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      Stabilization period before capturing an ultra-short vagal index can be shortened to 60 s in endurance athletes and to 90 s in university students

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      PLoS ONE
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          Abstract

          Purpose

          To find the shortest, acceptable stabilization period before recording resting, supine ultra-short-term Ln RMSSD and heart rate (HR).

          Method

          Thirty endurance-trained male athletes (age 24.1 ± 2.3 years, maximal oxygen consumption (VO 2max) 64.1 ± 6.6 ml·kg -1·min -1) and 30 male students (age 23.3 ± 1.8 years, VO 2max 52.8 ± 5.1 ml·kg -1·min -1) were recruited. Upon awaking at home, resting, supine RR intervals were measured continuously for 10 min using a Polar V800 HR monitor. Ultra-short-term Ln RMSSD and HR values were calculated from 1-min RR interval segments after stabilization periods from 0 to 4 min in 0.5 min increments and were compared with reference values calculated from 5-min segment after 5-min stabilization. Systematic bias and intraclass correlation coefficients (ICC) including 90% confidence intervals (CI) were calculated and magnitude based inference was conducted.

          Results

          The stabilization periods of up to 30 s for athletes and up to 60 s for students showed positive (possibly to most likely) biases for ultra-short-term Ln RMSSD compared with reference values. Stabilization periods of 60 s for athletes and 90 s for students showed trivial biases and ICCs were 0.84; 90% CI 0.72 to 0.91, and 0.88; 0.79 to 0.94, respectively. For HR, biases were trivial and ICCs were 0.93; 0.88 to 0.96, and 0.93; 0.88 to 0.96, respectively.

          Conclusion

          The shortest stabilization period required to stabilize Ln RMSSD and HR was set at 60 s for endurance-trained athletes and 90 s for university students.

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          Most cited references34

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          Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring.

          The measurement of heart rate variability (HRV) is often considered a convenient non-invasive assessment tool for monitoring individual adaptation to training. Decreases and increases in vagal-derived indices of HRV have been suggested to indicate negative and positive adaptations, respectively, to endurance training regimens. However, much of the research in this area has involved recreational and well-trained athletes, with the small number of studies conducted in elite athletes revealing equivocal outcomes. For example, in elite athletes, studies have revealed both increases and decreases in HRV to be associated with negative adaptation. Additionally, signs of positive adaptation, such as increases in cardiorespiratory fitness, have been observed with atypical concomitant decreases in HRV. As such, practical ways by which HRV can be used to monitor training status in elites are yet to be established. This article addresses the current literature that has assessed changes in HRV in response to training loads and the likely positive and negative adaptations shown. We reveal limitations with respect to how the measurement of HRV has been interpreted to assess positive and negative adaptation to endurance training regimens and subsequent physical performance. We offer solutions to some of the methodological issues associated with using HRV as a day-to-day monitoring tool. These include the use of appropriate averaging techniques, and the use of specific HRV indices to overcome the issue of HRV saturation in elite athletes (i.e., reductions in HRV despite decreases in resting heart rate). Finally, we provide examples in Olympic and World Champion athletes showing how these indices can be practically applied to assess training status and readiness to perform in the period leading up to a pinnacle event. The paper reveals how longitudinal HRV monitoring in elites is required to understand their unique individual HRV fingerprint. For the first time, we demonstrate how increases and decreases in HRV relate to changes in fitness and freshness, respectively, in elite athletes.
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            Time domain, geometrical and frequency domain analysis of cardiac vagal outflow: effects of various respiratory patterns.

