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Arquivos Brasileiros de Cardiologia

Print version ISSN 0066-782X

Arq. Bras. Cardiol. vol.103 no.3 São Paulo Sept. 2014  Epub Aug 01, 2014 

Original Articles

Effects of Exercise Training on Heart Rate Variability in Chagas Heart Disease

Bruno Ramos Nascimento1  2  3 

Márcia Maria Oliveira Lima3  4 

Maria do Carmo Pereira Nunes1  2  3 

Maria Clara Noman de Alencar2 

Henrique Silveira Costa3 

Marcelo Martins Pinto Filho1  2 

Vitor Emanuel Serafim Cota1 

Manoel Otávio da Costa Rocha1  3 

Antonio Luiz Pinho Ribeiro1  2  3 

1Faculdade de Medicina da Universidade Federal de Minas Gerais, Belo Horizonte, MG - Brazil

2Serviço de Cardiologia e Cirurgia Cardiovascular do Hospital das Clínicas da UFMG, Belo Horizonte, MG - Brazil

3Pós-graduação em Infectologia e Medicina Tropical - Faculdade de Medicina da UFMG, Belo Horizonte, MG - Brazil

4Escola de Fisioterapia da Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG - Brazil



Heart rate variability (HRV) is a marker of autonomic dysfunction severity. The effects of physical training on HRV indexes in Chagas heart disease (CHD) are not well established.


To evaluate the changes in HRV indexes in response to physical training in CHD.


Patients with CHD and left ventricular (LV) dysfunction, physically inactive, were randomized either to the intervention (IG, N = 18) or control group (CG, N = 19). The IG participated in a 12-week exercise program consisting of 3 sessions/week.


Mean age was 49.5 ± 8 years, 59% males, mean LVEF was 36.3 ± 7.8%. Baseline HRV indexes were similar between groups. From baseline to follow-up, total power (TP): 1653 (IQ 625 - 3418) to 2794 (1617 - 4452) ms, p = 0.02) and very low frequency power: 586 (290 - 1565) to 815 (610 - 1425) ms, p = 0.047) increased in the IG, but not in the CG. The delta (post - pre) HRV indexes were similar: SDNN 11.5 ± 30.0 vs. 3.7 ± 25.1 ms. p = 0.10; rMSSD 2 (6 - 17) vs. 1 (21 - 9) ms. p = 0.43; TP 943 (731 - 3130) vs. 1780 (921 - 2743) Hz. p = 0.46; low frequency power (LFP) 1.0 (150 - 197) vs. 60 (111 - 146) Hz. p = 0.85; except for high frequency power, which tended to increase in the IG: 42 (133 - 92) vs. 79 (61 - 328) Hz. p = 0.08).


In the studied population, the variation of HRV indexes was similar between the active and inactive groups. Clinical improvement with physical activity seems to be independent from autonomic dysfunction markers in CHD.

Key words: Chagas Cardiomyopathy; Exercise; Heart Rate



A variabilidade da frequência cardíaca (VFC) é marcador de gravidade da disfunção autonômica. Os efeitos do treinamento físico sobre índices de VFC na miocardiopatia chagásica (MPC) não são bem estabelecidos. Objetivo: Avaliar as mudanças nestes índices em resposta ao treinamento físico na MPC.


Pacientes com MPC e disfunção do ventrículo esquerdo (VE), fisicamente inativos, foram aleatorizados para os grupos intervenção (GI, N = 18) e controle (GC, N = 19). O GI participou de um programa de exercícios de 12 semanas, três sessões/semana.


A idade média foi de 49,5 ± 8 anos, 59% homens, FEVE de 36,3 ± 7,8%. Índices basais de VFC foram similares. Do basal ao seguimento, observamos no GI aumento da potência total (TP): 1.653 (IQ 625 - 3.418) para 2.794 (1.617 - 4.452) ms, p = 0,02) e potência de frequência muito baixa: 586 (290 - 1.565) para 815 (610 - 1.425) ms, p = 0,047), mas não no GC. A variação (pós/pré) dos índices de VFC foi similar: SDNN 11,5 ± 30,0 vs. 3,7 ± 25, 1 ms, p = 0,10; rMSSD 2 (6 - 17) vs. 1 (21 - 9) ms, p = 0,43; TP 943 (731 - 3.130) vs. 1.780 (921 - 2.743) Hz, p = 0,46 e potência de frequência baixa (LFP) 1,0 (150 - 197) vs. 60 (111 - 146) Hz, p = 0,85, exceto pela potência de alta frequência, que teve tendência a aumento no GI: 42 (133 - 92) vs. 79 (61 - 328) Hz, p = 0,08).


