2025
Cardiac 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 excursionArtificial Intelligence in the Management of Heart Failure
Cheema B, Hourmozdi J, Kline A, Ahmad F, Khera R. Artificial Intelligence in the Management of Heart Failure. Journal Of Cardiac Failure 2025 PMID: 40345521, DOI: 10.1016/j.cardfail.2025.02.020.Peer-Reviewed Original ResearchArtificial intelligenceState-of-the-art algorithmsData privacy concernsState-of-the-artManagement of heart failureAI-based toolsElectronic health recordsAI solutionsMultimodal dataHeart failureHealth recordsIntegration challengesHeart failure syndromeStructural heart diseaseHeart failure treatmentIntelligenceImplementation challengesModel performanceModel governanceAdvanced diseaseFailure syndromeCardiomyopathy diagnosisFailure treatmentRisk factorsHeart diseaseComputational 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 toolElectrocardiogramHeart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study
Dhingra L, Aminorroaya A, Sangha V, Pedroso A, Asselbergs F, Brant L, Barreto S, Ribeiro A, Krumholz H, Oikonomou E, Khera R. Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study. European Heart Journal 2025, 46: 1044-1053. PMID: 39804243, PMCID: PMC12086686, DOI: 10.1093/eurheartj/ehae914.Peer-Reviewed Original ResearchYale New Haven Health SystemELSA-BrasilPCP-HFUK BiobankHF riskBrazilian Longitudinal Study of Adult HealthLongitudinal Study of Adult HealthBrazilian Longitudinal StudyRisk of new-onset HFPooled Cohort EquationsPrimary HF hospitalizationsHigher HF riskHarrell's C-statisticRisk of deathNew-onset HFCohort EquationsHealth systemComprehensive clinical evaluationAdult HealthHeart failureIncident HFHF hospitalizationBaseline HFC-statisticPrevent HF
2024
Natural 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 groupsAutomated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing
Nargesi A, Adejumo P, Dhingra L, Rosand B, Hengartner A, Coppi A, Benigeri S, Sen S, Ahmad T, Nadkarni G, Lin Z, Ahmad F, Krumholz H, Khera R. Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing. JACC Heart Failure 2024, 13: 75-87. PMID: 39453355, DOI: 10.1016/j.jchf.2024.08.012.Peer-Reviewed Original ResearchReduced ejection fractionEjection fractionHeart failureLeft ventricular ejection fractionVentricular ejection fractionYale-New Haven HospitalIdentification of patientsCommunity hospitalIdentification of heart failureLanguage modelNorthwestern MedicineMeasure care qualityQuality of careNew Haven HospitalDeep learning-based natural language processingHFrEFGuideline-directed careDeep learning language modelsMIMIC-IIIDetect HFrEFNatural language processingReclassification improvementHospital dischargePatientsCare quality
2022
Performance of current risk stratification models for predicting mortality in patients with heart failure: a systematic review and meta-analysis
Siddiqi TJ, Ahmed A, Greene SJ, Shahid I, Usman MS, Oshunbade A, Alkhouli M, Hall ME, Murad MH, Khera R, Jain V, Van Spall HGC, Khan MS. Performance of current risk stratification models for predicting mortality in patients with heart failure: a systematic review and meta-analysis. European Journal Of Preventive Cardiology 2022, 29: 2027-2048. PMID: 35919956, DOI: 10.1093/eurjpc/zwac148.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsChronic heart failureLong-term mortalityMid-term mortalityAcute HFHeart failureRisk scoreGeneric inverse variance random effects modelInverse variance random-effects modelCurrent risk stratification modelsExcellent discriminationAcute heart failureRisk stratification modelShort-term mortalityLack of headRandom-effects modelGood discriminationAHF mortalityCause mortalityC-statisticNineteen studiesPatientsMortality predictionSystematic reviewHead comparisonMortalityRural-Urban Disparities in Heart Failure and Acute Myocardial Infarction Hospitalizations
