A new method to individualize monitoring of muscle recovery in athletes

Publication type:
Journal article
Metadata:
Autoren
  • Anne Hecksteden
  • Werner Pitsch
  • Ross Julian
  • Mark Pfeiffer
  • Michael Kellmann
  • Alexander Ferrauti
  • Tim Meyer
Sammlungen
  • metadata
ISSN
1555-0265
Ausgabe der Veröffentlichung
9
Zeitschrift
International journal of sports physiology and performance
Schlüsselwörter
  • 796 Sport
  • 796 Athletic and outdoor sports and games
Sprache
eng
Paginierung
Seiten: 1137 - 1142
Datum der Veröffentlichung
2017
Herausgeber
Human Kinetics
Herausgeber URL
http://dx.doi.org/10.1123/ijspp.2016-0120
Datum der Datenerfassung
2020
Datum, an dem der Datensatz öffentlich gemacht wurde
2020
Zugang
Public
Titel
A new method to individualize monitoring of muscle recovery in athletes
Ausgabe der Zeitschrift
12

Data source: METADATA.UB

Other metadata sources:
Autoren
  • Anne Hecksteden
  • Werner Pitsch
  • Ross Julian
  • Mark Pfeiffer
  • Michael Kellmann
  • Alexander Ferrauti
  • Tim Meyer
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000418351400003&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1123/ijspp.2016-0120
eISSN
1555-0273
Externe Identifier
  • Clarivate Analytics Document Solution ID: FQ4TQ
  • PubMed Identifier: 27967274
ISSN
1555-0265
Ausgabe der Veröffentlichung
9
Zeitschrift
INTERNATIONAL JOURNAL OF SPORTS PHYSIOLOGY AND PERFORMANCE
Schlüsselwörter
  • reference range
  • distribution
  • individualization
  • sport
Paginierung
1137 - 1142
Datum der Veröffentlichung
2017
Status
Published
Titel
A New Method to Individualize Monitoring of Muscle Recovery in Athletes
Sub types
  • Article
Ausgabe der Zeitschrift
12

Data source: Web of Science (Lite)

Abstract
<jats:sec sec-type="purpose"><jats:title>Purpose:</jats:title><jats:p>Assessment of muscle recovery is essential for the daily fine-tuning of training load in competitive sports, but individual differences may limit the diagnostic accuracy of group-based reference ranges. This article reports an attempt to develop individualized reference ranges using a Bayesian approach comparable to that developed for the Athlete Biological Passport.</jats:p></jats:sec> <jats:sec sec-type="methods"><jats:title>Methods:</jats:title><jats:p>Urea and creatine kinase (CK) were selected as indicators of muscle recovery. For each parameter, prior distributions and repeated-measures SDs were characterized based on data of 883 squad athletes (1758 data points, 1–8 per athlete, years 2013–2015). Equations for the individualization procedure were adapted from previous material to allow for discrimination of 2 physiological states (recovered vs nonrecovered). Evaluation of classificatory performance was carried out using data from 5 consecutive weekly microcycles in 14 elite junior swimmers and triathletes. Blood samples were collected every Monday (recovered) and Friday according to the repetitive weekly training schedule over 5 wk. On the group level, changes in muscle recovery could be confirmed by significant differences in urea and CK and validated questionnaires. Group-based reference ranges were derived from that same data set to avoid overestimating the potential benefit of individualization.</jats:p></jats:sec> <jats:sec sec-type="results"><jats:title>Results:</jats:title><jats:p>For CK, error rates were significantly lower with individualized classification (<jats:italic>P</jats:italic> vs group-based: test-pass error rate <jats:italic>P</jats:italic> = .008; test-fail error rate <jats:italic>P</jats:italic> &lt; .001). For urea, numerical improvements in error rates failed to reach significance.</jats:p></jats:sec> <jats:sec sec-type="conclusions"><jats:title>Conclusions:</jats:title><jats:p>Individualized reference ranges seem to be a promising tool to improve accuracy of monitoring muscle recovery. Investigating application to a larger panel of indicators is warranted.</jats:p></jats:sec>
Autoren
  • Anne Hecksteden
  • Werner Pitsch
  • Ross Julian
  • Mark Pfeiffer
  • Michael Kellmann
  • Alexander Ferrauti
  • Tim Meyer
DOI
10.1123/ijspp.2016-0120
eISSN
1555-0273
ISSN
1555-0265
Ausgabe der Veröffentlichung
9
Zeitschrift
International Journal of Sports Physiology and Performance
Paginierung
1137 - 1142
Datum der Veröffentlichung
2017
Status
Published
Herausgeber
Human Kinetics
Herausgeber URL
http://dx.doi.org/10.1123/ijspp.2016-0120
Datum der Datenerfassung
2022
Titel
A New Method to Individualize Monitoring of Muscle Recovery in Athletes
Ausgabe der Zeitschrift
12

