John Richard Wicks

Cardiorespiratory fitness measured by treadmill testing has prognostic significance in determining mortality with cardiovascular and other chronic disease states. The accuracy of a recently developed method for estimating maximal oxygen uptake (VO_2peak), the heart rate index (HRI), is dependent only on heart rate (HR) and was tested against oxygen uptake (VO₂), either measured or predicted from conventional treadmill parameters (speed, incline, protocol time). The HRI equation, METs = 6 x HRI– 5, where HRI = maximal HR/resting HR, provides a surrogate measure of VO_2peak. Forty large scale treadmill studies were identified through a systematic search using MEDLINE, Google Scholar and Web of Science in which VO_2peak was either measured (TM-VO_2meas; n = 20) or predicted (TM-VO_2pred; n = 20) based on treadmill parameters. All studies were required to have reported group mean data of both resting and maximal HRs for determination of HR index-derived oxygen uptake (HRI-VO₂). The 20 studies with measured VO₂ (TM-VO_2meas), involved 11,477 participants (median 337) with a total of 105,044 participants (median 3,736) in the 20 studies with predicted VO₂ (TM-VO_2pred). A difference of only 0.4% was seen between mean (±SD) VO_2peak for TM- VO_2meas and HRI-VO₂ (6.51±2.25 METs and 6.54±2.28, respectively; p = 0.84). In contrast, there was a highly significant 21.1% difference between mean (±SD) TM-VO_2pred and HRI-VO₂ (8.12±1.85 METs and 6.71±1.92, respectively; p2meas and HRI-VO₂ were almost identical, mean TM-VO_2pred was more than 20% greater than mean HRI-VO₂.

Energy expenditure measured in METs is widely used in cardiovascular medicine, exercise physiology, and nutrition assessment. However, measurement of METs requires complex equipment to determine oxygen uptake. A simple method to predict oxygen uptake on the basis of HR measurements without requirement for gas analysis, movement-recording devices, or exercise equipment (treadmills, cycle ergometers) would enable a simple prediction of energy expenditure. The purpose of this study was to determine whether HR can be used to accurately predict oxygen uptake. Published studies that reported a measured resting HR (HR(rest)), a measured activity HR (HR(absolute)), and a measured oxygen uptake (mL O(2)·kg(-1)·min(-1)) associated with the HR(absolute) were identified. A total of 220 data sets were extracted from 60 published exercise studies (total subject cohort = 11,257) involving a diverse range of age, pathophysiology, and the presence/absence of β-blocker therapy. Net HR (HR(net) = HR(absolute) - HR(rest)) and HR index (HR(index) = HR(absolute)/HR(rest)) were calculated from the HR data. A regression analysis of oxygen uptake (expressed as METs) was performed against HR(absolute), HR(net), and HR(index). Statistical models for the relationship between METs and the different HR parameters (HR(absolute), HR(net), and HR(index)) were developed. A comparison between regression analyses for the models and the actual data extracted from the published studies demonstrated that the best fit model was the regression equation describing the relationship between HR(index) and METs. Subgroup analyses of clinical state (normal, pathology), testing device (cycle ergometer, treadmill), test protocol (maximal, submaximal), gender, and the effect of β-blockade were all consistent with combined data analysis, demonstrating the robustness of the equation. HR(index) can be used to predict energy expenditure with the equation METs = 6HR(index) - 5.