Na população estudada, a variação dos índices de VFC foi similar entre os grupos ativo e inativo. A melhora clínica com o treinamento físico parece ser independente de marcadores de disfunção autonômica na MPC.

Palavras-Chave: Cardiomiopatia Chagásica; Exercício; Frequência Cardíaca


Chagas disease is an infection caused by the Trypanosoma cruzi , transmitted primarily by insects of the Triatominae family. It is estimated than 8-10 million people are infected worldwide, especially in Latin America, where the disease is still endemic1 , 2. Chagas cardiomyopathy (CHD) affects 20-40% of patients with the chronic form, and its pathogenesis is closely linked to neurogenic mechanisms, microvascular dysfunction, autoimmune processes and direct injury by the parasite2 - 4.

Cardiac autonomic dysfunction is known to be a characteristic and early finding of Chagas disease5 - 9, possibly related to deposits of autoantibodies10, causing desensitization of cardiac neurotransmitter receptors, early affecting cardiac vagal control11. The heart rate variability (HRV) is an indirect measure of the interactions between the sympathetic and parasympathetic systems, mediated by several physiological mechanisms such as reflex arcs, release of cytokine and vasoactive substances, among others. The values of HRV measurements in the time and frequency domains are known diagnostic, prognostic markers and predictors of complications, including mortality, in several systemic diseases, such as heart failure and sepsis12 - 14.

Among the non-pharmacological measures in the treatment of cardiovascular diseases, regular physical activity as a factor of vagal tone increase has shown a major impact on HRV indices and association with training intensity15 , 16. Significant HRV impairment has been demonstrated in CHD17, but studies suggest that, unlike other forms of heart failure, there seems to be a change in the association between physical exercise and HRV18, with no significant improvement of their indices being observed after supervised training programs5.

The objective of this study is to evaluate the changes of HRV indexes in the time and frequency domains in patients with Chagas heart disease and left ventricular dysfunction undergoing supervised exercise training for 12 weeks, compared with the inactive group of patients with the same clinical characteristics.


Study population and inclusion criteria

A complete description of the study design has been published previously19. Briefly, 145 subjects were recruited from the Cardiology and Chagas Disease Outpatient Clinics of Hospital das Clinicas, Universidade Federal de Minas Gerais. The volunteers were interviewed to obtain clinical history and current life habits. To be eligible for the study, patients had to have a previous diagnosis of CHD, based on at least two positive serologic tests for Trypanosoma cruzi antibodies, along with the presence of left ventricular dysfunction and capacity to attend the training program fully4. Patients with comorbidities, patients with pacemaker or resynchronization device and those that self-reported to be physically active were excluded. Forty patients met the inclusion criteria.

All patients had been clinically stable for at least three months, had sinus rhythm and were receiving standard medical therapy20. After randomization, carried out through an electronic system, patients were allocated to the intervention group (IG) or control group (CG). Informed consent was obtained from all patients, and the study was approved by the Research Ethics Committee of Universidade Federal de Minas Gerais, in accordance with the Declaration of Helsinki.

Study design and procedures

At the moment of inclusion, all patients underwent clinical examination, laboratory tests, 12-lead ECG, symptom-limited exercise stress test to establish training heart rate (HR) intensity, 6-minute walk test (6MWT), echocardiography and 24-h Holter monitoring to assess HRV indices. Functional capacity was assessed by Goldman and New York Heart Association (NYHA) criteria. Severity of cardiac impairment was determined by echocardiographic indices (ejection fraction, EF, and left ventricular end diastolic volume, LVEDV). All tests were performed in a two-week period before and after aerobic training. Examiners were blinded to the results of the other tests.

A symptom-limited exercise stress was performed on a treadmill (Digistress Pulsar Micromed, Brasilia, Brazil) using the Bruce protocol. Continuous monitoring was performed with 12-lead ECG, recorded every minute. Blood pressure was measured manually with a cuff in the standing position in the last 30 seconds of each stage and for four minutes in the recovery period. Heart rate was determined by ECG and the chronotropic response was calculated as the achieved percentage of heart rate predicted for age, according to the Astrand formula (220 - age) at peak exercise. The 6-minute walk test (6MWT) was performed according to standard protocol21 with two walks at maximum walking speed in a 30-meter corridor, separated by a 15-minute interval. A HR monitor (Polar FS2, Electro, Kempele, Finland) and a pulse oximeter (NoninOnyx 9500, Plymouth, Minnesota, USA) were used in the assessment.

