F. Borszcz, Artur Ferreira Tramontin, R. D. de Lucas, Vitor Pereira Costa
{"title":"5 分钟计时单车测试是最大摄氧量的有效预测指标吗?外部交叉验证研究","authors":"F. Borszcz, Artur Ferreira Tramontin, R. D. de Lucas, Vitor Pereira Costa","doi":"10.1123/ijspp.2023-0330","DOIUrl":null,"url":null,"abstract":"PURPOSE\nThis study aimed to cross-validate a recently proposed equation for the prediction of maximal oxygen uptake (V˙O2max) in cycling exercise by using the average power output normalized by the body mass from a 5-minute time trial (RPO5-min) as the independent variable. Further, the study aimed to update the predictive equation using Bayesian informative prior distributions and meta-analysis.\n\n\nMETHODS\nOn different days, 49 male cyclists performed an incremental graded exercise test until exhaustion and a 5-minute time trial on a stationary cycle ergometer. We compared the actual V˙O2max with the predicted value obtained from the RPO5-min, using a modified Bayesian Bland-Altman agreement analysis. In addition, this study updated the data on the linear regression between V˙O2max and RPO5-min, by incorporating information from a previous study as a Bayesian informative prior distribution or via meta-analysis.\n\n\nRESULTS\nOn average, the predicted V˙O2max using RPO5-min underestimated the actual V˙O2max by -6.6 mL·kg-1·min-1 (95% credible interval, -8.6 to -4.7 mL·kg-1·min-1). The lower and upper 95% limits of agreement were -17.2 (-22.7 to -12.3) and 3.8 (-1.0 to 9.5) mL·kg-1·min-1, respectively. When the current study's data were analyzed using the previously published data as a Bayesian informative prior distribution, the accuracy of predicting sample means was found to be better when compared with the data combined via meta-analyses.\n\n\nCONCLUSIONS\nThe proposed equation presented systematic bias in our sample, in which the prediction underestimated the actual V˙O2max. We provide an updated equation using the previous one as the prior distribution, which could be generalized to a greater audience of cyclists.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":"80 1","pages":"1-11"},"PeriodicalIF":4.3000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Is the 5-Minute Time-Trial Cycling Test a Valid Predictor of Maximal Oxygen Uptake? An External Cross-Validation Study.\",\"authors\":\"F. Borszcz, Artur Ferreira Tramontin, R. D. de Lucas, Vitor Pereira Costa\",\"doi\":\"10.1123/ijspp.2023-0330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PURPOSE\\nThis study aimed to cross-validate a recently proposed equation for the prediction of maximal oxygen uptake (V˙O2max) in cycling exercise by using the average power output normalized by the body mass from a 5-minute time trial (RPO5-min) as the independent variable. Further, the study aimed to update the predictive equation using Bayesian informative prior distributions and meta-analysis.\\n\\n\\nMETHODS\\nOn different days, 49 male cyclists performed an incremental graded exercise test until exhaustion and a 5-minute time trial on a stationary cycle ergometer. We compared the actual V˙O2max with the predicted value obtained from the RPO5-min, using a modified Bayesian Bland-Altman agreement analysis. In addition, this study updated the data on the linear regression between V˙O2max and RPO5-min, by incorporating information from a previous study as a Bayesian informative prior distribution or via meta-analysis.\\n\\n\\nRESULTS\\nOn average, the predicted V˙O2max using RPO5-min underestimated the actual V˙O2max by -6.6 mL·kg-1·min-1 (95% credible interval, -8.6 to -4.7 mL·kg-1·min-1). The lower and upper 95% limits of agreement were -17.2 (-22.7 to -12.3) and 3.8 (-1.0 to 9.5) mL·kg-1·min-1, respectively. When the current study's data were analyzed using the previously published data as a Bayesian informative prior distribution, the accuracy of predicting sample means was found to be better when compared with the data combined via meta-analyses.\\n\\n\\nCONCLUSIONS\\nThe proposed equation presented systematic bias in our sample, in which the prediction underestimated the actual V˙O2max. 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Is the 5-Minute Time-Trial Cycling Test a Valid Predictor of Maximal Oxygen Uptake? An External Cross-Validation Study.
PURPOSE
This study aimed to cross-validate a recently proposed equation for the prediction of maximal oxygen uptake (V˙O2max) in cycling exercise by using the average power output normalized by the body mass from a 5-minute time trial (RPO5-min) as the independent variable. Further, the study aimed to update the predictive equation using Bayesian informative prior distributions and meta-analysis.
METHODS
On different days, 49 male cyclists performed an incremental graded exercise test until exhaustion and a 5-minute time trial on a stationary cycle ergometer. We compared the actual V˙O2max with the predicted value obtained from the RPO5-min, using a modified Bayesian Bland-Altman agreement analysis. In addition, this study updated the data on the linear regression between V˙O2max and RPO5-min, by incorporating information from a previous study as a Bayesian informative prior distribution or via meta-analysis.
RESULTS
On average, the predicted V˙O2max using RPO5-min underestimated the actual V˙O2max by -6.6 mL·kg-1·min-1 (95% credible interval, -8.6 to -4.7 mL·kg-1·min-1). The lower and upper 95% limits of agreement were -17.2 (-22.7 to -12.3) and 3.8 (-1.0 to 9.5) mL·kg-1·min-1, respectively. When the current study's data were analyzed using the previously published data as a Bayesian informative prior distribution, the accuracy of predicting sample means was found to be better when compared with the data combined via meta-analyses.
CONCLUSIONS
The proposed equation presented systematic bias in our sample, in which the prediction underestimated the actual V˙O2max. We provide an updated equation using the previous one as the prior distribution, which could be generalized to a greater audience of cyclists.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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