2024
Hypertension Trends and Disparities Over 12 Years in a Large Health System: Leveraging the Electronic Health Records
Brush J, Lu Y, Liu Y, Asher J, Li S, Sawano M, Young P, Schulz W, Anderson M, Burrows J, Krumholz H. Hypertension Trends and Disparities Over 12 Years in a Large Health System: Leveraging the Electronic Health Records. Journal Of The American Heart Association 2024, 13: e033253. PMID: 38686864, PMCID: PMC11179912, DOI: 10.1161/jaha.123.033253.Peer-Reviewed Original ResearchConceptsElectronic health recordsRegional health systemImprove hypertension careHealth systemHealth recordsHypertension careDiastolic blood pressureAge-adjusted prevalence ratesNon-Hispanic Black patientsPrevalence ratesLarger health systemCross-sectional analysisTransformation of medical dataLeveraging real-world dataHigh prevalence rateHypertension trendsHypertension prevalenceBlood pressureBlood pressure measurementsHypertension diagnosisPrimary outcomeNational trendsProportion of patientsAntihypertensive medicationsBlack patients
2022
Three-Month Symptom Profiles Among Symptomatic Adults With Positive and Negative Severe Acute Respiratory Syndrome Coronavirus 2 Tests: A Prospective Cohort Study From the INSPIRE Group
Spatz E, Gottlieb M, Wisk L, Anderson J, Chang A, Gentile N, Hill M, Huebinger R, Idris A, Kinsman J, Koo K, Li S, McDonald S, Plumb I, Rodriguez R, Saydah S, Slovis B, Stephens K, Unger E, Wang R, Yu H, Hota B, Elmore J, Weinstein R, Venkatesh A. Three-Month Symptom Profiles Among Symptomatic Adults With Positive and Negative Severe Acute Respiratory Syndrome Coronavirus 2 Tests: A Prospective Cohort Study From the INSPIRE Group. Clinical Infectious Diseases 2022, 76: 1559-1566. PMID: 36573005, PMCID: PMC11361781, DOI: 10.1093/cid/ciac966.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 symptomsSARS-CoV-2 infectionPost-infectious syndromesProspective cohort studyCohort studyCOVID groupAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionSARS-CoV-2 test resultsSyndrome coronavirus 2 infectionEar/nose/throatSevere acute respiratory syndrome coronavirus 2 testsCoronavirus 2 infectionLong-term symptomsNose/throatLong COVIDSymptomatic adultsMean ageActive symptomsSymptom profilesDrug AdministrationSociodemographic characteristicsSymptomsInfectionMonthsSex-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 controlsLeading Causes of Death Among Adults Aged 25 to 44 Years by Race and Ethnicity in Texas During the COVID-19 Pandemic, March to December 2020
Faust JS, Chen AJ, Tiako M, Du C, Li SX, Krumholz HM, Barnett ML. Leading Causes of Death Among Adults Aged 25 to 44 Years by Race and Ethnicity in Texas During the COVID-19 Pandemic, March to December 2020. JAMA Internal Medicine 2022, 182: 87-90. PMID: 34807250, PMCID: PMC8609460, DOI: 10.1001/jamainternmed.2021.6734.Peer-Reviewed Original Research
2021
Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models
Triche EW, Xin X, Stackland S, Purvis D, Harris A, Yu H, Grady JN, Li SX, Bernheim SM, Krumholz HM, Poyer J, Dorsey K. Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models. JAMA Network Open 2021, 4: e218512. PMID: 33978722, PMCID: PMC8116982, DOI: 10.1001/jamanetworkopen.2021.8512.Peer-Reviewed Original ResearchConceptsPOA indicatorRisk factorsOutcome measuresQuality outcome measuresRisk-adjustment modelsClaims dataAdmission indicatorsPatient risk factorsAcute myocardial infarctionPatient-level outcomesAdministrative claims dataQuality improvement studyClaims-based measuresComparative effectiveness studiesPatient claims dataInternational Statistical ClassificationMortality outcome measuresRelated Health ProblemsHospital quality measuresRisk model performanceHospital stayIndex admissionCare algorithmHeart failureMortality outcomesDelays in antibiotic redosing: Association with inpatient mortality and risk factors for delay