24 h-Holter monitoring was performed using a portable three-channel tape recorder (Dynamics, Cardios, São Paulo, Brazil), at the beginning and end of the study. Subjects were instructed to maintain their normal daily activities during the recording. HRV analysis was performed when a good quality tracing of at least 18 h was available on a Burdick/DMI/Cardios Hospital Holter System (Spacelabs Burdick, Deerfield, Wisconsin, Sao Paulo, Brazil). Tracings were analyzed for five minutes every hour, and the sleep period with the loweat HR was used as reference.

The HRV indices were calculated in the time domain (SDNN: standard deviation of normal RR intervals; rMSSD: Root Mean Square of Successive Differences) and frequency domain (TP, total power; VLFP: very low frequency power; LFP: low frequency power; HFP, high frequency power).

Physical training protocol

The IG patients participated in a supervised program consisting of three sessions per week, on alternate days, totaling 36 sessions in 12 weeks, as detailed in a previous publication19. Briefly, the protocol consisted of warm-up exercises for 15 minutes, followed by a 30 minute-walk and 15 minutes of cooling down. Exercise intensity was based on peak HR achieved on a treadmill test limited by symptoms and calculated by the Karvonen formula (maximal HR - HR at rest) 50-70% + resting HR22 and was adjusted throughout the program. The CG patients were instructed to maintain their daily routines and were asked about physical activities during consultations.

Statistical Analysis

Statistical analysis was performed using SPSS software version 20.0 for Mac OSX (SPSS Inc., Chicago, Illinois, United States of America). For this analysis, a sample of 36 patients was calculated to detect a 15% difference in SDNN variation between groups, with α error = 5% and β error = 20%. Descriptive analysis of continuous and categorical variables was performed. The presence or absence of normal distribution of variables was performed with the Shapiro-Wilk's test. Continuous data were expressed as mean ± standard deviation or as median and interquartile (IQ) range Q1 - Q3 (25-75%) when presenting with non-normal distribution. Categorical variables were expressed as absolute values and percentages. Variations in measurements at the beginning and end of the study were expressed as delta values (Δ).

To evaluate the changes in continuous variables in relation to baseline, the paired Student's t test was used for normally distributed variables or paired Wilcoxon test if the distribution was not normal. The comparison of means between groups was performed using Student's t test for continuous variables with normal distribution and the Mann-Whitney test for those with non-normal distribution. The comparison of categorical variables between groups was performed by Chi-square test. When necessary, analysis of variance transformations were performed. A two-tailed significance level of 0.05 was considered statistically significant.


Of the 145 patients evaluated, 40 met the inclusion criteria. Throughout the study, two patients died (one patient in each group) and one patient did not complete the proposed procedures. The final sample consisted of 37 subjects: 18 in the IG and 19 in the CG. Demographic, clinical and echocardiographic characteristics of the groups are shown in Table 1. The male gender predominated and most patients had NYHA functional class I, with mean left ventricular ejection fraction (LVEF) < 40%. The only characteristic that differed between IG and CG was body mass index (BMI). Regarding medication, all patients received angiotensin-converting enzyme inhibitors (ACEI); 22.2% and 21.1% (p = 1.00), respectively, were taking beta-blockers; 22.2% and 15.8% (p = 0.693) were taking digitalis; 77.8% and 84.2% (p = 0.62) used amiodarone. The IG patients had complete adherence to the training program and, in the event of non-attendance, a new session was scheduled.

