board membersAuthor typeTraditional peer reviewLanguage modelIntelligent contentAuthor attributionGeneral textAI expertiseHuman authorityImproved accuracyAuthor's identityAuthor's manuscriptScientific journalsEssay contestPeer reviewPerception of qualityAuthorshipNature of authorshipIntelligenceLLMScientific writingScientific essayEssay qualityEssayCause-Specific Mortality Rates Among the US Black Population
Arun A, Caraballo C, Sawano M, Lu Y, Khera R, Yancy C, Krumholz H. Cause-Specific Mortality Rates Among the US Black Population. JAMA Network Open 2024, 7: e2436402. PMID: 39348122, PMCID: PMC11443349, DOI: 10.1001/jamanetworkopen.2024.36402.Commentaries, Editorials and LettersComparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes A Multinational, Federated Analysis of LEGEND-T2DM
Khera R, Aminorroaya A, Dhingra L, Thangaraj P, Pedroso Camargos A, Bu F, Ding X, Nishimura A, Anand T, Arshad F, Blacketer C, Chai Y, Chattopadhyay S, Cook M, Dorr D, Duarte-Salles T, DuVall S, Falconer T, French T, Hanchrow E, Kaur G, Lau W, Li J, Li K, Liu Y, Lu Y, Man K, Matheny M, Mathioudakis N, McLeggon J, McLemore M, Minty E, Morales D, Nagy P, Ostropolets A, Pistillo A, Phan T, Pratt N, Reyes C, Richter L, Ross J, Ruan E, Seager S, Simon K, Viernes B, Yang J, Yin C, You S, Zhou J, Ryan P, Schuemie M, Krumholz H, Hripcsak G, Suchard M. Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes A Multinational, Federated Analysis of LEGEND-T2DM. Journal Of The American College Of Cardiology 2024, 84: 904-917. PMID: 39197980, PMCID: PMC12045554, DOI: 10.1016/j.jacc.2024.05.069.Peer-Reviewed Original ResearchConceptsGLP-1 RAsSecond-line agentsGLP-1Antihyperglycemic agentsCardiovascular diseaseMACE riskGlucagon-like peptide-1 receptor agonistsSodium-glucose cotransporter 2 inhibitorsPeptide-1 receptor agonistsDipeptidyl peptidase-4 inhibitorsEffects of SGLT2isType 2 diabetes mellitusPeptidase-4 inhibitorsAdverse cardiovascular eventsCox proportional hazards modelsRandom-effects meta-analysisCardiovascular risk reductionTarget trial emulationProportional hazards model
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