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
Hospital Phenotypes in the Management of Patients Admitted for Acute Myocardial Infarction
Xu X, Li SX, Lin H, Normand SL, Lagu T, Desai N, Duan M, Kroch EA, Krumholz HM. Hospital Phenotypes in the Management of Patients Admitted for Acute Myocardial Infarction. Medical Care 2016, 54: 929-936. PMID: 27261637, PMCID: PMC5305177, DOI: 10.1097/mlr.0000000000000571.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionPercutaneous coronary interventionICU admission rateICU admissionMyocardial infarctionAdmission ratesProcedure ratesIntensive care unit admissionHigher ICU admissionLower ICU admissionCare unit admissionCoronary artery bypassPatients' clinical characteristicsManagement of patientsOpen heart surgeryRisk-standardized mortalityArtery bypassUnit admissionClinical characteristicsCoronary interventionReadmission ratesGroup of hospitalsHospital costsPractice patternsCABGThe 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 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