2021
Performance Metrics for the Comparative Analysis of Clinical Risk Prediction Models Employing Machine Learning
Huang C, Li SX, Caraballo C, Masoudi FA, Rumsfeld JS, Spertus JA, Normand ST, Mortazavi BJ, Krumholz HM. Performance Metrics for the Comparative Analysis of Clinical Risk Prediction Models Employing Machine Learning. Circulation Cardiovascular Quality And Outcomes 2021, 14: e007526. PMID: 34601947, DOI: 10.1161/circoutcomes.120.007526.Peer-Reviewed Original ResearchSARS-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
Surgeons: Buyer beware—does “universal” risk prediction model apply to patients universally?
Mori M, Shahian DM, Huang C, Li SX, Normand ST, Geirsson A, Krumholz HM. Surgeons: Buyer beware—does “universal” risk prediction model apply to patients universally? Journal Of Thoracic And Cardiovascular Surgery 2020, 160: 176-179.e2. PMID: 32241616, DOI: 10.1016/j.jtcvs.2019.11.144.Peer-Reviewed Original Research
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
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 ResearchThe china patient‐centered evaluative assessment of cardiac events (PEACE) prospective study of percutaneous coronary intervention: Study design
Du X, Pi Y, Dreyer RP, Li J, Li X, Downing NS, Li L, Feng F, Zhan L, Zhang H, Guan W, Xu X, Li S, Lin Z, Masoudi FA, Spertus JA, Krumholz HM, Jiang L, Group F. The china patient‐centered evaluative assessment of cardiac events (PEACE) prospective study of percutaneous coronary intervention: Study design. Catheterization And Cardiovascular Interventions 2016, 88: e212-e221. PMID: 26945565, PMCID: PMC5215582, DOI: 10.1002/ccd.26461.Peer-Reviewed Original ResearchMeSH KeywordsChinaClinical ProtocolsCoronary AngiographyHealth StatusHealthcare DisparitiesHumansMedication AdherenceMyocardial InfarctionPatient Reported Outcome MeasuresPatient-Centered CarePercutaneous Coronary InterventionPredictive Value of TestsProspective StudiesResearch DesignRisk AssessmentRisk FactorsSecondary PreventionTime FactorsTreatment OutcomeConceptsPercutaneous coronary interventionPatient-reported outcomesCardiovascular risk factor controlRisk factor controlProspective studyHealth statusMedical historyLong-term clinical outcomesLong-term patient outcomesHospital-level factorsIndependent core laboratoryNationwide prospective studyLong-term outcomesPatient's medical historyHospital outcomesCoronary interventionPatient demographicsSecondary preventionConsecutive patientsMedical chartsPCI indicationPrimary outcomeClinical outcomesClinical presentationHealthcare utilization
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 use
2014
National Patterns of Risk-Standardized Mortality and Readmission After Hospitalization for Acute Myocardial Infarction, Heart Failure, and Pneumonia: Update on Publicly Reported Outcomes Measures Based on the 2013 Release
Suter LG, Li SX, Grady JN, Lin Z, Wang Y, Bhat KR, Turkmani D, Spivack SB, Lindenauer PK, Merrill AR, Drye EE, Krumholz HM, Bernheim SM. National Patterns of Risk-Standardized Mortality and Readmission After Hospitalization for Acute Myocardial Infarction, Heart Failure, and Pneumonia: Update on Publicly Reported Outcomes Measures Based on the 2013 Release. Journal Of General Internal Medicine 2014, 29: 1333-1340. PMID: 24825244, PMCID: PMC4175654, DOI: 10.1007/s11606-014-2862-5.Peer-Reviewed Original ResearchConceptsRisk-standardized mortality ratesAcute myocardial infarctionHeart failurePneumonia mortalityMyocardial infarctionMedian risk-standardized mortality rateHospital-level mortalityUnplanned readmission ratePrincipal discharge diagnosisHospital performanceRisk-Standardized MortalityHF mortalityReadmission resultsReadmission ratesDischarge diagnosisOutcome measuresAMI mortalityReadmission measuresPneumoniaMortality rateService MedicareHierarchical logistic modelsMortalityMedicaid ServicesReadmission
2013
Dominance of Furosemide for Loop Diuretic Therapy in Heart Failure Time to Revisit the Alternatives?
Bikdeli B, Strait KM, Dharmarajan K, Partovian C, Coca SG, Kim N, Li SX, Testani JM, Khan U, Krumholz HM. Dominance of Furosemide for Loop Diuretic Therapy in Heart Failure Time to Revisit the Alternatives? Journal Of The American College Of Cardiology 2013, 61: 1549-1550. PMID: 23500272, PMCID: PMC4038646, DOI: 10.1016/j.jacc.2012.12.043.Peer-Reviewed Original Research
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