Featured Publications
Individualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials
Oikonomou EK, Spatz ES, Suchard MA, Khera R. Individualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials. The Lancet Digital Health 2022, 4: e796-e805. PMID: 36307193, PMCID: PMC9768739, DOI: 10.1016/s2589-7500(22)00170-4.Peer-Reviewed Original ResearchConceptsSystolic blood pressure controlBlood pressure controlIntensive systolic blood pressure controlType 2 diabetesPressure controlCardiovascular benefitsClinical trialsMajor adverse cardiovascular eventsFirst major adverse cardiovascular eventLarge randomised clinical trialsACCORD-BP trialAdverse cardiovascular eventsRandomised clinical trialsSystolic blood pressureCox regression analysisTreatment effectsHazard ratio estimatesACCORD-BPBP trialCardiovascular eventsBlood pressurePrimary outcomeStandard treatmentBaseline variablesIndex patients
2024
Performance of contemporary cardiovascular risk stratification scores in Brazil: an evaluation in the ELSA-Brasil study
Camargos A, Barreto S, Brant L, Ribeiro A, Dhingra L, Aminorroaya A, Bittencourt M, Figueiredo R, Khera R. Performance of contemporary cardiovascular risk stratification scores in Brazil: an evaluation in the ELSA-Brasil study. Open Heart 2024, 11: e002762. PMID: 38862252, PMCID: PMC11168182, DOI: 10.1136/openhrt-2024-002762.Peer-Reviewed Original ResearchConceptsPooled Cohort EquationsELSA-BrasilRisk scoreCardiovascular diseaseCVD eventsCommunity-based cohort studyArea under the receiver operating characteristic curveCVD risk scoreELSA-Brasil studyIncident CVD eventsMiddle-income countriesAdjudicated CVD eventsCardiovascular disease riskCVD scoreCohort EquationsNational guidelinesRisk stratification scoresWhite womenAge/sex groupsCohort studyProspective cohortLMICsSex/race groupsHigher incomeRisk discrimination
2023
Machine learning in precision diabetes care and cardiovascular risk prediction
Oikonomou E, Khera R. Machine learning in precision diabetes care and cardiovascular risk prediction. Cardiovascular Diabetology 2023, 22: 259. PMID: 37749579, PMCID: PMC10521578, DOI: 10.1186/s12933-023-01985-3.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsArtificial intelligence solutionsArtificial intelligence productsData-driven methodIntelligence solutionsArtificial intelligenceMachine learningPersonalized solutionsIntelligence productsBias mitigationMachineKey issuesPredictive modelSuch modelsSuccessful applicationRisk predictionParadigm shiftIntelligenceKey propertiesApplicationsLearningPersonalized careFrameworkSolutionCurrent regulatory frameworkHealthcareUse of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020
Dhingra L, Aminorroaya A, Oikonomou E, Nargesi A, Wilson F, Krumholz H, Khera R. Use of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020. JAMA Network Open 2023, 6: e2316634. PMID: 37285157, PMCID: PMC10248745, DOI: 10.1001/jamanetworkopen.2023.16634.Peer-Reviewed Original ResearchMeSH KeywordsAdultCardiovascular DiseasesCross-Sectional StudiesFemaleHumansHypertensionMaleMiddle AgedObesityRisk FactorsConceptsHealth Information National Trends SurveyUS adultsExacerbate disparitiesWearable device usersCardiovascular diseaseCardiovascular healthPopulation-based cross-sectional studySelf-reported cardiovascular diseaseCardiovascular disease risk factorsNational Trends SurveyOverall US adult populationCardiovascular risk factor profileSelf-reported accessAssociated with lower useUse of wearable devicesImprove cardiovascular healthLower household incomeLower educational attainmentUS adult populationRisk factor profileNationally representative sampleCross-sectional studyProportion of adultsTrends SurveyWearable device dataSex Difference in Outcomes of Acute Myocardial Infarction in Young Patients
