Featured Publications
Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment
Herrin J, Abraham NS, Yao X, Noseworthy PA, Inselman J, Shah ND, Ngufor C. Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment. JAMA Network Open 2021, 4: e2110703. PMID: 34019087, PMCID: PMC8140376, DOI: 10.1001/jamanetworkopen.2021.10703.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overAnticoagulantsAntifibrinolytic AgentsAtrial FibrillationClinical Decision-MakingCohort StudiesCross-Sectional StudiesFemaleFibrinolytic AgentsGastrointestinal HemorrhageHumansMachine LearningMaleMiddle AgedMyocardial IschemiaPredictive Value of TestsRetrospective StudiesRisk AssessmentThienopyridinesUnited StatesVenous ThromboembolismYoung AdultConceptsGastrointestinal bleedingIschemic heart diseaseCross-sectional studyThienopyridine antiplatelet agentAntithrombotic treatmentVenous thromboembolismAntiplatelet agentsRandom survival forestStudy cohortAtrial fibrillationValidation cohortHeart diseaseHAS-BLED risk scoreRetrospective cross-sectional studyCox proportional hazards regressionHAS-BLED scorePrior GI bleedPatients 18 yearsCohort of patientsEntire study cohortProportional hazards regressionOptumLabs Data WarehouseMedicare Advantage enrolleesPositive predictive valueRisk prediction model
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