Kemmler CB, Sangal RB, Rothenberg C, Li SX, Shofer FS, Abella BS, Venkatesh AK, Foster SD. Delays in antibiotic redosing: Association with inpatient mortality and risk factors for delay. The American Journal Of Emergency Medicine 2021, 46: 63-69. PMID: 33735698, DOI: 10.1016/j.ajem.2021.02.058.Peer-Reviewed Original ResearchConceptsSecond dose administrationEmergency departmentDose administrationRisk factorsEmergency Severity IndexHospital mortalityFirst doseSecond doseED boardingAntibiotic dosesEnd-stage renal diseaseExtremes of weightHigh acuity presentationsRetrospective cohort studyStage renal diseaseWorse clinical outcomesSerious bacterial infectionsOdds of delayEarly hospital courseSingle healthcare systemAntibiotic redosingDosing intervalHospital courseCohort studyInpatient mortalitySARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate Among the Non-Congregate Population in Connecticut
Mahajan S, Caraballo C, Li SX, Dong Y, Chen L, Huston SK, Srinivasan R, Redlich CA, Ko AI, Faust JS, Forman HP, Krumholz HM. SARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate Among the Non-Congregate Population in Connecticut. The American Journal Of Medicine 2021, 134: 812-816.e2. PMID: 33617808, PMCID: PMC7895685, DOI: 10.1016/j.amjmed.2021.01.020.Peer-Reviewed Original ResearchConceptsInfection hospitalization rateInfection fatality rateHospitalization ratesFatality rateSeroprevalence estimatesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodiesSARS-CoV-2 antibodiesConnecticut Hospital AssociationNon-Hispanic black peopleProportion of deathsCoronavirus disease 2019Total infected individualsTotal hospitalizationsAdverse outcomesNon-congregate settingsHigh burdenDisease 2019Prevalence studyMost subgroupsInfected individualsHospitalizationOlder peopleHospital AssociationConnecticut DepartmentDeath
2020
Seroprevalence of SARS-CoV-2-Specific IgG Antibodies Among Adults Living in Connecticut: Post-Infection Prevalence (PIP) Study
Mahajan S, Srinivasan R, Redlich CA, Huston SK, Anastasio KM, Cashman L, Massey DS, Dugan A, Witters D, Marlar J, Li SX, Lin Z, Hodge D, Chattopadhyay M, Adams MD, Lee C, Rao LV, Stewart C, Kuppusamy K, Ko AI, Krumholz HM. Seroprevalence of SARS-CoV-2-Specific IgG Antibodies Among Adults Living in Connecticut: Post-Infection Prevalence (PIP) Study. The American Journal Of Medicine 2020, 134: 526-534.e11. PMID: 33130124, PMCID: PMC7598362, DOI: 10.1016/j.amjmed.2020.09.024.Peer-Reviewed Original ResearchConceptsSARS-CoV-2-specific IgG antibodiesWeighted seroprevalenceIgG antibodiesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodiesSARS-CoV-2-specific antibodiesConnecticut residentsSelf-reported adherenceImmunoglobulin G antibodiesSARS-CoV-2Symptomatic illnessSerology testingSeroprevalence studyG antibodiesPrevalence studyGeneral populationPercentage of peopleSeroprevalenceLack antibodiesMajority of respondentsAntibodiesHispanic subpopulationsConvenience sampleHispanic populationCOVID-19Risk mitigation behaviors
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 setDevelopment and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data
Krumholz HM, Warner F, Coppi A, Triche EW, Li SX, Mahajan S, Li Y, Bernheim SM, Grady J, Dorsey K, Desai NR, Lin Z, Normand ST. Development and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data. JAMA Network Open 2019, 2: e198406. PMID: 31411709, PMCID: PMC6694388, DOI: 10.1001/jamanetworkopen.2019.8406.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionHeart failurePopulation-based programsPOA codesSingle diagnostic codeDiagnostic codesComparative effectiveness research studyPublic reportingIndex admission diagnosisDays of hospitalizationClinical Modification codesService claims dataAcute care hospitalsMultiple care settingsPatient-level modelsAdmission diagnosisTotal hospitalizationsCare hospitalPrevious diagnosisNinth RevisionMyocardial infarctionCandidate variablesCare settingsClaims dataMAIN OUTCOMEComparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data
Krumholz HM, Coppi AC, Warner F, Triche EW, Li SX, Mahajan S, Li Y, Bernheim SM, Grady J, Dorsey K, Lin Z, Normand ST. Comparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data. JAMA Network Open 2019, 2: e197314. PMID: 31314120, PMCID: PMC6647547, DOI: 10.1001/jamanetworkopen.2019.7314.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionICD-9-CM codesMortality risk modelHeart failureHospital admissionC-statisticMAIN OUTCOMEMortality rateRisk-standardized mortality ratesHospital risk-standardized mortality ratesIndex admission diagnosisPatients 65 yearsDays of hospitalizationComparative effectiveness studiesClaims-based dataHospital-level performance measuresMedicare claims dataPatient-level modelsCMS modelRisk-adjustment modelsRisk modelHospital performance measuresAdmission diagnosisNinth RevisionMyocardial infarctionAssociation Between Insurance Status and Access to Hospital Care in Emergency Department Disposition
