2024
Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure
Adejumo P, Thangaraj P, Dhingra L, Aminorroaya A, Zhou X, Brandt C, Xu H, Krumholz H, Khera R. Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure. JAMA Network Open 2024, 7: e2443925. PMID: 39509128, PMCID: PMC11544492, DOI: 10.1001/jamanetworkopen.2024.43925.Peer-Reviewed Original ResearchConceptsFunctional status assessmentArea under the receiver operating characteristic curveClinical documentationElectronic health record dataHF symptomsOptimal care deliveryHealth record dataAssess functional statusStatus assessmentClinical trial participationProcessing of clinical documentsFunctional status groupCare deliveryOutpatient careMain OutcomesMedical notesTrial participantsNew York Heart AssociationFunctional statusQuality improvementRecord dataHeart failureClinical notesDiagnostic studiesStatus groups
2003
Depressive symptoms are the strongest predictors of short-term declines in health status in patients with heart failure
Rumsfeld JS, Havranek E, Masoudi FA, Peterson ED, Jones P, Tooley JF, Krumholz HM, Spertus JA, Consortium C. Depressive symptoms are the strongest predictors of short-term declines in health status in patients with heart failure. Journal Of The American College Of Cardiology 2003, 42: 1811-1817. PMID: 14642693, DOI: 10.1016/j.jacc.2003.07.013.Peer-Reviewed Original ResearchConceptsKansas City Cardiomyopathy QuestionnaireKCCQ summary scoreDepressive symptomsQuality of lifeHealth statusKCCQ scoresHeart failureDepressed patientsSummary scoresMulticenter prospective cohort studyStrongest predictorBaseline KCCQ scoresProspective cohort studySignificant depressive symptomsSpecific health statusTreatment of depressionShort-term worseningPredictors of changeHF careHF symptomsCohort studyPrimary outcomePotential confoundersPatient variablesMultivariable model