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 cohortQuantifying the utilization of medical devices necessary to detect postmarket safety differences: A case study of implantable cardioverter defibrillators
Bates J, Parzynski CS, Dhruva SS, Coppi A, Kuntz R, Li S, Marinac‐Dabic D, Masoudi FA, Shaw RE, Warner F, Krumholz HM, Ross JS. Quantifying the utilization of medical devices necessary to detect postmarket safety differences: A case study of implantable cardioverter defibrillators. Pharmacoepidemiology And Drug Safety 2018, 27: 848-856. PMID: 29896873, PMCID: PMC6436550, DOI: 10.1002/pds.4565.Peer-Reviewed Original ResearchConceptsAdverse event ratesSafety differencesEvent ratesMedical device utilizationICD utilizationRate ratioNational Cardiovascular Data RegistryICD modelsImplantable cardioverter defibrillatorEvent rate ratioMost patientsCardioverter defibrillatorProportion of individualsAmerican CollegeData registryRoutine surveillanceSample size estimatesAverage event rateDevice utilizationSignificance levelDifferencesPatientsRegistryDefibrillatorICD
2014
Hospital Variation in Intravenous Inotrope Use for Patients Hospitalized With Heart Failure
Allen LA, Fonarow GC, Grau-Sepulveda MV, Hernandez AF, Peterson PN, Partovian C, Li SX, Heidenreich PA, Bhatt DL, Peterson ED, Krumholz HM. Hospital Variation in Intravenous Inotrope Use for Patients Hospitalized With Heart Failure. Circulation Heart Failure 2014, 7: 251-260. PMID: 24488983, PMCID: PMC5459367, DOI: 10.1161/circheartfailure.113.000761.Peer-Reviewed Original ResearchMeSH KeywordsAgedCardiotonic AgentsCross-Sectional StudiesDose-Response Relationship, DrugFemaleFollow-Up StudiesGuideline AdherenceHeart FailureHospital MortalityHospitalsHumansInfusions, IntravenousInpatientsLength of StayMaleOutcome Assessment, Health CarePractice Patterns, Physicians'RegistriesRetrospective StudiesSurvival RateUnited StatesConceptsInotrope useHeart failureInotropic therapyInotropic agentsGuidelines-Heart Failure registryIntravenous inotropic agentsIntravenous inotropic therapyRisk-standardized ratesUse of inotropesHeart failure hospitalizationHospital-level ratesRandom hospital effectsFailure hospitalizationClinical characteristicsHospital factorsInpatient mortalityClinical factorsClinical outcomesHospital variationHospital characteristicsHospital effectsPatientsUS hospitalsHospitalStudy period