Venkatesh AK, Chou SC, Li SX, Choi J, Ross JS, D’Onofrio G, Krumholz HM, Dharmarajan K. Association Between Insurance Status and Access to Hospital Care in Emergency Department Disposition. JAMA Internal Medicine 2019, 179: 686-693. PMID: 30933243, PMCID: PMC6503571, DOI: 10.1001/jamainternmed.2019.0037.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAsthmaCritical CareCross-Sectional StudiesDatabases, FactualEmergency Service, HospitalFemaleHealth Services AccessibilityHospitalizationHumansInsurance CoverageInsurance, HealthLung DiseasesMaleMedicaidMedically UninsuredMiddle AgedPatient DischargePatient TransferPneumoniaPulmonary Disease, Chronic ObstructiveUnited StatesConceptsNational Emergency Department SampleEmergency Department SampleCommon medical conditionsUninsured patientsCritical care capabilitiesED dischargeED visitsED transfersPulmonary diseaseCare capabilitiesInsurance statusHigher oddsMedicaid beneficiariesMedical conditionsChronic obstructive pulmonary diseaseAcute pulmonary diseaseEmergency department transfersAdult ED visitsHospital admission ratesObstructive pulmonary diseaseEmergency department dispositionPatient insurance statusPatient case mixHospital ownership statusIntensive care capabilities
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
2017
Systolic Blood Pressure Response in SPRINT (Systolic Blood Pressure Intervention Trial) and ACCORD (Action to Control Cardiovascular Risk in Diabetes): A Possible Explanation for Discordant Trial Results
Huang C, Dhruva SS, Coppi AC, Warner F, Li S, Lin H, Nasir K, Krumholz HM. Systolic Blood Pressure Response in SPRINT (Systolic Blood Pressure Intervention Trial) and ACCORD (Action to Control Cardiovascular Risk in Diabetes): A Possible Explanation for Discordant Trial Results. Journal Of The American Heart Association 2017, 6: e007509. PMID: 29133522, PMCID: PMC5721802, DOI: 10.1161/jaha.117.007509.Peer-Reviewed Original ResearchConceptsSystolic blood pressure responseBlood pressure responseTreatment groupsCause deathVisit variabilityDiscordant trialsBlood pressure trialStandard treatment groupPressure responseACCORD participantsPressure trialSBP responseHeart failureMean SBPPrimary outcomeSBPDiscordant resultsMean differenceSimilar interventionsTrial resultsTrialsSimilar mean differencesTreatment effectsSignificant differencesStrokeHeterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial)
Dhruva SS, Huang C, Spatz ES, Coppi AC, Warner F, Li SX, Lin H, Xu X, Furberg CD, Davis BR, Pressel SL, Coifman RR, Krumholz HM. Heterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial). Hypertension 2017, 70: 94-102. PMID: 28559399, DOI: 10.1161/hypertensionaha.117.09221.Peer-Reviewed Original ResearchConceptsAntihypertensive therapySystolic blood pressure responseAdverse cardiovascular eventsFavorable initial responseBlood pressure responseHigher hazard ratioCardiovascular eventsCardiovascular outcomesHazard ratioMultivariable adjustmentHeart failureAverage SBPRandomized trialsOdds ratioCardiovascular diseaseSBPStudy participantsRespondersMonthsPressure responseImmediate respondersALLHATEarly responseInitial responseSuperior discrimination
2016
Analysis of Machine Learning Techniques for Heart Failure Readmissions
Mortazavi BJ, Downing NS, Bucholz EM, Dharmarajan K, Manhapra A, Li SX, Negahban SN, Krumholz HM. Analysis of Machine Learning Techniques for Heart Failure Readmissions. Circulation Cardiovascular Quality And Outcomes 2016, 9: 629-640. PMID: 28263938, PMCID: PMC5459389, DOI: 10.1161/circoutcomes.116.003039.Peer-Reviewed Original ResearchTreatment for Multiple Acute Cardiopulmonary Conditions in Older Adults Hospitalized with Pneumonia, Chronic Obstructive Pulmonary Disease, or Heart Failure