Sawano M, Lu Y, Caraballo C, Mahajan S, Dreyer R, Lichtman J, D'Onofrio G, Spatz E, Khera R, Onuma O, Murugiah K, Spertus J, Krumholz H. Sex Difference in Outcomes of Acute Myocardial Infarction in Young Patients. Journal Of The American College Of Cardiology 2023, 81: 1797-1806. PMID: 37137590, DOI: 10.1016/j.jacc.2023.03.383.Peer-Reviewed Original ResearchMeSH KeywordsFemaleHealth StatusHospitalizationHumansMaleMyocardial InfarctionRisk FactorsSex CharacteristicsSex FactorsConceptsAcute myocardial infarctionNoncardiac hospitalizationsSubdistribution HRYounger patientsMyocardial infarctionSex differencesYoung womenCause-specific hospitalizationsCause of hospitalizationWorse health statusSignificant sex disparityNoncardiovascular hospitalizationsVIRGO StudyIndex episodeAdverse outcomesIncidence rateHospitalizationHigh riskSex disparitiesHealth statusPatientsU.S. hospitalsWomenInfarctionOutcomesQuantifying Blood Pressure Visit-to-Visit Variability in the Real-World Setting: A Retrospective Cohort Study
Lu Y, Linderman G, Mahajan S, Liu Y, Huang C, Khera R, Mortazavi B, Spatz E, Krumholz H. Quantifying Blood Pressure Visit-to-Visit Variability in the Real-World Setting: A Retrospective Cohort Study. Circulation Cardiovascular Quality And Outcomes 2023, 16: e009258. PMID: 36883456, DOI: 10.1161/circoutcomes.122.009258.Peer-Reviewed Original ResearchConceptsRetrospective cohort studyBlood pressure valuesPatient characteristicsReal-world settingCohort studyPatient subgroupsYale New Haven Health SystemMean body mass indexSystolic blood pressure valuesBlood pressure visitHistory of hypertensionCoronary artery diseaseManagement of patientsMultivariable linear regression modelsBlood pressure readingsBody mass indexPatient-level measuresBlood pressure variationAbsolute standardized differencesNon-Hispanic whitesAntihypertensive medicationsReal-world practiceVisit variabilityArtery diseaseRegression models
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 comparisonMortalitySex-Specific Risk Factors Associated With First Acute Myocardial Infarction in Young Adults
Lu Y, Li SX, Liu Y, Rodriguez F, Watson KE, Dreyer RP, Khera R, Murugiah K, D’Onofrio G, Spatz ES, Nasir K, Masoudi FA, Krumholz HM. Sex-Specific Risk Factors Associated With First Acute Myocardial Infarction in Young Adults. JAMA Network Open 2022, 5: e229953. PMID: 35503221, PMCID: PMC9066284, DOI: 10.1001/jamanetworkopen.2022.9953.Peer-Reviewed Original ResearchConceptsFirst acute myocardial infarctionAcute myocardial infarctionPsychosocial risk factorsRisk factor profilePopulation attributable fractionRisk factor associationsRisk factorsOdds ratioYoung womenAMI subtypesMyocardial infarctionPrevention of AMIType 1 acute myocardial infarctionFactor profileRisk of AMITraditional cardiovascular risk factorsSex-specific risk factorsFactor associationsYoung adultsRisk factor modificationCardiovascular risk factorsStrong associationNutrition Examination SurveyCase-control studyPopulation-based controlsDepression and Perceived Stress After Spontaneous Coronary Artery Dissection and Comparison With Other Acute Myocardial Infarction (the VIRGO Experience)
Murugiah K, Chen L, Dreyer RP, Bouras G, Safdar B, Lu Y, Spatz ES, Gupta A, Khera R, Ng VG, Bueno H, Tweet MS, Spertus JA, Hayes SN, Lansky A, Krumholz HM. Depression and Perceived Stress After Spontaneous Coronary Artery Dissection and Comparison With Other Acute Myocardial Infarction (the VIRGO Experience). The American Journal Of Cardiology 2022, 173: 33-38. PMID: 35365290, PMCID: PMC9133198, DOI: 10.1016/j.amjcard.2022.03.005.Peer-Reviewed Original ResearchConceptsSpontaneous coronary artery dissectionPatient Health Questionnaire-9Coronary artery dissectionPSS-14 scoreArtery dissectionBaseline PHQ-9 scoreAcute myocardial infarction patientsCardiovascular risk factorsPHQ-9 scoresAcute myocardial infarctionMyocardial infarction patientsYears of agePerceived Stress Scale scoresStress Scale scoresLinear mixed-effects analysisSCAD casesVIRGO StudyQuestionnaire-9Infarction patientsMixed-effects analysisMyocardial infarctionSubgroup analysisRisk factorsRoutine screeningClinical acuityPhenomapping-Derived Tool to Individualize the Effect of Canagliflozin on Cardiovascular Risk in Type 2 Diabetes.