Table 1 Comparison of clinical, demographic and echocardiographic characteristics between the control and intervention groups 

Characteristic Control Group (n = 19) Intervention Group (n = 18) p
Male gender (n, %) 12 (63.2%) 10 (55.6%) 0.74
Age, years (mean ± SD) 50.1 ± 6.6 48.6 ± 9.0 0.55
BMI (kg/m2, median IQ) 22.5 (21.5-24.8) 24.6 (23.7-27.9) 0.042*
SBP at rest (mmHg, median IQ) 120 (110-130) 115 (110-120) 0.13
DBP at rest (mmHg, median IQ) 80 (70-80) 80 (70-80) 0.987
Functional class NYHA I/II (n, %) 14 (73.7%)/5 (26.3%) 10 (55.6%)/8 (44.4%) 0.31
Functional class Goldman I/II/III (n, %) 12 (63.2%)/5 (26.3%)/2 (10.5%) 10 (55.6%)/7 (38.9%)/3 (8.1%) 0.66
LVEF (%, mean ± SD) 37.1 ± 7.6 36.6 ± 7.4 0.84
LVDD (mm, mean ± SD) 50.3 ± 5.4 50.9 ± 7.3 0.77
LVDS (mm, mean ± SD) 64.0 ± 4.9 64.2 ± 5.6 0.90

SD: standard deviation; LVEF: left ventricular ejection fraction; BMI: body mass index; IQ: interquartile range (25-75); NYHA functional class - New York Heart Association; DBP: diastolic blood pressure; SBP: systolic blood pressure; LVDD: left ventricular diameter during diastole; LVDS: left ventricular diameter during systole.

In relation to the baseline 12-lead ECG, the characteristics were similar between the IG and CG groups (Table 2), except for lower HR in IG and greater PR interval in this group. Regarding the 24-h Holter variables, the groups were also similar (Table 2), except for mean and minimum HR, which were lower in the IG (Table 2).

Table 2 Comparison of electrocardiographic baseline and 24-h Holter variables between the control group and the intervention group 

Variable Control group (n = 19) Intervention group (n = 18) p
Baseline ECG
HR (bpm, median IQ)) 64(55-73) 56 (52-60) 0.036*
PRi Interval (ms, median IQ) 160 (151-194) 192 (175-230) 0.029*
QRS duration (ms, median IQ) 135 (96-150) 147 (118-154) 0.343
QTc Interval (ms. mean ± SD) 437 ± 31 448 ± 33 0.300
LBBB (n, %) 1 (5.3%) 0 1.000
RBBB (n, %) 10 (52.6%) 14 (77.8%) 0.170
LAHB (n, %) 5 (26.3%) 10 (55.5%) 0.099
Baseline 24-h Holter
Mean HR (mean ± SD) 67.7 ± 7.7 61.7 ± 7.5 0.023*
Minimum HR (mean ± SD) 47.2 ± 5.7 42.8 ± 7.2 0.044*
AVB (1st and 2nd degree) 3 (15.8%) 5 (27.8%) 0.447
Supraventricular ectopic beats 58 (10-697) 133 (16-401) 0.903
Supraventricular tachycardia 0 (0-1) 0(0-1) 0.679
Ventricular ectopic beats 851 (583-2137) 1347 (314-2624) 0.738
Ventricular tachycardia 0 (0-1) 2(0-8) 0.252

AVB: atrioventricular block; RBBB: right bundle branch block; LBBB: left bundle-branch block; SD: standard deviation; HR: heart rate; LAHB: left anterior hemiblock; IQ: interquartile range 1–3 (25-75%).

*significant p value.

At the functional assessments at the end of the study, there was a significant improvement in Goldman functional classification in IG patients. At the stress test, although baseline and post-training VO2 max was similar between the groups, its variation was significantly higher in IG, as well as a significantly greater increase in test time in the IG compared to the CG (Table 3). At 6-minute walk test, the distance walked at baseline was similar between the groups, but at the end of the study this distance was significantly higher in IG; the variation was also higher when compared to the baseline (Table 3).

Table 3 Comparison of changes in clinical functional variables, of exercise stress test and the six-minute walk test between the control group and the intervention group 

Variable Control group (n = 19) Intervention Group (n = 18) p
Improvement in NYHA functional class (n, %) 0 2 (11.1%) 0.23
Improvement in Goldman functional class (n, %) 1 (5.3%) 8 (44.4%) 0.008*
ST: VO2 maximal pre/post-training (ml/kg/min, mean ± SD) 31.4 ± 7.2/33.5 ± 6.8 27.3 ± 5.7/34.3 ± 4.9 0.07/0.71
ST: ΔVO2 maximal (ml/kg/min, mean ± SD) 2.2 ± 4.8 7.0 ± 3.6 < 0.001*
ST: time of test pre/post-training (min, mean ± SD) 9.4 ± 3.0/10.2 ± 3.0 7.6 ± 2.4/10.6 ± 2.2 0.05/0.68
ST: Δ time of test (min, mean ± SD) 0.8 ± 2.0 3.0 ± 1.6 < 0.001*
6MWT: distance walked pre/post-training (m, mean ± SD) 521.8 ± 91.1/530.3 ± 69.1 525.4 ± 85.5/593.3 ± 78.5 0.902/0.014*
6MWT: Δ of walked distance (m, mean ± SD) 8.4 ± 49.1 67.8 ± 54.7 0.001*