Minhas AMK, Sheikh AB, Ijaz SH, Mostafa A, Nazir S, Khera R, Loccoh EC, Warraich HJ. Rural-Urban Disparities in Heart Failure and Acute Myocardial Infarction Hospitalizations. The American Journal Of Cardiology 2022, 175: 164-169. PMID: 35577603, DOI: 10.1016/j.amjcard.2022.04.014.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionHeart failureHospital mortalityUrban hospitalRural hospitalsInflation-adjusted costStudy periodAMI hospitalizationMortality gapNational Inpatient SampleLength of stayAcute myocardial infarction hospitalizationsShorter mean lengthMyocardial infarction hospitalizationsHF hospitalizationCardiovascular outcomesClinical outcomesConsistent decreaseMyocardial infarctionInpatient SampleRural-urban disparitiesCardiovascular careHospitalizationHospitalMean length
2021
Nonalcoholic Fatty Liver Disease and Risk of Heart Failure Among Medicare Beneficiaries
Fudim M, Zhong L, Patel KV, Khera R, Abdelmalek MF, Diehl AM, McGarrah RW, Molinger J, Moylan CA, Rao VN, Wegermann K, Neeland IJ, Halm EA, Das SR, Pandey A. Nonalcoholic Fatty Liver Disease and Risk of Heart Failure Among Medicare Beneficiaries. Journal Of The American Heart Association 2021, 10: e021654. PMID: 34755544, PMCID: PMC8751938, DOI: 10.1161/jaha.121.021654.Peer-Reviewed Original ResearchConceptsNonalcoholic fatty liver diseaseIncident heart failureReduced ejection fractionFatty liver diseaseHeart failureEjection fractionMedicare beneficiariesHF subtypesLiver diseaseHigh riskBackground Nonalcoholic fatty liver diseaseBaseline NAFLDAssociation of NAFLDNew-onset heart failureConclusions PatientsCohort studyPrior diagnosisBlack patientsNinth RevisionKidney diseaseOutpatient claimsRisk factorsIndependent associationHigh burdenMedicare patientsForgone Medical Care Associated With Increased Health Care Costs Among the U.S. Heart Failure Population
Thomas A, Valero-Elizondo J, Khera R, Warraich HJ, Reinhardt SW, Ali HJ, Nasir K, Desai NR. Forgone Medical Care Associated With Increased Health Care Costs Among the U.S. Heart Failure Population. JACC Heart Failure 2021, 9: 710-719. PMID: 34391737, DOI: 10.1016/j.jchf.2021.05.010.Peer-Reviewed Original ResearchConceptsHeart failureHealth care utilizationHealth care costsHealth care expendituresCare utilizationCare costsMedical careMore emergency department visitsTotal health care costsCare expendituresAnnual health careAnnual inpatient costsPrevalence of patientsEmergency department visitsMedical Expenditure Panel SurveyOverall health care spendingHF patientsElderly patientsCare AssociatedDepartment visitsFailure populationInpatient costsHealth care spendingLeading causePatientsOut‐of‐pocket Annual Health Expenditures and Financial Toxicity from Healthcare Costs in Patients with Heart Failure in the United States
Wang SY, Valero‐Elizondo J, Ali H, Pandey A, Cainzos‐Achirica M, Krumholz HM, Nasir K, Khera R. Out‐of‐pocket Annual Health Expenditures and Financial Toxicity from Healthcare Costs in Patients with Heart Failure in the United States. Journal Of The American Heart Association 2021, 10: e022164. PMID: 33998273, PMCID: PMC8483501, DOI: 10.1161/jaha.121.022164.Peer-Reviewed Original ResearchConceptsGreater risk-adjusted oddsRisk-adjusted oddsHeart failureMedical Expenditure Panel SurveyCatastrophic financial burdenPocket healthcare expensesHigh financial burdenFinancial toxicityHealthcare expensesFinancial burdenHealthcare costsCatastrophic burdenMajor public health burdenLow-income familiesBackground Heart failurePublic health burdenInsurance premiumsPanel SurveyPocket healthcare costsAnnual health expenditureWorld Health OrganizationConclusions PatientsHealth insurance premiumsPocket healthcare expenditureHealth burdenContemporary National Patterns of Eligibility and Utilization of Novel Cardioprotective Anti‐hyperglycemic agents in Type 2 Diabetes