            The purpose of this study was to compare the applicability of four different measures of heart rate variability (HRV) in the assessment of cardiac vagal outflow, with special reference to the effect of breathing pattern. The anticholinergic effects of an intravenous glycopyrrolate infusion (5 microg x kg(-1) x h(-1) for 2 h) during spontaneous and controlled (15 min(-1)) breathing rate were investigated in eight volunteers, and the effects of different fixed breathing rates (6-15-24 min(-1)) and hyperventilation in 12 subjects. Cardiac vagal activity was assessed by ECG recordings in which the following measures of HRV were computed: the high-frequency (HF) spectral component, the instantaneous RR interval (RRI) variability (SD1) analysed from the Poincaré plots, the percentage of differences between successive RRIs greater than 50 ms (pNN50), and the square root of the mean squared differences of successive RRIs (RMSSD). On average, glycopyrrolate reduced the HF spectral component by 99.8%, SD1 by 91.3%, pNN50 by 100% and RMSSD by 97.0%. The change of breathing pattern from controlled to spontaneous decreased significantly the HF component and pNN50, but did not affect SD1 or RMSSD. Rapid breathing rate (24 min(-1)) decreased the HF component, but had no effects on the other measures. A controlled breathing rate is needed for a reliable assessment of cardiac vagal outflow by the spectral analysis technique. The quantitative geometrical analysis of short-term RRI variability from the Poincaré plots and the time domain measure RMSSD were not significantly affected by changes in the breathing rate, suggesting that these indices are more suitable for the measurement of cardiac vagal outflow during the 'free-running' ambulatory conditions.
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              Endurance training guided individually by daily heart rate variability measurements.

              Purpose of this study was to test utility of heart rate variability (HRV) in daily endurance exercise prescriptions. Twenty-six healthy, moderately fit males were randomized into predefined training group (TRA, n = 8), HRV-guided training group (HRV, n = 9), and control group (n = 9). Four-week training period consisted of running sessions lasting 40 min each at either low- or high-intensity level. TRA group trained on 6 days a week, with two sessions at low and four at high intensity. Individual training program for HRV group was based on individual changes in high-frequency R-R interval oscillations measured every morning. Increase or no change in HRV resulted in high-intensity training on that day. If there was significant decrease in HRV (below reference value [10-day mean-SD] or decreasing trend for 2 days), low-intensity training or rest was prescribed. Peak oxygen consumption (VO(2peak)) and maximal running velocity (Load(max)) were measured in maximal treadmill test before and after the training. In TRA group, Load(max) increased from 15.1 +/- 1.3 to 15.7 +/- 1.2 km h(-1) (P = 0.004), whereas VO(2peak) did not change significantly (54 +/- 4 pre and 55 +/- 3 ml kg(-1) min(-1) post, P = 0.224). In HRV group, significant increases were observed in both Load(max) (from 15.5 +/- 1.0 to 16.4 +/- 1.0 km h(-1), P < 0.001) and VO(2peak) (from 56 +/- 4 to 60 +/- 5 ml kg(-1) min(-1), P = 0.002). The change in Load(max) was significantly greater in HRV group compared to TRA group (0.5 +/- 0.4 vs. 0.9 +/- 0.2 km h(-1), P = 0.048, adjusted for baseline values). No significant differences were observed in the changes of VO(2peak) between the groups. We concluded that cardiorespiratory fitness can be improved effectively by using HRV for daily training prescription.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 October 2018
                2018
                : 13
                : 10
                : e0205115
                Affiliations
                [1 ] Department of Natural Sciences in Kinanthropology, Faculty of Physical Culture, Palacký University Olomouc, Olomouc, Czech Republic
                [2 ] Faculty of Health, Discipline of Sport and Exercise Science, UC-Research Institute for Sport and Exercise, University of Canberra, Canberra, Australia
                [3 ] School of Health Sciences, Discipline of Biokinetics, Exercise and Leisure Sciences, University of KwaZulu-Natal, Durban, South Africa
                University of Bourgogne France Comté, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-7236-8328
                Article
                PONE-D-18-18684
                10.1371/journal.pone.0205115
                6175275
                30296274
                84c93687-a3c5-467d-a997-a1e0f94c0557
                © 2018 Krejčí et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 June 2018
                : 19 September 2018
                Page count
                Figures: 0, Tables: 4, Pages: 12
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001824, Grantová Agentura České Republiky;
                Award ID: No 16-13750S
                This work was supported by the Czech Science Foundation (URL: gacr.cz) under Grant No 16-13750S. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Electrophysiological Techniques
                Cardiac Electrophysiology
                Electrocardiography
                Medicine and Health Sciences
                Cardiology
                Heart Rate
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Respiration
                Oxygen Consumption
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Respiration
                Oxygen Consumption
                Physical Sciences
                Mathematics
                Probability Theory
                Probability Distribution
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Respiration
                Breathing
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Respiration
                Breathing
                Biology and Life Sciences
                Sports Science
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Height
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Height
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Respiration
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Respiration
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                All relevant data are within the paper and its Supporting Information files.

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