SD: standard-deviation; NYHA: New York Heart Association; ST: stress test; VO2: maximal oxygen uptake; 6MWT – six-minute walk test.

*Statistically significant p value.

When evaluating the HRV indices in the time domain (SDNN and rMSSD), no statistically significant variations were observed in the values at the end of the study when compared to the baseline in both groups, and ΔSDNN and ΔrMSSD were similar between them (Table 4). Regarding HRV indices in the frequency domain (TP, VLFP, LFP and HFP), there was significant increase in TP and VLFP compared to baseline in IG, but not in CG. The ΔTP and ΔVLFP values, however, were similar between groups. Regarding HFP, there was an increase in IG and decrease in the CG (no significant difference compared to baseline) and there was a non-statistically significant trend of ΔHFP difference between groups: 79 (61-328) vs. -42 (-133 - 92) Hz, p = 0.083.

Table 4 Indices of heart rate variability at baseline and at the end of the study 

Variable Group Pre Post Delta (Δ) p (pre vs. post) p (dif.)
SDNN (ms. mean ± SD) GC (n = 19) 126.4 ± 31.3 137.9 ± 43.0 11.5 ± 30.0 0.112 0.102
GI (n = 18) 163.9 ± 54.7 160.2 ± 50.0 -3.7 ± 25.1 0.536
rMSSD (ms. median IQ) GC (n = 19) 27 (23-44) 39 (19-53) 2 (-6-17) 0.542 0.429
GI (n = 18) 44(30-83) 41 (32-74) -1 (-21-9) 0.678
TP (Hz. median IQ) GC (n = 19) 1526 (709-2850) 2423 (1132-4234) 943 (-731-3130) 0.091 0.521
GI (n = 18) 1653 (625-3418) 2794 (1617-4452) 1780 (921-2743) 0.017*
VLFP (Hz. median IQ) GC (n = 19) 666 (427-1230) 1215 (527-3003) 682 (-208-2019) 0.126 0.849
GI (n = 18) 586 (290-1565) 815 (610-1425) 371 (27-1171) 0.047*
LFP (Hz. median IQ) GC (n = 19) 124 (77-447) 202 (50-482) -1.0 (-150-197) 0.629 0.849
GI (n = 18) 192 (38-418) 161 (76-292) 60 (-111-146) 0.733
HFP (Hz. median IQ) GC (n = 19) 166 (86-291) 154 (62-422) -42 (-133-92) 0.494 0.083
GI (n = 18) 190 (87-443) 256 (207-462) 79 (-61-328) 0.156

SD: standard-deviation; CG: control group; IG: intervention group; HFP: high-frequency power; IQ: interquartile range (25-75); LFP: low-frequency power; pre-post: comparison of the results of the group at the beginning and end of the study; rMSSD: root mean square of successive differences; SDNN: standard deviation of NN intervals; TP: total power; VLFP: very low-frequency power.

*Statistically significant p value.


In this prospective, randomized therapeutic study in patients with Chagas cardiomyopathy and left ventricular dysfunction, exercise training resulted in no significant changes in HRV indices, although it resulted in improved functional class, as well as stress 6-minute walk test variables. We observed an increase in only two indices of HRV in the frequency domain (TP and VLFP) compared to the baseline in the IG, but with statistically similar variation between groups. Additionally, there was a trend towards greater positive variation of HFP in IG compared to CG.

HRV is reduced in Chagas patients with and without the cardiac form (including the indeterminate form)6 , 7 , 9 , 18 , 23, and the reduction in its indices is correlated with levels of antimuscarinic antibodies10, which are increased in infected patients. The levels of these antibodies seem to be associated with clinical markers of autonomic dysfunction24, including the reduction of the chronotropic response to stress, suggesting clinical and physiopathological significance in Chagas disease25. It is controversial the existence of an association between reduced HRV autonomic dysfunction marker and severity of ventricular dysfunction or the evolutionary stage of the disease26 - 31.

