2023
Developing an Actionable Taxonomy of Persistent Hypertension Using Electronic Health Records
Lu Y, Du C, Khidir H, Caraballo C, Mahajan S, Spatz E, Curry L, Krumholz H. Developing an Actionable Taxonomy of Persistent Hypertension Using Electronic Health Records. Circulation Cardiovascular Quality And Outcomes 2023, 16: e009453. PMID: 36727515, DOI: 10.1161/circoutcomes.122.009453.Peer-Reviewed Original ResearchConceptsPersistent hypertensionElectronic health recordsBlood pressureHealth recordsPharmacologic agentsPrescribed treatmentYale New Haven Health SystemTreatment planAdditional pharmacologic agentsAntihypertensive treatment intensificationConsecutive outpatient visitsElevated blood pressurePersistence of hypertensionElectronic health record dataHealth record dataEligible patientsTreatment intensificationChart reviewHispanic patientsOutpatient visitsMean agePharmacological treatmentConventional content analysisHypertensionClinician notes
2020
Assessment of Prevalence, Awareness, and Characteristics of Isolated Systolic Hypertension Among Younger and Middle-Aged Adults in China
Mahajan S, Feng F, Hu S, Lu Y, Gupta A, Murugiah K, Gao Y, Lu J, Liu J, Zheng X, Spatz ES, Zhang H, Krumholz HM, Li J. Assessment of Prevalence, Awareness, and Characteristics of Isolated Systolic Hypertension Among Younger and Middle-Aged Adults in China. JAMA Network Open 2020, 3: e209743. PMID: 33289843, PMCID: PMC7724558, DOI: 10.1001/jamanetworkopen.2020.9743.Peer-Reviewed Original ResearchConceptsMiddle-aged adultsSystolic hypertensionCardiac Events Million Persons ProjectOlder individualsIsolated systolic hypertensionManagement of ISHMillion Persons ProjectPrevalence of ISHPrevious cardiovascular eventsSystolic blood pressureTypes of hypertensionAssessment of prevalenceCross-sectional studyHypertension subtypesCardiovascular eventsBlood pressureChina PatientMean ageHypertensionMAIN OUTCOMEAwareness ratePrevalenceAged adultsYoung adultsAdultsRelationship of Age With the Hemodynamic Parameters in Individuals With Elevated Blood Pressure
Mahajan S, Gu J, Caraballo C, Lu Y, Spatz ES, Zhao H, Zhang M, Sun N, Zheng X, Lu H, Yuan H, J. Z, Krumholz HM. Relationship of Age With the Hemodynamic Parameters in Individuals With Elevated Blood Pressure. Journal Of The American Geriatrics Society 2020, 68: 1520-1528. PMID: 32212398, DOI: 10.1111/jgs.16411.Peer-Reviewed Original ResearchConceptsElevated blood pressureBlood pressureCardiac indexHemodynamic profileHemodynamic parametersHealth checkup centerFinal study populationPathophysiology of hypertensionSelection of therapyCross-sectional studyMin/Relationship of ageDifferent age groupsHemodynamic assessmentMean ageStudy populationMAIN OUTCOMEAge strataAge groupsLarger studyImpedance cardiographyAgeSVRIWomenMenBurden 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
2019
Development and Validation of a Model for Predicting the Risk of Acute Kidney Injury Associated With Contrast Volume Levels During Percutaneous Coronary Intervention
Huang C, Li SX, Mahajan S, Testani JM, Wilson FP, Mena CI, Masoudi FA, Rumsfeld JS, Spertus JA, Mortazavi BJ, Krumholz HM. Development and Validation of a Model for Predicting the Risk of Acute Kidney Injury Associated With Contrast Volume Levels During Percutaneous Coronary Intervention. JAMA Network Open 2019, 2: e1916021. PMID: 31755952, PMCID: PMC6902830, DOI: 10.1001/jamanetworkopen.2019.16021.Peer-Reviewed Original ResearchConceptsCreatinine level increaseAcute kidney injuryPercutaneous coronary interventionContrast volumeAKI riskKidney injuryCoronary interventionBaseline riskCardiology National Cardiovascular Data Registry's CathPCI RegistryNational Cardiovascular Data Registry CathPCI RegistryRisk of AKIAcute Kidney Injury AssociatedDifferent baseline risksPCI safetyCathPCI RegistryInjury AssociatedMean ageDerivation setPreprocedural riskMAIN OUTCOMEAmerican CollegePrognostic studiesUS hospitalsCalibration slopeValidation set
2018
Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study
Huang C, Murugiah K, Mahajan S, Li SX, Dhruva SS, Haimovich JS, Wang Y, Schulz WL, Testani JM, Wilson FP, Mena CI, Masoudi FA, Rumsfeld JS, Spertus JA, Mortazavi BJ, Krumholz HM. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study. PLOS Medicine 2018, 15: e1002703. PMID: 30481186, PMCID: PMC6258473, DOI: 10.1371/journal.pmed.1002703.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAgedClinical Decision-MakingData MiningDecision Support TechniquesFemaleHumansMachine LearningMaleMiddle AgedPercutaneous Coronary InterventionProtective FactorsRegistriesReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeConceptsPercutaneous coronary interventionNational Cardiovascular Data RegistryRisk prediction modelAKI eventsAKI riskCoronary interventionAKI modelMean ageCardiology-National Cardiovascular Data RegistryAcute kidney injury riskAKI risk predictionRetrospective cohort studyIdentification of patientsCandidate variablesAvailable candidate variablesCohort studyPCI proceduresPoint of careBrier scoreAmerican CollegeData registryPatientsCalibration slopeInjury riskSame cohort