Oikonomou EK, Suchard MA, McGuire DK, Khera R. Phenomapping-Derived Tool to Individualize the Effect of Canagliflozin on Cardiovascular Risk in Type 2 Diabetes. Diabetes Care 2022, 45: 965-974. PMID: 35120199, PMCID: PMC9016734, DOI: 10.2337/dc21-1765.Peer-Reviewed Original ResearchConceptsCanagliflozin Cardiovascular Assessment StudyMajor adverse cardiovascular eventsType 2 diabetesHazard ratioSodium-glucose cotransporter 2 inhibitorsCardiovascular disease benefitAdverse cardiovascular eventsCotransporter 2 inhibitorsEffects of canagliflozinCanagliflozin dosesCanagliflozin's effectsCardiovascular eventsCardiovascular riskPatients 5Cardioprotective effectsSGLT2 inhibitorsDisease benefitBaseline variablesOriginal trialCanagliflozinType 2DiabetesPatientsRisk estimatesEffect estimates
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 patientsScope and Social Determinants of Food Insecurity Among Adults With Atherosclerotic Cardiovascular Disease in the United States
Mahajan S, Grandhi GR, Valero‐Elizondo J, Mszar R, Khera R, Acquah I, Yahya T, Virani SS, Blankstein R, Blaha MJ, Cainzos‐Achirica M, Nasir K. Scope and Social Determinants of Food Insecurity Among Adults With Atherosclerotic Cardiovascular Disease in the United States. Journal Of The American Heart Association 2021, 10: e020028. PMID: 34387089, PMCID: PMC8475063, DOI: 10.1161/jaha.120.020028.Peer-Reviewed Original ResearchConceptsHigh-risk characteristicsUS adultsNational Health Interview Survey dataHealth Interview Survey dataAtherosclerotic cardiovascular diseaseCoronary heart diseaseSelf-reported diagnosisNon-Hispanic blacksInterview Survey dataFood Security Survey ModuleCardiovascular disease resultsLow family incomeAdult Food Security Survey ModuleFood insecurityHeart diseaseASCVDCardiovascular diseasePocket healthcare expenditureHigher oddsSociodemographic determinantsDisease resultsStudy participantsSocial determinantsHealthcare expendituresSociodemographic subgroupsAssociation of Kidney Disease With Outcomes in COVID‐19: Results From the American Heart Association COVID‐19 Cardiovascular Disease Registry
Rao A, Ranka S, Ayers C, Hendren N, Rosenblatt A, Alger HM, Rutan C, Omar W, Khera R, Gupta K, Mody P, DeFilippi C, Das SR, Hedayati SS, de Lemos JA. Association of Kidney Disease With Outcomes in COVID‐19: Results From the American Heart Association COVID‐19 Cardiovascular Disease Registry. Journal Of The American Heart Association 2021, 10: e020910. PMID: 34107743, PMCID: PMC8477855, DOI: 10.1161/jaha.121.020910.Peer-Reviewed Original ResearchConceptsAcute kidney injuryMajor adverse cardiac eventsAdverse cardiac eventsChronic kidney diseaseCardiac eventsKidney diseaseCause mortalityAmerican Heart Association COVID-19 Cardiovascular Disease RegistryCOVID-19Major adverse cardiovascular eventsEnd-stage kidney diseaseCardiovascular Disease RegistryLarge multicenter registryNonfatal heart failureSerial laboratory dataAdverse cardiovascular eventsNonfatal myocardial infarctionKey secondary outcomesCardiovascular disease outcomesPrimary exposure variableNonfatal strokeCardiogenic shockCardiovascular deathCardiovascular eventsCardiovascular outcomesElectronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit
Kunitomo Y, Thomas A, Chouairi F, Canavan ME, Kochar A, Khera R, Katz JN, Murphy C, Jentzer J, Ahmad T, Desai NR, Brennan J, Miller PE. Electronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit. American Heart Journal 2021, 238: 85-88. PMID: 33891906, DOI: 10.1016/j.ahj.2021.04.004.Peer-Reviewed Original ResearchConceptsCardiac intensive care unitIntensive care unitRothman IndexCare unitRisk scoreModern cardiac intensive care unitSequential Organ Failure Assessment scoreOrgan Failure Assessment scoreElectronic health recordsCICU mortalityCICU patientsSOFA scoreCICU admissionClinical outcomesEarly prognosticationObservational studyPrognostic abilityAssessment scoresOutcome predictionHealth recordsGood calibrationSuperior discriminationPatientsAdmissionScores
2020
Revascularization Practices and Outcomes in Patients With Multivessel Coronary Artery Disease Who Presented With Acute Myocardial Infarction and Cardiogenic Shock in the US, 2009-2018
Khera R, Secemsky EA, Wang Y, Desai NR, Krumholz HM, Maddox TM, Shunk KA, Virani SS, Bhatt DL, Curtis J, Yeh RW. Revascularization Practices and Outcomes in Patients With Multivessel Coronary Artery Disease Who Presented With Acute Myocardial Infarction and Cardiogenic Shock in the US, 2009-2018. JAMA Internal Medicine 2020, 180: 1317-1327. PMID: 32833024, PMCID: PMC9377424, DOI: 10.1001/jamainternmed.2020.3276.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedCohort StudiesCoronary VesselsFemaleFollow-Up StudiesHospital MortalityHumansMaleMiddle AgedMyocardial InfarctionPatient DischargePercutaneous Coronary InterventionRisk AssessmentRisk FactorsShock, CardiogenicST Elevation Myocardial InfarctionTime FactorsTreatment OutcomeUnited StatesConceptsST-segment elevation myocardial infarctionMultivessel percutaneous coronary interventionMultivessel coronary artery diseasePercutaneous coronary interventionAcute myocardial infarctionCoronary artery diseaseCulprit vessel percutaneous coronary interventionCardiogenic shockHospital mortalityArtery diseaseMyocardial infarctionCohort studyPrimary outcomeHospital variationPCI strategyMedicare beneficiariesUnderwent multivessel PCISignificant hospital variationElevation myocardial infarctionSubset of patientsHigh-risk populationRecent evidenceHospital complicationsPCI useRevascularization practiceTemporal Trends in Heart Failure Incidence Among Medicare Beneficiaries Across Risk Factor Strata, 2011 to 2016
Khera R, Kondamudi N, Zhong L, Vaduganathan M, Parker J, Das SR, Grodin JL, Halm EA, Berry JD, Pandey A. Temporal Trends in Heart Failure Incidence Among Medicare Beneficiaries Across Risk Factor Strata, 2011 to 2016. JAMA Network Open 2020, 3: e2022190. PMID: 33095250, PMCID: PMC7584929, DOI: 10.1001/jamanetworkopen.2020.22190.Peer-Reviewed Original ResearchConceptsHeart failure incidenceHF risk factorsHF incidenceClinical Modification codesRisk factorsAcute MIMedicare beneficiariesFailure incidenceHF prevention strategiesRisk factor strataNational cohort studyService Medicare beneficiariesUnique Medicare beneficiariesInternational Statistical ClassificationRace/ethnicityPrior HFPrevalent hypertensionCohort studyIncident HFNinth RevisionPrevious diagnosisCardiovascular conditionsTenth RevisionMAIN OUTCOMEInternational ClassificationPerformance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index
