Accurate Prediction of Cardiorespiratory Fitness Using Cycle Ergometry in Minimally Disabled Persons With Relapsing-Remitting Multiple Sclerosis

Abstract

Motl RW, Fernhall B. Accurate prediction of cardiorespiratory fitness using cycle ergometry in minimally disabled persons with relapsing-remitting multiple sclerosis. ObjectiveTo examine the accuracy of predicting peak oxygen consumption (Vo2peak) primarily from peak work rate (WRpeak) recorded during a maximal, incremental exercise test on a cycle ergometer among persons with relapsing-remitting multiple sclerosis (RRMS) who had minimal disability. DesignCross-sectional study. SettingClinical research laboratory. ParticipantsWomen with RRMS (n=32) and sex-, age-, height-, and weight-matched healthy controls (n=16) completed an incremental exercise test on a cycle ergometer to volitional termination. InterventionNot applicable. Main Outcome MeasuresMeasured and predicted Vo2peak and WRpeak. ResultsThere were strong, statistically significant associations between measured and predicted Vo2peak in the overall sample (R2=.89, standard error of the estimate=127.4mL/min) and subsamples with (R2=.89, standard error of the estimate=131.3mL/min) and without (R2=.85, standard error of the estimate=126.8mL/min) multiple sclerosis (MS) based on the linear regression analyses. Based on the 95% confidence limits for worst-case errors, the equation predicted Vo2peak within 10% of its true value in 95 of every 100 subjects with MS. ConclusionsPeak Vo2 can be accurately predicted in persons with RRMS who have minimal disability as it is in controls by using established equations and WRpeak recorded from a maximal, incremental exercise test on a cycle ergometer.