Prediction VO2max during cycle ergometry based on submaximal ventilatory indicators.

There are several equations to predict maximum oxygen consumption (VO2max) from ergometric test variables on different ergometers. However, a similar equation using ventilatory thresholds of ergospirometry in a submaximal test on a cycle ergometer is unavailable. The aim of the present study was to assess the accuracy of VO2max prediction models based on indicators of submaximal effort. Accordingly, 4,640 healthy, nonathlete women ages 20 years and older volunteered to be tested on a cycle ergometer using a maximum incremental protocol. The subjects were randomly assigned to 2 groups: group A (estimation) and group B (validation). From the independent variables of weight in kilograms, the second workload threshold (WT2), and heart rate of the second threshold (HRT2), it was possible to build a multiple linear regression model to predict maximal oxygen consumption (VO2max = 40.302 - 0.497 [Weight] - 0.001 [HRT2] + 0.239 [WT2] in mL O2/kg/min(-1); r = 0.995 and standard error of the estimate [SEE] = 0.68 mL O2/kg/min(-1)). The cross-validation method was used in group B with group A serving as the basis for building the model and the validation dataset. The results showed that, in healthy nonathlete women, it is possible to predict VO2max with a minimum of error (SEE = 1.00%) from submaximal indicators obtained in an incremental test.

RCT Entities:   Population Interventions Outcomes