Title page for ETD etd-63198-9314

Type of Document Master's Thesis
Author Fabiato, Francois Stephane
Author's Email Address arizk@co.hanover.va.us
URN etd-63198-9314
Title Predicting physical fitness outcomes of exercise rehabilitation: An retrospective examination of program admission data from patient records in a hospital-based early outpatient cardiac rehabilitation program
Degree Master of Science
Department Health and Physical Education
Advisory Committee
Advisor Name Title
Herbert, William G. Committee Chair
Baffi, Charles R. Committee Member
Griffith, Parks Committee Member
  • Cardiac Rehabilitation
  • outcome-based research
  • predictor variables
Date of Defense 1998-03-01
Availability unrestricted



Francois S. Fabiato


Economic justification for rehabilitative services has resulted

in the need for outcome based research which could quantify success

or failure in individual patients and formulate baseline

variables which could predict outcomes. The purpose of this

study is to investigate the utilization of baseline clinical,

exercise test, and psychosocial variables to predict clinically

relevant changes in exercise tolerance of cardiac patients who

participated in early outpatient cardiac rehabilitation. Clinical

records were analyzed retrospectively to obtain clinical, psychosocial

and exercise test data for 94 patients referred to an early

outpatient cardiac rehabilitation program at a large urban hospital

in the Southeast US. All patients participated in supervised exercise

training 3d/wk for 2-3 months. A standardized training outcome score

STO) was devised to evaluate training effect by tabulating changes

in patients predicted VO2, body weight and exercising heart rates

after 8-12 weeks of exercise based cardiac rehabilitation.

STO = Predicted VO2 change + BW change- HR change. The Multi-Factorial

Analysis was applied to derive coefficients in the STO formula so

that the STO scores reflected the independent effects of BW, HR

and Predicted V02 changes on training outcome. Patients were

classified into one of three possible outcome categories based on

STO scores, i.e. improvement, no change, or decline. Thresholds

for classifying patients were the following; STO scores greater

than or equal to 3 SEM above the mean = improved, (N= 40: 41%),

STO scores less than or equal to 3 SEM below the mean = decline,

(N=34: 35%), STO scores within 3 SEM= no change, (N=23: 24%).

Multiple logistic regression was used to identify patient attributes

predictive of improvement, decline, or no change from measures

routinely collected at the point of admission to rehabilitation.

The model for prediction of improvement correctly classified 70% of

patients as those who improved vs. those who did not (sensitivity

70%, specificity 71%). This model generated the following variables

as having predictive capabilities; recent CABG, emotional status,

social status, calcium channel blocker, recent angioplasty, maximum

diastolic BP, maximum systolic BP and resting systolic BP. The model

for predicting those who declined vs. those who did not decline

demonstrated higher correct classification rate of 74% and specificity

(84%). This model generated the following variables as having predictive

capabilities; social status, calcium channel blocker, orthopedic limitation,

role function, QOL score and Digitalis. However, these models may include

certain bias because the same observations to fit the model were also

used to estimate the classification errors. Therefore, cross validation

was performed utilizing the single point deletion method; this method

yielded somewhat lower fraction correct classification rates (66%,69%)

and sensitivity rates (56%,44%) for improvement vs. no improvement and

decline vs. no decline groups respectively. Conclusion A combined set

of baseline clinical, psychosocial and exercise measures can demonstrate

moderate success in predicting training outcome based on STO scores in

hospital outpatient cardiac rehabilitation. In contrast psychosocial

data seem to account for more of the variance in prediction of decline

than other types of baseline variables examined in this study. Baseline

blood pressure responses both at rest and during exercise were the greatest

predictors of improvement. However, cross validation of these models

indicates that these results could be biased eliciting overly optimistic

predictive capabilities, due to the analysis of fitted data. These

models need to be validated in independent sample with patients in

similar settings.

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