2024
Characterizing the progression of subclinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms
Oikonomou E, Sangha V, Coppi A, Krumholz H, Miller E, Khera R. Characterizing the progression of subclinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms. European Heart Journal 2024, 45: ehae666.2089. DOI: 10.1093/eurheartj/ehae666.2089.Peer-Reviewed Original ResearchDiagnosis of ATTR-CMATTR-CMBone scintigraphy scansClinical diagnosisTransthyretin amyloid cardiomyopathyMonths of diagnosisSex-matched controlsElectrocardiographic (ECGIndolent courseCardiac amyloidosisScintigraphy scanAmyloid cardiomyopathyEchocardiographic studiesAI-ECGEchocardiogramEventual diagnosisDetect longitudinal changesConfirmatory testDiagnosisClinical diseasePercentage of individualsLongitudinal changesECGMedianMonths
2011
Improvements in Door-to-Balloon Time in the United States, 2005 to 2010
Krumholz HM, Herrin J, Miller LE, Drye EE, Ling SM, Han LF, Rapp MT, Bradley EH, Nallamothu BK, Nsa W, Bratzler DW, Curtis JP. Improvements in Door-to-Balloon Time in the United States, 2005 to 2010. Circulation 2011, 124: 1038-1045. PMID: 21859971, PMCID: PMC3598634, DOI: 10.1161/circulationaha.111.044107.Peer-Reviewed Original ResearchConceptsPrimary percutaneous coronary interventionPercutaneous coronary interventionBalloon timeCoronary interventionMedian timeST-segment elevation myocardial infarctionHigher median timeCharacteristics of patientsPercentage of patientsTimeliness of treatmentYears of ageRegistry studyMyocardial infarctionInpatient measuresPatientsHospital groupMedicaid ServicesCalendar yearInterventionMinutesMedianGroupYearsPercentageInfarction