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      • Record: found
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      Partial-body cryostimulation after training improves sleep quality in professional soccer players

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          Abstract

          Objective

          The aim of the present investigation was to determine whether using cryostimulation (partial-body cryostimulation) impacts sleep quality in professional soccer players. Different exposure durations at − 180 °C were tested randomly after standardized training sessions in nine professional soccer players (no cryostimulation, 180-s exposure, two 90-s exposures separated by a 5-min rest at room temperature, and 90-s exposure), and the effects on sleep quality using 3-dimensional accelerometers worn during sleep were assessed.

          Results

          The number of movements during the night after partial-body cryostimulation was significantly reduced only in the 180-s exposure condition (p < 0.05, very large effect size) compared with the control condition. Partial-body cryostimulation seems to induce a positive impact on sleep quality that may be dose-dependent.

          Trial registration Australia and New Zealand Clinical Trials Registry (ANZCTR), ACTRN12619000330145, date of registration: 4/03/2019. Retrospectively registered

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          Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients.

          Clete Kushida, Arthur Chang, Chirag Gadkary … (2001)
          Comparison of polysomnography (PSG)-derived sleep parameters (total sleep time, sleep efficiency, and number of awakenings) to those derived from actigraphy and subjective questionnaires. Actigraphy is commonly used to assist sleep specialists in the diagnosis of various sleep and circadian-rhythm disorders. However, few validation studies incorporate large sample sizes, typical sleep clinic patients, or comparisons with subjective reports of sleep parameters. Clinical series with 100 consecutive sleep-disordered patients (69 men, 31 women, mean age of 49+/-14.7 years) at a tertiary sleep disorders center. Sensitivity, specificity, and accuracy measures were obtained from epoch-by-epoch comparison of PSG and actigraphic data. Subjective sleep parameter data were derived from questionnaires given to subjects in the morning following their recording night. We found that total sleep time and sleep efficiency did not significantly differ between PSG data and the combined data obtained from actigraphy and subjective reports. Using a high-threshold (low-wake-sensitivity) actigraphic algorithm, the number of awakenings was not significantly different from those detected by PSG. We recommend the use of subjective data as an adjunct to actigraphic data in estimating total sleep time and sleep efficiency in sleep-disordered patients, especially those with disorders of excessive somnolence.
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            The importance of a priori sample size estimation in strength and conditioning research.

            Michael Beck (2013)
            The statistical power, or sensitivity of an experiment, is defined as the probability of rejecting a false null hypothesis. Only 3 factors can affect statistical power: (a) the significance level (α), (b) the magnitude or size of the treatment effect (effect size), and (c) the sample size (n). Of these 3 factors, only the sample size can be manipulated by the investigator because the significance level is usually selected before the study, and the effect size is determined by the effectiveness of the treatment. Thus, selection of an appropriate sample size is one of the most important components of research design but is often misunderstood by beginning researchers. The purpose of this tutorial is to describe procedures for estimating sample size for a variety of different experimental designs that are common in strength and conditioning research. Emphasis is placed on selecting an appropriate effect size because this step fully determines sample size when power and the significance level are fixed. There are many different software packages that can be used for sample size estimation. However, I chose to describe the procedures for the G*Power software package (version 3.1.4) because this software is freely downloadable and capable of estimating sample size for many of the different statistical tests used in strength and conditioning research. Furthermore, G*Power provides a number of different auxiliary features that can be useful for researchers when designing studies. It is my hope that the procedures described in this article will be beneficial for researchers in the field of strength and conditioning.
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              Heart rate variability, sleep and sleep disorders.

              Phyllis Stein, Yachuan Pu (2012)
              Heart rate (HR) is modulated by the combined effects of the sympathetic and parasympathetic nervous systems. Therefore, measurement of changes in HR over time (heart rate variability or HRV) provides information about autonomic functioning. HRV has been used to identify high risk people, understand the autonomic components of different disorders and to evaluate the effect of different interventions, etc. Since the signal required to measure HRV is already being collected on the electrocardiogram (ECG) channel of the polysomnogram (PSG), collecting data for research on HRV and sleep is straightforward, but applications have been limited. As reviewed here, HRV has been applied to understand autonomic changes during different sleep stages. It has also been applied to understand the effect of sleep-disordered breathing, periodic limb movements and insomnia both during sleep and during the daytime. HRV has been successfully used to screen people for possible referral to a Sleep Lab. It has also been used to monitor the effects of continuous positive airway pressure (CPAP). A novel HRV measure, cardiopulmonary coupling (CPC) has been proposed for sleep quality. Evidence also suggests that HRV collected during a PSG can be used in risk stratification models, at least for older adults. Caveats for accurate interpretation of HRV are also presented. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Wafa Douzi: wafa.douzi01@univ-poitiers.fr
                Olivier Dupuy: olivier.dupuy@univ-poitiers.fr
                Dimitri Theurot: dimitri.theurot01@univ-poitiers.fr
                Geoffroy Boucard: geoffroy.boucard@univ-poitiers.fr
                Benoit Dugué:
                ORCID: http://orcid.org/0000-0003-2660-8244
                benoit.dugue@univ-poitiers.fr
                Journal
                Journal ID (nlm-ta): BMC Res Notes
                Journal ID (iso-abbrev): BMC Res Notes
                Title: BMC Research Notes
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1756-0500
                Publication date (Electronic): 15 March 2019
                Publication date PMC-release: 15 March 2019
                Publication date Collection: 2019
                Volume: 12
                Electronic Location Identifier: 141
                Affiliations
                [1 ]ISNI 0000 0001 2160 6368, GRID grid.11166.31, Laboratoire Mobilité Vieillissement Exercice (MOVE)-EA6314, Faculty of Sport Sciences, , University of Poitiers, ; 8 allée Jean Monnet, 86000 Poitiers, France
                [2 ]ISNI 0000 0001 2160 6368, GRID grid.11166.31, Centre de Recherches sur la Cognition et l’Apprentissage (UMR7295), , Université de Poitiers and Université François-Rabelais de Tours, ; Poitiers, France
                Author information
                http://orcid.org/0000-0003-2660-8244
                Article
                Publisher ID: 4172
                DOI: 10.1186/s13104-019-4172-9
                PMC ID: 6419922
                PubMed ID: 30876470
                SO-VID: 43bcba52-61a0-49d5-8e76-6b0be0aa6d19
                Copyright © © The Author(s) 2019
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 4 December 2018
                Date accepted : 11 March 2019
                Categories
                Subject: Research Note
                Custom metadata
                issue-copyright-statement © The Author(s) 2019

                ScienceOpen disciplines: Medicine
                Keywords: cryostimulation,cryotherapy,exercise recovery,sleep,soccer
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: cryostimulation, cryotherapy, exercise recovery, sleep, soccer

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