2024
Artificial intelligence applied to electrocardiographic images for scalable screening of cardiac amyloidosis
Sangha V, Oikonomou E, Krumholz H, Miller E, Khera R. Artificial intelligence applied to electrocardiographic images for scalable screening of cardiac amyloidosis. European Heart Journal 2024, 45: ehae666.3436. DOI: 10.1093/eurheartj/ehae666.3436.Peer-Reviewed Original ResearchATTR-CMBone scintigraphy scansTransthyretin amyloid cardiomyopathyPositive predictive valueAI-ECG algorithmCardiac amyloidosisScintigraphy scanAmyloid cardiomyopathyAI-ECGSex-matchedDevelopment cohortMyocardial remodelingUnder-diagnosedUnder-treatedMatched controlsPredictive valueUnder-recognizedTransthyretin stabilizersConvolutional neural networkPatientsECGArtificial intelligenceHospitalPrevalenceTransthyretin
2023
Reclassification of moderate aortic stenosis based on data-driven phenotyping of hemodynamic progression
Cho I, Kim W, Kim S, Ko K, Seong Y, Kim D, Seo J, Shim C, Ha J, Mori M, Gupta A, You S, Hong G, Krumholz H. Reclassification of moderate aortic stenosis based on data-driven phenotyping of hemodynamic progression. Scientific Reports 2023, 13: 6694. PMID: 37095171, PMCID: PMC10125992, DOI: 10.1038/s41598-023-33683-1.Peer-Reviewed Original ResearchConceptsRapid progression groupModerate aortic stenosisAortic valve replacementSlow progression groupAortic stenosisProgression groupHemodynamic progressionRapid progressionMore rapid progressionLatent class trajectory modelingTransthoracic echocardiography studyBetween-group differencesData-driven phenotypingPressure gradient measurementAVR ratesModerate ASCause mortalityValve replacementEchocardiography studyAtrial fibrillationTTE studiesEchocardiographic dataRisk factorsPredictive valuePatients
2015
Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data
Horwitz LI, Grady JN, Cohen DB, Lin Z, Volpe M, Ngo CK, Masica AL, Long T, Wang J, Keenan M, Montague J, Suter LG, Ross JS, Drye EE, Krumholz HM, Bernheim SM. Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data. Journal Of Hospital Medicine 2015, 10: 670-677. PMID: 26149225, PMCID: PMC5459369, DOI: 10.1002/jhm.2416.Peer-Reviewed Original ResearchConceptsSame-hospital readmissionsNegative predictive valuePositive predictive valuePredictive valueReadmission measuresHospital-wide readmission measureGold standard chart reviewAdministrative claims-based algorithmDiagnostic cardiac catheterizationClaims-based algorithmLarge teaching centersAcute care hospitalsSmall community hospitalUnplanned readmissionChart reviewCardiac catheterizationScheduled careSpecificity 96.5Community hospitalReadmissionClaims dataCardiac devicesHealth systemTeaching centerPublic reporting
1997
Validation of a clinical prediction rule for left ventricular ejection fraction after myocardial infarction in patients ≥ 65 years old
Krumholz H, Howes C, Murillo J, Vaccarino L, Radford M, Ellerbeck E. Validation of a clinical prediction rule for left ventricular ejection fraction after myocardial infarction in patients ≥ 65 years old. The American Journal Of Cardiology 1997, 80: 11-15. PMID: 9205012, DOI: 10.1016/s0002-9149(97)00299-3.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCohort StudiesConnecticutEchocardiographyElectrocardiographyFemaleHumansMaleMedicareMultivariate AnalysisMyocardial InfarctionPilot ProjectsPredictive Value of TestsRetrospective StudiesRisk FactorsStroke VolumeTreatment OutcomeUnited StatesVentricular Function, LeftConceptsLeft ventricular ejection fractionAcute myocardial infarctionClinical prediction ruleVentricular ejection fractionPositive predictive valuePrediction ruleElderly patientsEjection fractionMyocardial infarctionExclusion criteriaPredictive valueEligible elderly patientsRetrospective chart reviewConnecticut cohortChest painBypass surgeryChart reviewDiabetes mellitusMedicare patientsPatientsPilot studyMultivariate modelInfarctionElectrocardiogram interpretationOriginal study