Prediction of normal values for lactate threshold estimated by gas exchange in men and women |
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Authors: | James A. Davis Thomas W. Storer Vincent J. Caiozzo |
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Affiliation: | (1) Laboratory of Applied Physiology, California State University, Long Beach, CA 90840, USA, US;(2) Exercise Science Laboratory, El Camino College, Torrance, CA 90506, USA, US;(3) Neuromuscular Research Laboratory, University of California, Irvine, CA 92717, USA, US;(4) Department of Kinesiology and Physical Education, California State University, 1250 Bellflower Boulevard, Long Beach, CA 90840-4901, USA, US |
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Abstract: | Lactate threshold (LT) is an index of exercise capacity and can be estimated from the gas exchange consequences of a metabolic acidosis (LTGE). In recent years, it has emerged as a diagnostic tool in the evaluation of subjects with exercise limitation. The purpose of this study was to develop LTGE prediction equations on a relatively large sample of adults and to cross-validate each equation. A total of 204 healthy, sedentary, nonsmoking subjects (103 men and 101 women), aged 20–70 years, underwent graded exercise testing on a cycle ergometer. The V-slope technique was used to detect LTGE as the oxygen uptake (V˙O2) at the breakpoint of the carbon dioxide output versus V˙O2 relationship. Multiple linear regression was used to develop 12 equations with combinations of the following predictor variables: age, height, body mass, and fat-free mass. Eight of the equations are gender-specific and four are generalized with gender as a dummy variable. The equations were cross-validated using the predicted residual sum of squares (PRESS) method. The results demonstrate that the equations had relatively high multiple correlations (0.577–0.863) and low standard errors of the estimate (0.123–0.228 1 · min−1). The PRESS method demonstrated that the equations are generalizable, i.e., can be used in future studies without a significant loss of accuracy. Since we tested only healthy, sedentary subjects, our equations can be used to predict the lower limit of normal for a given subject. Using individual data for healthy and diseased subjects from the literature, we found that our gender-specific equations rarely miscategorized subjects unless they were obese and mass was a predictor variable. We conclude that our equations provide accurate predictions of normal values for LTGE and that they are generalizable to other subject populations. Accepted: 13 February 1997 |
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Keywords: | Cross-validation Cycle ergometer Healthy sedentary nonsmoking subjects Multiple linear regression V-slope technique |
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