2023
Contemporary Methods for Predicting Acute Kidney Injury After Coronary Intervention
Uzendu A, Kennedy K, Chertow G, Amin A, Giri J, Rymer J, Bangalore S, Lavin K, Anderson C, Wang T, Curtis J, Spertus J. Contemporary Methods for Predicting Acute Kidney Injury After Coronary Intervention. JACC Cardiovascular Interventions 2023, 16: 2294-2305. PMID: 37758384, PMCID: PMC10795198, DOI: 10.1016/j.jcin.2023.07.041.Peer-Reviewed Original ResearchConceptsAcute kidney injuryPercutaneous coronary interventionValidation cohortKidney injuryCoronary interventionClinical careIncidence of AKIBedside risk scoreBaseline renal functionNCDR CathPCI RegistryLogistic regression modelsAKI riskNew dialysisAKI predictionCathPCI RegistryRenal functionCommon complicationDerivation cohortMedian ageAKI modelClinical instabilityPCI proceduresC-statisticPatient riskContrast doses
2019
Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention
Mortazavi BJ, Bucholz EM, Desai NR, Huang C, Curtis JP, Masoudi FA, Shaw RE, Negahban SN, Krumholz HM. Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention. JAMA Network Open 2019, 2: e196835. PMID: 31290991, PMCID: PMC6624806, DOI: 10.1001/jamanetworkopen.2019.6835.Peer-Reviewed Original ResearchConceptsPercutaneous coronary interventionMajor bleedingC-statisticCoronary interventionMAIN OUTCOMEIndex percutaneous coronary interventionSubsequent coronary artery bypassPercutaneous coronary intervention (PCI) proceduresHospital major bleedingMajor bleeding ratesNationwide clinical registryCoronary artery bypassCoronary intervention proceduresComparative effectiveness studiesRisk score modelComplexity of presentationMean c-statisticCoronary angiography dataRegistry modelNCDR modelsArtery bypassBleeding eventsPrediction of riskClinical variablesBleeding rate
2016
Development and validation of a simple risk score to predict 30‐day readmission after percutaneous coronary intervention in a cohort of medicare patients
Minges KE, Herrin J, Fiorilli PN, Curtis JP. Development and validation of a simple risk score to predict 30‐day readmission after percutaneous coronary intervention in a cohort of medicare patients. Catheterization And Cardiovascular Interventions 2016, 89: 955-963. PMID: 27515069, PMCID: PMC5397364, DOI: 10.1002/ccd.26701.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlgorithmsDecision Support TechniquesFemaleHumansLogistic ModelsMaleMedicareMultivariate AnalysisOdds RatioPatient ReadmissionPercutaneous Coronary InterventionPredictive Value of TestsRegistriesReproducibility of ResultsRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeUnited StatesConceptsRisk of readmissionPCI patientsRisk scoreMultivariable logistic regression modelRisk score developmentDays of dischargeSimple risk scoreTime of dischargeModel c-statisticLogistic regression modelsStepwise selection modelCathPCI RegistryHospital dischargeReadmission ratesClinical factorsRevascularization proceduresValidation cohortC-statisticReadmissionHigh riskMedicare feeLower riskService claimsPatientsCohort