Nargesi AA, Jeyashanmugaraja GP, Desai N, Lipska K, Krumholz H, Khera R. Contemporary National Patterns of Eligibility and Utilization of Novel Cardioprotective Anti‐hyperglycemic agents in Type 2 Diabetes. Journal Of The American Heart Association 2021, 10: e021084. PMID: 33998258, PMCID: PMC8403287, DOI: 10.1161/jaha.121.021084.Peer-Reviewed Original ResearchMeSH KeywordsAgedBiomarkersBlood GlucoseCardiovascular DiseasesDiabetes Mellitus, Type 2Drug UtilizationEligibility DeterminationFemaleGlucagon-Like Peptide-1 ReceptorGuideline AdherenceHeart Disease Risk FactorsHumansIncretinsMaleMiddle AgedNutrition SurveysPractice Guidelines as TopicPractice Patterns, Physicians'Risk AssessmentSodium-Glucose Transporter 2 InhibitorsTime FactorsTreatment OutcomeUnited StatesConceptsSGLT-2 inhibitorsType 2 diabetes mellitusAtherosclerotic cardiovascular diseaseChronic kidney diseaseLarge clinical trialsGLP-1RAsDiabetes mellitusCardiovascular diseaseHeart failureKidney diseaseClinical trialsHigh-risk atherosclerotic cardiovascular diseaseGLP-1RA useAmerican Diabetes AssociationNutrition Examination SurveyAnti-hyperglycemic agentsPublic health benefitsComplex survey designCardiovascular riskGuideline recommendationsDiabetes AssociationExamination SurveyProtective therapyNational HealthAmerican College
2020
The Upcoming Epidemic of Heart Failure in South Asia
Martinez-Amezcua P, Haque W, Khera R, Kanaya AM, Sattar N, Lam CSP, Harikrishnan S, Shah SJ, Kandula NR, Jose PO, Narayan KMV, Agyemang C, Misra A, Jenum AK, Bilal U, Nasir K, Cainzos-Achirica M. The Upcoming Epidemic of Heart Failure in South Asia. Circulation Heart Failure 2020, 13: e007218. PMID: 32962410, DOI: 10.1161/circheartfailure.120.007218.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsType 2 diabetes mellitusHeart failureCoronary heart diseaseHeart diseaseHF epidemicDiabetes mellitusEarly type 2 diabetes mellitusLifestyle-related risk factorsPrognosis of HFPremature coronary heart diseasePremature heart failurePrevalent heart failureRheumatic heart diseaseSouth AsiansAbdominal obesityGeneral obesitySouth Asian populationRisk factorsDramatic healthGlobal burdenRecent studiesUrgent interventionUnderrecognized threatTobacco productsUpcoming epidemicPost-discharge acute care and outcomes following readmission reduction initiatives: national retrospective cohort study of Medicare beneficiaries in the United States
Khera R, Wang Y, Bernheim SM, Lin Z, Krumholz HM. Post-discharge acute care and outcomes following readmission reduction initiatives: national retrospective cohort study of Medicare beneficiaries in the United States. The BMJ 2020, 368: l6831. PMID: 31941686, PMCID: PMC7190056, DOI: 10.1136/bmj.l6831.Peer-Reviewed Original ResearchConceptsAcute care utilizationAcute myocardial infarctionRetrospective cohort studyHeart failureCare utilizationPost-discharge periodEmergency departmentMyocardial infarctionDay mortalityCohort studyHospital admissionObservation unitAcute careNational retrospective cohort studyPost-acute care utilizationHospital Readmissions Reduction ProgramObservation unit carePost-discharge mortalityDay readmission rateRisk of deathReadmissions Reduction ProgramReadmission reduction initiativesReadmission ratesUnit careInpatient unit
2019
Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction
Angraal S, Mortazavi BJ, Gupta A, Khera R, Ahmad T, Desai NR, Jacoby DL, Masoudi FA, Spertus JA, Krumholz HM. Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction. JACC Heart Failure 2019, 8: 12-21. PMID: 31606361, DOI: 10.1016/j.jchf.2019.06.013.Peer-Reviewed Original ResearchConceptsHF hospitalizationRisk of mortalityEjection fractionBlood urea nitrogen levelsLogistic regressionPrevious HF hospitalizationHeart failure hospitalizationReduced ejection fractionReceiver-operating characteristic curveRisk of deathBody mass indexBlood urea nitrogenUrea nitrogen levelsHealth status dataMean c-statisticKCCQ scoresTOPCAT trialFailure hospitalizationHeart failureHemoglobin levelsMass indexC-statisticHospitalizationUrea nitrogenMortalityNational Trends in Healthcare-Associated Infections for Five Common Cardiovascular Conditions
Miller PE, Guha A, Khera R, Chouairi F, Ahmad T, Nasir K, Addison D, Desai NR. National Trends in Healthcare-Associated Infections for Five Common Cardiovascular Conditions. The American Journal Of Cardiology 2019, 124: 1140-1148. PMID: 31371062, PMCID: PMC7883647, DOI: 10.1016/j.amjcard.2019.06.029.Peer-Reviewed Original ResearchConceptsLength of stayCommon cardiovascular conditionCentral line-associated bloodstream infectionsCatheter-associated urinary tract infectionsLine-associated bloodstream infectionsUrinary tract infectionVentilator-associated pneumoniaClostridium difficile infectionCardiovascular conditionsTract infectionsBloodstream infectionsDifficile infectionOutcome of HAICoronary artery bypassTotal hospital chargesAcute myocardial infarctionSkilled care facilityHealthcare-Associated InfectionsValue-based careHospital mortalityArtery bypassCardiogenic shockHeart failurePropensity matchingAtrial fibrillationEvaluation of 30-Day Hospital Readmission and Mortality Rates Using Regression-Discontinuity Framework
Khera R, Wang Y, Nasir K, Lin Z, Krumholz HM. Evaluation of 30-Day Hospital Readmission and Mortality Rates Using Regression-Discontinuity Framework. Journal Of The American College Of Cardiology 2019, 74: 219-234. PMID: 31296295, PMCID: PMC8669780, DOI: 10.1016/j.jacc.2019.04.060.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionHospital Readmissions Reduction ProgramHeart failureReadmission ratesElderly Medicare feeMedian readmission rateReadmissions Reduction ProgramPost-discharge daysInstitution of strategiesHospital readmissionReadmission riskMyocardial infarctionReadmission reductionCardiovascular conditionsEligible hospitalsMedicare feeReadmission penaltiesMortality rateDay 1Day 30ReadmissionDay 60HospitalU.S. hospitalsHospitalization
2018
Trends in 30-Day Readmission Rates for Medicare and Non-Medicare Patients in the Era of the Affordable Care Act
Angraal S, Khera R, Zhou S, Wang Y, Lin Z, Dharmarajan K, Desai NR, Bernheim SM, Drye EE, Nasir K, Horwitz LI, Krumholz HM. Trends in 30-Day Readmission Rates for Medicare and Non-Medicare Patients in the Era of the Affordable Care Act. The American Journal Of Medicine 2018, 131: 1324-1331.e14. PMID: 30016636, PMCID: PMC6380174, DOI: 10.1016/j.amjmed.2018.06.013.Peer-Reviewed Original ResearchConceptsHospital Readmissions Reduction ProgramReadmission ratesAcute myocardial infarctionHeart failurePatient groupMyocardial infarctionCause readmission rateNationwide Readmissions DatabaseReadmissions Reduction ProgramNon-Medicare patientsNon-target conditionsLower readmissionAffordable Care ActMedicare beneficiariesAge groupsPrivate insuranceCare ActPneumoniaInfarctionPatientsReduction programsMedicareGroupReadmissionFailure
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