Defining a set of patient attributes that predict exercise performance outcome following an exercise training program in a population of coronary artery disease patients

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dc.contributor.authorPierson, Lee M.en
dc.contributor.departmentHealth and Physical Educationen
dc.date.accessioned2014-03-14T21:48:43Zen
dc.date.adate2008-11-01en
dc.date.available2014-03-14T21:48:43Zen
dc.date.issued1996en
dc.date.rdate2008-11-01en
dc.date.sdate2008-11-01en
dc.description.abstractThe purpose of this study was to evaluate the utility of baseline clinical and graded exercise test (GXT) variables in predicting exercise training outcome in cardiac rehabilitation patients. Data were extracted from the records of 60 cardiac patients who had participated in a community-based exercise program for 5-9 months. Two separate markers of exercise tolerance were used to evaluate training effect: 1) rate-pressure product at a submaximal reference workload of 5 METs (RPPSMETs), and 2) estimated peak METs (pkMETs). These two markers of exercise tolerance were found to have a low correlation (r = -0.29). Patients were classified into one of three possible outcome categories for each marker of exercise tolerance, i.e., improvement, no change, or decline. Thresholds for classifying patients into improvement or decline groups were ± 10% for the RPPSMETs marker and ± 1 MET for the pkKMETs marker. Outcome classifications using the RPPSMETs marker were as follows: improvement, 37 (62%); no change, 13 (22%); decline, 10 (17%). Use of the pkKMETs marker to classify patients into outcome groups yielded: improvement, 45 (75%); no change, 15 (25%); with no patients classified in the decline group. Multiple logistic regression was used to identify patient attributes predictive of improvement and decline for each exercise tolerance marker. Baseline variables were found to yield a model highly predictive of improvement in RPPSMETs (correct classification rate = 87%; sensitivity = 92%; specificity = 78%). The best single predictor of improvement outcome was high baseline RPPS5MET values. A model could not be generated to successfully predict decline in exercise tolerance. Baseline variables selected for prediction of improvement outcome, as defined by pkMETs marker, yielded a model with limited utility due to low specificity (correct classification rate = 87%; sensitivity = 96%; specificity = 60%).en
dc.description.degreeMaster of Scienceen
dc.format.extentix, 127 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-11012008-063510en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11012008-063510/en
dc.identifier.urihttp://hdl.handle.net/10919/45411en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V855_1996.P527.pdfen
dc.relation.isformatofOCLC# 36436271en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectExerciseen
dc.subjectcardiacen
dc.subjecttrainingen
dc.subjectoutcomeen
dc.subjectrehabilitationen
dc.subject.lccLD5655.V855 1996.P527en
dc.titleDefining a set of patient attributes that predict exercise performance outcome following an exercise training program in a population of coronary artery disease patientsen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineHealth and Physical Educationen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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