Khera R, Pandey A, Ayers CR, Carnethon MR, Greenland P, Ndumele CE, Nambi V, Seliger SL, Chaves PHM, Safford MM, Cushman M, Xanthakis V, Ramachandran V, Mentz RJ, Correa A, Lloyd-Jones DM, Berry JD, de Lemos JA, Neeland IJ. Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index. JAMA Network Open 2020, 3: e2023242. PMID: 33119108, PMCID: PMC7596579, DOI: 10.1001/jamanetworkopen.2020.23242.Peer-Reviewed Original ResearchConceptsHigh-sensitivity C-reactive proteinPooled Cohort EquationsASCVD riskAtherosclerotic cardiovascular diseaseBody mass indexBMI categoriesCohort EquationsObesity categoriesCohort studySevere obesityWaist circumferenceBMI groupsMass indexUnderweight categoryAtherosclerotic cardiovascular disease riskMean baseline BMIRisk of ASCVDUsual clinical measuresCardiovascular disease riskC-reactive proteinPooled individual-level dataSevere obesity groupLongitudinal cohort studyNormal weight categoryAdults ages 40The 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 epidemicFinancial Hardship After Traumatic Injury: Risk Factors and Drivers of Out-of-Pocket Health Expenses
O'Neill KM, Jean RA, Gross CP, Becher RD, Khera R, Elizondo JV, Nasir K. Financial Hardship After Traumatic Injury: Risk Factors and Drivers of Out-of-Pocket Health Expenses. Journal Of Surgical Research 2020, 256: 1-12. PMID: 32663705, DOI: 10.1016/j.jss.2020.05.095.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedChildChild, PreschoolCost of IllnessCross-Sectional StudiesFamilyFemaleFinancial StressHealth ExpendituresHospitalizationHumansInfantInfant, NewbornInsurance, HealthMaleMiddle AgedPrescription DrugsRetrospective StudiesRisk FactorsSocioeconomic FactorsUnited StatesWounds and InjuriesYoung AdultConceptsTraumatic injuryOOP expensesPocket health expensesExcess financial burdenHealth expensesInpatient costsCatastrophic medical expensesFinancial burdenMultivariable logistic regression analysisMedical expensesHealth care factorsCostly medical conditionsCross-sectional studyMedical Expenditure Panel SurveyLogistic regression analysisPrescription drug costsFinancial hardshipHealth care systemFamily membersTrauma-related disordersPrimary outcomeCare factorsEmergency roomRisk factorsDrug costsBurden and Consequences of Financial Hardship From Medical Bills Among Nonelderly Adults With Diabetes Mellitus in the United States
Caraballo C, Valero-Elizondo J, Khera R, Mahajan S, Grandhi GR, Virani SS, Mszar R, Krumholz HM, Nasir K. Burden and Consequences of Financial Hardship From Medical Bills Among Nonelderly Adults With Diabetes Mellitus in the United States. Circulation Cardiovascular Quality And Outcomes 2020, 13: e006139. PMID: 32069093, DOI: 10.1161/circoutcomes.119.006139.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsBlack or African AmericanComorbidityCost of IllnessCross-Sectional StudiesDiabetes MellitusFemaleFinancing, PersonalFood SupplyHealth Care CostsHealth Care SurveysHealth ExpendituresHealth Services AccessibilityHumansIncomeMaleMedically UninsuredMiddle AgedPatient ComplianceRisk AssessmentRisk FactorsUnited StatesYoung AdultConceptsDiabetes mellitusMedical billsHigher oddsMedical careNational Health Interview Survey dataHealth Interview Survey dataCost-related medication nonadherenceHigher comorbidity burdenCost-related nonadherenceSelf-reported diagnosisNon-Hispanic blacksInterview Survey dataFinancial hardshipMedication nonadherenceMean ageNonmedical needsHigh prevalenceMellitusMultivariate analysisPocket expenditureFood insecurityNonadherenceHigh financial distressPatientsAdults