2024
Racial 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, 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 ageHypertension 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
2021
Disparities in Excess Mortality Associated with COVID-19 — United States, 2020
Rossen LM, Ahmad FB, Anderson RN, Branum AM, Du C, Krumholz HM, Li SX, Lin Z, Marshall A, Sutton PD, Faust JS. Disparities in Excess Mortality Associated with COVID-19 — United States, 2020. MMWR Morbidity And Mortality Weekly Report 2021, 70: 1114-1119. PMID: 34411075, PMCID: PMC8375709, DOI: 10.15585/mmwr.mm7033a2.Peer-Reviewed Original ResearchConceptsMortality incidence ratesIncidence rateExcess mortalityAge groupsHighest excess mortality ratesExcess Mortality AssociatedGreater excess mortalityExcess mortality ratesAI/AN populationsNon-Hispanic American IndianNon-Hispanic blacksNational Vital Statistics SystemCOVID-19 pandemicPublic health messagingNon-Hispanic white populationRace/ethnicityVital Statistics SystemMortality AssociatedLack of adjustmentMortality rateExcess deathsAN populationsEthnic groupsHealth messagingHispanic personsDelays 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 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 OUTCOMEAssociation 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
Heterogeneity 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 Research
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 useIntravenous Fluids in Acute Decompensated Heart Failure
Bikdeli B, Strait KM, Dharmarajan K, Li SX, Mody P, Partovian C, Coca SG, Kim N, Horwitz LI, Testani JM, Krumholz HM. Intravenous Fluids in Acute Decompensated Heart Failure. JACC Heart Failure 2015, 3: 127-133. PMID: 25660836, PMCID: PMC4438991, DOI: 10.1016/j.jchf.2014.09.007.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overCohort StudiesDatabases, FactualFemaleFluid TherapyHeart FailureHospital MortalityHospitalizationHumansInfusions, IntravenousIntensive Care UnitsIntubation, IntratrachealIsotonic SolutionsMaleMiddle AgedRenal Replacement TherapyRetrospective StudiesRinger's SolutionSaline Solution, HypertonicSodium Potassium Chloride Symporter InhibitorsUnited StatesYoung AdultConceptsAcute decompensated heart failureDecompensated heart failureHeart failureIntravenous fluidsRetrospective cohort studyCritical care admissionRenal replacement therapyDays of hospitalizationProportion of hospitalizationsHalf-normal salineWarrants further investigationOnly diureticsCare admissionHospital deathHospital outcomesCohort studyLoop diureticsPatient groupReplacement therapyWorse outcomesNormal salineInpatient careMedian volumePatientsHospitalization
2013
Acute Decompensated Heart Failure Is Routinely Treated as a Cardiopulmonary Syndrome
Dharmarajan K, Strait KM, Lagu T, Lindenauer PK, Tinetti ME, Lynn J, Li SX, Krumholz HM. Acute Decompensated Heart Failure Is Routinely Treated as a Cardiopulmonary Syndrome. PLOS ONE 2013, 8: e78222. PMID: 24250751, PMCID: PMC3824040, DOI: 10.1371/journal.pone.0078222.Peer-Reviewed Original ResearchConceptsDecompensated heart failureHeart failureRespiratory therapyHospital daysCardiopulmonary syndromeAcute decompensated heart failureAcute heart failure treatmentChronic obstructive pulmonary diseaseReceipt of medicationHeart failure hospitalizationHigh-dose corticosteroidsHospital day 2Hospital day 3Half of patientsChronic lung diseaseDays of hospitalizationHeart failure treatmentObstructive pulmonary diseaseShortness of breathIntensive care unitPrincipal discharge diagnosisLate intubationAcute asthmaFailure hospitalizationHospital death
2012
Procedure Intensity and the Cost of Care
Chen SI, Dharmarajan K, Kim N, Strait KM, Li SX, Safavi KC, Lindenauer PK, Krumholz HM, Lagu T. Procedure Intensity and the Cost of Care. Circulation Cardiovascular Quality And Outcomes 2012, 5: 308-313. PMID: 22576844, PMCID: PMC3415230, DOI: 10.1161/circoutcomes.112.966069.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overCosts and Cost AnalysisCross-Sectional StudiesFemaleHeart FailureHospital Bed CapacityHospital CostsHospital MortalityHospitalizationHospitals, RuralHospitals, TeachingHospitals, UrbanHumansLength of StayLinear ModelsMaleMiddle AgedModels, EconomicOutcome and Process Assessment, Health CareResidence CharacteristicsRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeUnited StatesYoung AdultConceptsHF hospitalizationHeart failureInvasive proceduresHospital groupRisk-standardized mortality ratesProportion of patientsLength of stayCost of careWilcoxon rank sum testHigher procedure ratesRank sum testPatient demographicsPerspective databaseMedian lengthSurgical proceduresProcedure ratesHospitalizationOutcome differencesMortality rateHospitalPatientsPractice styleProcedure useSum testOverall use
2011
Long-term Trends in Short-term Outcomes in Acute Myocardial Infarction
Nguyen HL, Saczynski JS, Gore JM, Waring ME, Lessard D, Yarzebski J, Reed G, Spencer FA, Li SX, Goldberg RJ. Long-term Trends in Short-term Outcomes in Acute Myocardial Infarction. The American Journal Of Medicine 2011, 124: 939-946. PMID: 21962314, PMCID: PMC3185241, DOI: 10.1016/j.amjmed.2011.05.023.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionShort-term outcomesOlder patientsAtrial fibrillationMyocardial infarctionAdverse short-term outcomesGreater Worcester medical centersShort-term death ratesShort-term mortality rateMen 75 yearsShort-term mortalityTargeted treatment approachCardiogenic shockHeart failureMajor complicationsAge differencesElderly menMedical CenterStudy populationMortality rateTreatment approachesPatientsDeath rateFemale residentsWomen