Featured Publications
Inter-Rater Reliability for the Amputation Endpoint in the National Vascular Quality Initiative
Smolderen K, Romain G, Scierka L, Cleman J, Rahman M, Siddiqui W, Lau F, Mao J, Akhlaghi N, Higaki A, Fowler X, Carroll M, Telma K, Alvermann T, Baribeau V, Goodney P, Mena-Hurtado C. Inter-Rater Reliability for the Amputation Endpoint in the National Vascular Quality Initiative. JACC Cardiovascular Interventions 2024, 17: 622-631. PMID: 38479964, DOI: 10.1016/j.jcin.2024.01.003.Peer-Reviewed Original ResearchConceptsElectronic health recordsElectronic health record reviewAmputation dataPeripheral arterial diseaseInterrater reliabilityVQI registryAcademic health systemTrained data collectorsNational quality registryInter-rater reliabilityEvaluate interrater reliabilityNational reporting systemHealth recordsQuality registryHealth systemCurrent Procedural Terminology codesInter-raterVascular Quality Initiative registryVascular Quality InitiativeProcedural Terminology codesNational Vascular Quality InitiativeRegistryQuality InitiativeAmputationSpearman's r
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 ResearchMeSH KeywordsAcute Kidney InjuryAgedContrast MediaCreatinineFemaleHumansMaleModels, StatisticalPercutaneous Coronary InterventionReproducibility of ResultsRisk AssessmentRisk FactorsConceptsCreatinine 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