Association between heart rate variability threshold and post-exercise vagal reactivation.
The autonomic nervous system (ANS), through its vagal and sympathetic branches, regulates the heart rate (HR) behavior of the cardiovascular system (14). At rest, vagal tone is predominant in the heart, which results in bradycardia (9). During exercise, in order to supply the necessary metabolic demand, HR is increased, primarily due to reduced vagal modulation with concomitant increase in the sympathetic activity (9). This behavior of the ANS, which is required during exercise, also persists during post-exercise recovery of which HR recovery is subdivided into a phase of rapid and monoexponential decline in HR (Quick Step Recovery) followed by a phase of slow and sustained decline (Slow Recovery Phase). During the phase of rapid recovery, the decline in the HR is mainly dependent on the vagal reactivation. This is considered an important cardioprotective mechanism (9, 15), which is associated with an increased relative risk of mortality, especially in cardiac arrhythmias (1, 8).
The heart rate variability (HRV) is used in order to quantify the influence of the autonomic nervous system on the heart. The HRV comprises variations in the intervals, measured in milliseconds (ms) between consecutive beats of sinus origin (14). However, HRV rates depend on the steady pattern of data, a situation which is not found during recovery. Thus, Goldberger et al. (12) and Buchheit et al. (6) have developed methods to evaluate the autonomic recovery through the HRV. The behavior of the autonomic nervous system during exercise can be assessed by HRV threshold (HRVT). The HRVTH proposed by Lima and Kiss (16), has been appointed as the autonomic point of transition, in which the increase in HR would not be obtained by means of vagal withdrawal and would be influenced by the sympathetic activity (23). The HRVT is directly related to the first lactate (16) and ventilatory (21) threshold. Physical training has been touted as a way to improve the autonomic control of HR (18).
As previously stated, physical training has positive effects on autonomic modulation both at rest (24) and during exercise (18), showing increased vagal modulation when assessed by HRV. However, in addition to favoring a greater vagal predominance, it enables better vagal reactivation after exercise (better recovery) (5), allowing the physiological predisposition to new training stimuli. Yamamoto et al. (24) demonstrated that the autonomic post-exercise recovery develops after only 4 wks of aerobic training, thus showing to be an interesting parameter to observe the effect of aerobic exercise training. The same study demonstrated that the autonomic modulation at rest did not change after 4 wks of training, unlike the HR recovery and the physical performance after intervention. Buchheit et al. (4) also pointed out that the higher vagal modulation at rest has no direct relationship with the best post-exercise recovery. Hence, vagal tone behavior during exercise may have a greater relationship with vagal recovery, although such a relationship has not yet been verified.
Thus, the present study was designed to investigate the relationship between autonomic modulation during exercise on autonomic post-exercise recovery, especially in the fast recovery phase.
Eleven male subjects were evaluated (aged 24.8 [+ or -] 4.4 yrs, body weight 76.1 [+ or -] 10.9 kg, height 175 [+ or -] 8.6 cm). On order to participate in the study subjects should meet the following eligibility criteria: be a non-smoker, not have any cardiovascular disease, not make continuous use of any substances which could affect the cardiovascular or autonomic nervous system. All subjects assessed completed the term of free informed consent, following the guidelines of the Brazilian legislation for human studies.
This study was conducted in 2 days of evaluation with a 72-hr break between them. Throughout the experimental protocol, participants were instructed not to ingest alcoholic or caffeinated drinks and not to practice physical exercise in the 24 hrs preceding the tests.
On the first day of assessment, anthropometric measurements of body mass and height were performed. After obtaining such measures, the assessed subjects remained lying in the supine position for 10 min. Over this period, the HR at rest (HR rest) (Polar RS800CX, Polar Electro Oy, Finland) was assessed on a beat-to-beat basis, thus allowing the analysis of the heart rate variability at rest (HRV rest). At the end of the rest period, subjects were submitted to a progressive exercise test on a cycle ergometer (167 Ergocycle, Ergofit, Germany).
The progressive exercise protocol, adapted from Lucia et al (17), began with a power of 50 W for 2 min having an addition of 25 W every minute, from the second minute on. Throughout the exercise test, rating of perceived exertion (RPE) was assessed at the end of each stage by means of the Borg 10-point scale (3). Maximum heart rate (HR max) was obtained from the stress test, which was defined as the highest HR value reached during the incremental test. Maximum power (W max) was defined as the last stage of the progressive test that accompanied a HR max obtained [greater than or equal to]90% of the value obtained by the formula 220-age and a subjective exertion scale response above 9 points.
Seventy-two hours after the incremental test, subjects returned to the laboratory where they remained in a supine position for 10 min in order to measure the HR rest and RMSSD rest. After the rest period, the subjects underwent 5 min of exercise in the cycle ergometer at 50% W max followed by 5 min of recovery in the supine position.
Heart Rate Variability Threshold Assessment
The HR data obtained during the incremental test for identification of the HRVT were used in the identification of the HRVT. The HRVT comprises the stage of the progressive test in which the SD1 index of the Pointcare Plotting showed a value below 3 ms. In order to identify the SD1, the HR data were transmitted from the heart rate monitor (Polar RS800CX, Polar Electro Oy, Finland) for the Polar Pro Trainer (Polar [R]) software via the infrared interface where the data were stored. Then, the data were sent to the Kubios HRV software, passing through the "moderate" filter and curve adjustment in "smooth priors", windowing was performed at 1-min basis and the analysis of the SD1 index was obtained at each stage of the incremental test. The HRVT was determined at the point in which the SD1 index showed a value below 3 ms.
