Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction

Detalhes bibliográficos
Autor(a) principal: Sotero, Rafael da Costa
Data de Publicação: 2007
Outros Autores: Campbell, Carmen Silvia Grubert, Pardono, Emerson, Puga, Guilherme Morais, Simões, Herbert Gustavo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UCB
Texto Completo: http://hdl.handle.net/123456789/145
https://repositorio.ucb.br:9443/jspui/handle/123456789/7401
Resumo: The purpose of this study was to analyze the possibility of identifying the lactate minimum velocity (LM) and estimating the maximal lactate steady state intensity (MLSS) by applying a polynomial function to just three stages of the LM test. Seventeen physically active males (24.1 ± 4.0 years; 23.8 ±2.2kg.m2(-1) BMI; 11.7 ± 3.8% body fat) performed: 1) a 1600m time trial (1600mV); 2) a 150m sprint to induce hyperlactatemia, and then an incremental test (InT) consisting of 6 x 800m at intensities of 78, 81, 84, 87, 90 and 93% of 1600mV; 3) 2 to 3 sessions of constant 30 min running tests to identify MLSS. Blood lactate [lac] was determined by an electrochemical method (YSI - 2700 SELECT). The LM was identifi ed visually (LMv) as well by applying polynomial function to the [lac] responses at all 6 stages (LMp), to the 1st, 3rd and 5th stages (LMp135), to the 1st, 3rd and 6th stages (LMp136) and to the 1st, 4th and 6th stages (LMp146) of InT. The ANOVA detected no differences between the velocities (m.min-1) identifi ed by LMv (196.0 ± 17.8) LMp (198.0 ± 17.6), LMp135 (197.7 ± 17.6), LMp136 (200.0 ±17.2), LMp146 (199,7 ± 18,1) and MLSS (198.7 ±16.6) (p>0.05), with a high correlation among each other (p<0.01). The polynomial function identifi ed LM even when applied to just 3 stages of the incremental test, enabling for prediction of MLSS intensity with a reduced number of blood samples being collected during testing.
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spelling Sotero, Rafael da CostaCampbell, Carmen Silvia GrubertPardono, EmersonPuga, Guilherme MoraisSimões, Herbert Gustavo2016-10-10T03:51:21Z2016-10-10T03:51:21Z2007SOTERO, Rafael da Costa et al. Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction. Brazilian Journal of Kinanthropometry and Human Performance, North America, 9, nov. 2007.http://hdl.handle.net/123456789/145https://repositorio.ucb.br:9443/jspui/handle/123456789/7401The purpose of this study was to analyze the possibility of identifying the lactate minimum velocity (LM) and estimating the maximal lactate steady state intensity (MLSS) by applying a polynomial function to just three stages of the LM test. Seventeen physically active males (24.1 ± 4.0 years; 23.8 ±2.2kg.m2(-1) BMI; 11.7 ± 3.8% body fat) performed: 1) a 1600m time trial (1600mV); 2) a 150m sprint to induce hyperlactatemia, and then an incremental test (InT) consisting of 6 x 800m at intensities of 78, 81, 84, 87, 90 and 93% of 1600mV; 3) 2 to 3 sessions of constant 30 min running tests to identify MLSS. Blood lactate [lac] was determined by an electrochemical method (YSI - 2700 SELECT). The LM was identifi ed visually (LMv) as well by applying polynomial function to the [lac] responses at all 6 stages (LMp), to the 1st, 3rd and 5th stages (LMp135), to the 1st, 3rd and 6th stages (LMp136) and to the 1st, 4th and 6th stages (LMp146) of InT. The ANOVA detected no differences between the velocities (m.min-1) identifi ed by LMv (196.0 ± 17.8) LMp (198.0 ± 17.6), LMp135 (197.7 ± 17.6), LMp136 (200.0 ±17.2), LMp146 (199,7 ± 18,1) and MLSS (198.7 ±16.6) (p>0.05), with a high correlation among each other (p<0.01). The polynomial function identifi ed LM even when applied to just 3 stages of the incremental test, enabling for prediction of MLSS intensity with a reduced number of blood samples being collected during testing.Made available in DSpace on 2016-10-10T03:51:21Z (GMT). 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dc.title.pt_BR.fl_str_mv Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
dc.title.alternative.pt_BR.fl_str_mv Ajuste polinomial como nova técnica para determinação da velocidade do lactato mínimo com redução de coletas sanguíneas
title Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
spellingShingle Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
Sotero, Rafael da Costa
Lactate
Maximal lactate steady state
Running
Polynomial function
title_short Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
title_full Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
title_fullStr Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
title_full_unstemmed Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
