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

Abstract

dc:description.abstract

The 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%).

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Health and Physical Education
Department dc:contributor.department
Health and Physical Education
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
1996

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Pierson, Lee M.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
etd-11012008-063510
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/45411

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Pierson, Lee M.. Defining a set of patient attributes that predict exercise performance outcome following an exercise training program in a population of coronary artery disease patients. masters thesis, Virginia Tech, 1996. http://hdl.handle.net/10919/45411