Data source: Crossref

Abstract
<h4>Purpose</h4>Assessment of muscle recovery is essential for the daily fine-tuning of training load in competitive sports, but individual differences may limit the diagnostic accuracy of group-based reference ranges. This article reports an attempt to develop individualized reference ranges using a Bayesian approach comparable to that developed for the Athlete Biological Passport.<h4>Methods</h4>Urea and creatine kinase (CK) were selected as indicators of muscle recovery. For each parameter, prior distributions and repeated-measures SDs were characterized based on data of 883 squad athletes (1758 data points, 1-8 per athlete, years 2013-2015). Equations for the individualization procedure were adapted from previous material to allow for discrimination of 2 physiological states (recovered vs nonrecovered). Evaluation of classificatory performance was carried out using data from 5 consecutive weekly microcycles in 14 elite junior swimmers and triathletes. Blood samples were collected every Monday (recovered) and Friday according to the repetitive weekly training schedule over 5 wk. On the group level, changes in muscle recovery could be confirmed by significant differences in urea and CK and validated questionnaires. Group-based reference ranges were derived from that same data set to avoid overestimating the potential benefit of individualization.<h4>Results</h4>For CK, error rates were significantly lower with individualized classification (P vs group-based: test-pass error rate P = .008; test-fail error rate P < .001). For urea, numerical improvements in error rates failed to reach significance.<h4>Conclusions</h4>Individualized reference ranges seem to be a promising tool to improve accuracy of monitoring muscle recovery. Investigating application to a larger panel of indicators is warranted.
Autoren
  • Anne Hecksteden
  • Werner Pitsch
  • Ross Julian
  • Mark Pfeiffer
  • Michael Kellmann
  • Alexander Ferrauti
  • Tim Meyer
DOI
10.1123/ijspp.2016-0120
eISSN
1555-0273
Externe Identifier
  • PubMed Identifier: 27967274
Open access
false
ISSN
1555-0265
Ausgabe der Veröffentlichung
9
Zeitschrift
International journal of sports physiology and performance
Schlüsselwörter
  • Muscle, Skeletal
  • Humans
  • Urea
  • Creatine Kinase
  • Bayes Theorem
  • Muscle Fatigue
  • Algorithms
  • Reference Values
  • Sports
  • Female
  • Male
  • Athletes
  • Biomarkers
Sprache
eng
Medium
Print-Electronic
Online publication date
2016
Paginierung
1137 - 1142
Datum der Veröffentlichung
2017
Status
Published
Datum der Datenerfassung
2016
Titel
A New Method to Individualize Monitoring of Muscle Recovery in Athletes.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
12

Data source: Europe PubMed Central

Abstract
PURPOSE: Assessment of muscle recovery is essential for the daily fine-tuning of training load in competitive sports, but individual differences may limit the diagnostic accuracy of group-based reference ranges. This article reports an attempt to develop individualized reference ranges using a Bayesian approach comparable to that developed for the Athlete Biological Passport. METHODS: Urea and creatine kinase (CK) were selected as indicators of muscle recovery. For each parameter, prior distributions and repeated-measures SDs were characterized based on data of 883 squad athletes (1758 data points, 1-8 per athlete, years 2013-2015). Equations for the individualization procedure were adapted from previous material to allow for discrimination of 2 physiological states (recovered vs nonrecovered). Evaluation of classificatory performance was carried out using data from 5 consecutive weekly microcycles in 14 elite junior swimmers and triathletes. Blood samples were collected every Monday (recovered) and Friday according to the repetitive weekly training schedule over 5 wk. On the group level, changes in muscle recovery could be confirmed by significant differences in urea and CK and validated questionnaires. Group-based reference ranges were derived from that same data set to avoid overestimating the potential benefit of individualization. RESULTS: For CK, error rates were significantly lower with individualized classification (P vs group-based: test-pass error rate P = .008; test-fail error rate P < .001). For urea, numerical improvements in error rates failed to reach significance. CONCLUSIONS: Individualized reference ranges seem to be a promising tool to improve accuracy of monitoring muscle recovery. Investigating application to a larger panel of indicators is warranted.
Autoren
  • Anne Hecksteden
  • Werner Pitsch
  • Ross Julian
  • Mark Pfeiffer
  • Michael Kellmann
  • Alexander Ferrauti
  • Tim Meyer
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/27967274
DOI
10.1123/ijspp.2016-0120
eISSN
1555-0273
Ausgabe der Veröffentlichung
9
Zeitschrift
Int J Sports Physiol Perform
Schlüsselwörter
  • distribution
  • individualization
  • reference range
  • sport
  • Algorithms
  • Athletes
  • Bayes Theorem
  • Biomarkers
  • Creatine Kinase
  • Female
  • Humans
  • Male
  • Muscle Fatigue
  • Muscle, Skeletal
  • Reference Values
  • Sports
  • Urea
Sprache
eng
Country
United States
Paginierung
1137 - 1142
Datum der Veröffentlichung
2017
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
2018
Titel
A New Method to Individualize Monitoring of Muscle Recovery in Athletes.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
12

Data source: PubMed

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