Rest and Recovery of heart rate variability
The autonomic modulation at rest was measured by the RMSSD index. The HRV rec was assessed during the recovery period after exercise at 50% of W max, which was obtained through the RMSSD index from the 2nd-min to the 5th-min of the recovery period (5). The analyses of the indices were obtained by Kubios HRV software, "moderate" filter and "smooth priors" curve adjust with windowing regarding the last 5 min at rest and the final 3 min of recovery. Since the RMSSD data do not show a normal distribution, logarithmic transformation of the data was used (LnRMSS[D.sub.Rest]; LnRMSS[D.sub.2-5min]).
Data were treated through the mean [+ or -] SD. Pearson's correlation (P<0.05) was performed to verify the interaction between the HRVT and the vagal reactivation, as measured by RMSS[D.sub.2-5min]. All analyses were performed by using the SPSS 20 software.
Table 1 shows the measures at rest, at maximal progressive aerobic exercise, and the percentage of the maximum percentage load at which the HRVT was identified. The maximum load percentage applied to the HRVT was 0.40 [+ or -] 0.14. Regarding the correlation between the HRVT and the vagal reactivation, r = 0.35 (P = 0.293) was observed between the variables (Figure 1).
[FIGURE 1 OMITTED]
To our knowledge, this study is the first to evaluate the relationship between HRVT and vagal reactivation. We expected a significant correlation between both, since they are mediated by the same autonomic axis and influenced by similar factors. However, according to the results, it was observed that the vagal reactivation is not entirely associated with the HRVT, that is, the best vagal reactivation is not directly explained by a late vagal withdrawal.
Several factors influence vagal reactivation () with emphasis on training (5) and on the maximal cardiorespiratory capacity (20). Ostojic et al. (20) compared the HR recovery in soccer athletes (V[O.sub.2] max >60 mL x [kg.sup.-1] x [min.sup.-1]) and sub-athletes (V[O.sub.2] max >50 mL x [kg.sup.-1] x [min.sup.-1]), and it was found that those who
were considered athletes showed better HR recovery in the first 20 sec of recovery after the maximal exercise test.
Demonstrating the influence of cardiorespiratory fitness on the behavior of vagal reactivation assessed by the HR recovery, Buchheit and Gindre (5) found a direct relationship between the physical training load and post-exercise vagal recovery. In this study, it was found that individuals with a higher training load had better autonomic recovery after the maximal test. However, even if the correlation is significant, the value is moderate (0.55). This study did not assess the type of training the subjects were submitted to, and the high intensity training with intervals has provided a better vagal reactivation after exercise when compared to the continuous aerobic training.
Besides aerobic capacity and training load, other factors influence autonomic recovery, such as intensity (10) and type of exercise (19), catecholamine concentration (13), and body temperature stabilization (22). Body temperature regulation appears to be the primary factor via activated by external mechanisms that are capable of enhancing vagal reactivation, such as obtained by water immersion (2, 7). Possibly such responses concerning body temperature restoration and/or vascular tone are cofactors likely to improve vagal reactivation, which may hinder the direct association of the recovery with the HRVT.
Recently, parasympathetic suppression has been reported by Oliveira and colleagues (10) who used the RMSS[D.sub.30s] index in the first 5 min of recovery after an incremental test. Their work indicates that the autonomic recovery may be associated with both vagal reactivation and decrease in the sympathetic modulation after the maximal exercise. However, at submaximal exercise, below the second ventilatory threshold, autonomic recovery was almost exclusively dependent on the vagal reactivation (9).
This study evaluated the HRVT, through the method proposed by Lima and Kiss (16), which is based on the analysis of the SD1 index. There are other ways to analyze the HRVT, such as by means of the HRV spectral analysis proposed by Quinart et al. (21). The proposal would give rise to other forms of analysis.
A weak correlation was found between the HRVT and the vagal reactivation. Therefore, the findings from this study indicate that post-exercise vagal reactivation is not exclusively associated with higher vagal modulation during exercise.
This study received financial support from Coordenagao de Aperfeigoamento de Pessoal de Nivel Superior (CAPES).
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Thiago Seixas Duarte , Antonio Jose Ferreira Junior , Edson Campana Rezende , Leonardo Coelho Pertence , Joao Carlos Bouzas Marins , Jorge Roberto Perrout de Lima 
 laboratory of Motor Assessment, Faculty of Physical Education and Sports, Federal University of Juiz de Fora, Brazil,  Faculty Presbiteriana Gammon, Lavras, Brazil,  Laboratory of Human Performance, Federal University of Vigosa, Brazil
Address for correspondence: Thiago Seixas Duarte, Faculdade de Educagao Ffsica e Desportos, Universidade Federal de Juiz de Fora, Campus Universitario, Martelos, Juiz de Fora--MG, Brazil. Zip-code: 36036-900; Phone +55328837-9166; Email: email@example.com
Table 1. Descriptive Data of the Subjects. HR Rest LnRMSSD Maximal HR % Maximal (beats x Rest (ms) (beats x Load (W) [min.sup.-1]) [min.sup.-1]) 64.5 [+ 1.59 [+ 189.63 [+ 0.40 [+ or -] 7.65 or -] 0.19 or -] 10.28 or -] 0.14
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|Author:||Duarte, Thiago Seixas; Ferreira, Antonio Jose, Jr.; Rezende, Edson Campana; Pertence, Leonardo Coelh|
|Publication:||Journal of Exercise Physiology Online|
|Date:||Oct 1, 2014|
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