Dharmarajan K, Strait KM, Tinetti ME, Lagu T, Lindenauer PK, Lynn J, Krukas MR, Ernst FR, Li SX, Krumholz HM. Treatment for Multiple Acute Cardiopulmonary Conditions in Older Adults Hospitalized with Pneumonia, Chronic Obstructive Pulmonary Disease, or Heart Failure. Journal Of The American Geriatrics Society 2016, 64: 1574-1582. PMID: 27448329, PMCID: PMC4988873, DOI: 10.1111/jgs.14303.Peer-Reviewed Original ResearchMeSH KeywordsAdrenal Cortex HormonesAgedAged, 80 and overAnti-Bacterial AgentsCardiotonic AgentsCohort StudiesComorbidityCross-Sectional StudiesDiureticsDrug Therapy, CombinationFemaleHeart FailureHospitalizationHumansMalePneumoniaPulmonary Disease, Chronic ObstructiveRetrospective StudiesUnited StatesVasodilator AgentsConceptsChronic obstructive pulmonary diseaseAcute cardiopulmonary conditionsObstructive pulmonary diseaseHeart failureCardiopulmonary conditionsOlder adultsPulmonary diseasePremier Research DatabaseEpisodes of pneumoniaRetrospective cohort studyReal-world treatmentHF hospitalizationCohort studyHospital daysPneumonia hospitalizationsCOPD hospitalizationsClinical syndromeAcute conditionsPneumoniaDiagnostic uncertaintyResearch DatabaseHospitalizationDiagnostic categoriesU.S. hospitalsAdultsChina Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction: Study Design
Li J, Dreyer RP, Li X, Du X, Downing NS, Li L, Zhang HB, Feng F, Guan WC, Xu X, Li SX, Lin ZQ, Masoudi FA, Spertus JA, Krumholz HM, Jiang LX, Group T. China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction: Study Design. Chinese Medical Journal 2016, 129: 72-80. PMID: 26712436, PMCID: PMC4797546, DOI: 10.4103/0366-6999.172596.Peer-Reviewed Original ResearchConceptsPatient-reported outcomesAcute myocardial infarctionChina PatientMedical historyMyocardial infarctionPatient experienceLong-term adverse eventsRisk factor controlConsecutive AMI patientsAMI studyPatient's medical historyQuality of lifeNational Coordinating CentreQuality improvement activitiesHospital outcomesCardiac eventsPatient demographicsAdverse eventsMedical chartsHealthcare utilizationAMI patientsMedication adherenceProspective studyHospitalization eventsRisk factors
2015
Hospital variation in admission to intensive care units for patients with acute myocardial infarction
Chen R, Strait KM, Dharmarajan K, Li SX, Ranasinghe I, Martin J, Fazel R, Masoudi FA, Cooke CR, Nallamothu BK, Krumholz HM. Hospital variation in admission to intensive care units for patients with acute myocardial infarction. American Heart Journal 2015, 170: 1161-1169. PMID: 26678638, PMCID: PMC5459386, DOI: 10.1016/j.ahj.2015.09.003.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAnterior Wall Myocardial InfarctionCoronary Care UnitsHealth Care RationingHospital MortalityHumansLength of StayMaleMiddle AgedOutcome and Process Assessment, Health CarePatient AdmissionQuality ImprovementRetrospective StudiesRisk AssessmentTriageUnited StatesConceptsAcute myocardial infarctionIntensive care unitCritical care therapiesRisk-standardized mortality ratesHospital risk-standardized mortality ratesICU admissionResource-intensive settingsCare therapyAMI patientsCare unitMyocardial infarctionMortality rateAdult hospitalizationsHospital variationNinth RevisionClinical ModificationICU triageInternational ClassificationBetter outcomesPatientsHospitalAdmissionPremier databaseTherapyAppropriate useHospital Variability in Use of Anticoagulant Strategies During Acute Myocardial Infarction Treated With an Early Invasive Strategy
Arnold SV, Li SX, Alexander KP, Spertus JA, Nallamothu BK, Curtis JP, Kosiborod M, Gupta A, Wang TY, Lin H, Dharmarajan K, Strait KM, Lowe TJ, Krumholz HM. Hospital Variability in Use of Anticoagulant Strategies During Acute Myocardial Infarction Treated With an Early Invasive Strategy. Journal Of The American Heart Association 2015, 4: e002009. PMID: 26077589, PMCID: PMC4599539, DOI: 10.1161/jaha.115.002009.Peer-Reviewed Original ResearchConceptsEarly invasive strategyAnticoagulant strategiesMyocardial infarctionBleeding rateInvasive strategyAcute myocardial infarction patientsOptimal anticoagulant strategyHalf of patientsPercutaneous coronary interventionAcute myocardial infarctionMyocardial infarction patientsHospital use patternsComparative effectiveness studiesRisk-standardized mortalityChoice of anticoagulantsMedian odds ratioCoronary interventionPatient factorsSystemic anticoagulationHospital variabilityInfarction patientsPrincipal diagnosisOdds ratioMultivariate regression modelPatterns of use