title_sort Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction
author Sotero, Rafael da Costa
author_facet Sotero, Rafael da Costa
Campbell, Carmen Silvia Grubert
Pardono, Emerson
Puga, Guilherme Morais
Simões, Herbert Gustavo
author_role author
author2 Campbell, Carmen Silvia Grubert
Pardono, Emerson
Puga, Guilherme Morais
Simões, Herbert Gustavo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Sotero, Rafael da Costa
Campbell, Carmen Silvia Grubert
Pardono, Emerson
Puga, Guilherme Morais
Simões, Herbert Gustavo
dc.subject.por.fl_str_mv Lactate
Maximal lactate steady state
Running
Polynomial function
topic Lactate
Maximal lactate steady state
Running
Polynomial function
dc.description.abstract.por.fl_txt_mv The purpose of this study was to analyze the possibility of identifying the lactate minimum velocity (LM) and estimating the maximal lactate steady state intensity (MLSS) by applying a polynomial function to just three stages of the LM test. Seventeen physically active males (24.1 ± 4.0 years; 23.8 ±2.2kg.m2(-1) BMI; 11.7 ± 3.8% body fat) performed: 1) a 1600m time trial (1600mV); 2) a 150m sprint to induce hyperlactatemia, and then an incremental test (InT) consisting of 6 x 800m at intensities of 78, 81, 84, 87, 90 and 93% of 1600mV; 3) 2 to 3 sessions of constant 30 min running tests to identify MLSS. Blood lactate [lac] was determined by an electrochemical method (YSI - 2700 SELECT). The LM was identifi ed visually (LMv) as well by applying polynomial function to the [lac] responses at all 6 stages (LMp), to the 1st, 3rd and 5th stages (LMp135), to the 1st, 3rd and 6th stages (LMp136) and to the 1st, 4th and 6th stages (LMp146) of InT. The ANOVA detected no differences between the velocities (m.min-1) identifi ed by LMv (196.0 ± 17.8) LMp (198.0 ± 17.6), LMp135 (197.7 ± 17.6), LMp136 (200.0 ±17.2), LMp146 (199,7 ± 18,1) and MLSS (198.7 ±16.6) (p>0.05), with a high correlation among each other (p<0.01). The polynomial function identifi ed LM even when applied to just 3 stages of the incremental test, enabling for prediction of MLSS intensity with a reduced number of blood samples being collected during testing.
dc.description.status.pt_BR.fl_txt_mv Publicado
description The purpose of this study was to analyze the possibility of identifying the lactate minimum velocity (LM) and estimating the maximal lactate steady state intensity (MLSS) by applying a polynomial function to just three stages of the LM test. Seventeen physically active males (24.1 ± 4.0 years; 23.8 ±2.2kg.m2(-1) BMI; 11.7 ± 3.8% body fat) performed: 1) a 1600m time trial (1600mV); 2) a 150m sprint to induce hyperlactatemia, and then an incremental test (InT) consisting of 6 x 800m at intensities of 78, 81, 84, 87, 90 and 93% of 1600mV; 3) 2 to 3 sessions of constant 30 min running tests to identify MLSS. Blood lactate [lac] was determined by an electrochemical method (YSI - 2700 SELECT). The LM was identifi ed visually (LMv) as well by applying polynomial function to the [lac] responses at all 6 stages (LMp), to the 1st, 3rd and 5th stages (LMp135), to the 1st, 3rd and 6th stages (LMp136) and to the 1st, 4th and 6th stages (LMp146) of InT. The ANOVA detected no differences between the velocities (m.min-1) identifi ed by LMv (196.0 ± 17.8) LMp (198.0 ± 17.6), LMp135 (197.7 ± 17.6), LMp136 (200.0 ±17.2), LMp146 (199,7 ± 18,1) and MLSS (198.7 ±16.6) (p>0.05), with a high correlation among each other (p<0.01). The polynomial function identifi ed LM even when applied to just 3 stages of the incremental test, enabling for prediction of MLSS intensity with a reduced number of blood samples being collected during testing.
publishDate 2007
dc.date.issued.fl_str_mv 2007
dc.date.accessioned.fl_str_mv 2016-10-10T03:51:21Z
dc.date.available.fl_str_mv 2016-10-10T03:51:21Z
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dc.identifier.citation.fl_str_mv SOTERO, Rafael da Costa et al. Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction. Brazilian Journal of Kinanthropometry and Human Performance, North America, 9, nov. 2007.
dc.identifier.uri.fl_str_mv http://hdl.handle.net/123456789/145
https://repositorio.ucb.br:9443/jspui/handle/123456789/7401
identifier_str_mv SOTERO, Rafael da Costa et al. Polynomial adjustment as a new technique for determination of lactate minimum velocity with blood sampling reduction. Brazilian Journal of Kinanthropometry and Human Performance, North America, 9, nov. 2007.
url http://hdl.handle.net/123456789/145
https://repositorio.ucb.br:9443/jspui/handle/123456789/7401
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