Although the prognostic value of HRV reduction has not been demonstrated in Chagas' disease, it is known that in several cardiac and systemic diseases, reduced HRV is a strong and independent prognostic marker, with good prediction of adverse events12 - 14. In heart failure from other causes, there is an association between reduced indices with adverse events, such as decompensation, hospital readmissions, ventricular dysfunction progression and mortality32 - 34.

Some methodological issues should be considered in the analysis of our data, especially regarding the variability of HRV indices between different measures. The reproducibility of these variables at rest and during stress has been previously demonstrated35, but other studies suggest that although the indices in the time domain (SDNN and rMSSD) are reproducible, the same is not true in relation to the frequency domain variables obtained by spectral analysis36 , 37. Thus, considering the sample size calculation based on the time domain index, the interpretation of negative results in the frequency domain should be made with caution. Furthermore, our data dispersion was generally higher than that observed in those studies.

Regular physical activity is known to be beneficial in heart failure38, with improved functional capacity and possible prognostic impact. Pooled data suggest an effect on serum prognostic markers such as B-type natriuretic peptide and functional variables in specific subgroups39. Moreover, supervised activity programs have a beneficial effect on HRV indices in healthy subjects and in patients with ventricular dysfunction of different etiologies at different stages and clinical contexts15 , 16 , 40 , 41, data that somehow have biological plausibility, considering the abnormal behavior of the sympathetic and parasympathetic modulation in the disease. In a way, it would be possible to propose the assessment of HRV as an objective marker of the beneficial effects of physical training.

Similarly to ventricular dysfunction from other etiologies, physical training seems to have a beneficial effect in patients with Chagas cardiomyopathy, both in functional capacity and mortality8 , 19 , 42. However, the beneficial effect of exercise training on cardiac autonomic control, observed in other diseases, has not been demonstrated in Chagas heart disease.

Sousa et al18 verified that the strong association observed in normal individuals between the intensity of physical activity and vagal HRV indices was not present in chagasic patients, suggesting that in Chagas disease, the usual vagotonic effect of exercise is not observed. More recently, Souza et al18 evaluated indices of the time domain before and after a supervised exercise program in 18 chagasic patients and found no differences in the indices after training5. This lack of response expected from the increased vagal tone with aerobic training could be explained by the characteristics of the autonomic dysfunction in early Chagas disease, relatively independent from left ventricular dysfunction and associated to antimuscarinic autoantibodies1. Another possibility is that the impairment of the cardiac excitoconductive system, particularly the sinus node1, impair the capacity of the parasympathetic ANS to modulate the beat-to-beat variation, typical of HRV.

At any rate, one might suspect that the clinical benefits observed with aerobic training in patients with Chagas cardiomyopathy do not involve the potential benefits of increased vagal tone, such as a decrease in the risk of sudden death18. Despite methodological considerations in the evaluation of HRV, this hypothesis has been consistently tested in our study, with an exercise program of which effectiveness was assessed clinically and functionally, and which application did not result in any significant changes in HRV indices.


The analysis of HRV indices showed greater variability than initially expected, which may be related to physiopathological characteristics of Chagas heart disease. For this reason, sampling limitations may have hindered the detection of statistical differences between the groups (type I error). The trend to the difference observed between the groups regarding ΔHFP could be confirmed or not with a larger sample. Furthermore, in spite of the sample randomization and considerable similarity between the groups, small differences in baseline (such as mean and minimum HR at Holter) can influence the interpretation of results.

The time of exercise training may also have been insufficient for the detection of changes, considering the sample size, as well as its intensity (mild to moderate). However, longer training periods also did not result in significant changes in HRV indices, as shown in a previous study5. Moreover, the absence of isometric exercises, as recommended by guidelines for cardiac rehabilitation, may also have contributed to the negative result. Finally, the effect of training in the IG could have been more objectively evaluated through functional testing with analysis of expired gases.


In the studied population, exercise training did not significantly alter HRV indices in Chagas patients with LV dysfunction, although it resulted in functional improvement. The only changes observed in relation to baseline were increased TP and VLFP in the IG, with no significant difference in changes between groups. The data are consistent with previous publications and suggest that the clinical benefits of physical conditioning in Chagas heart disease are independent from HRV indices. Future studies in larger populations are needed in order to reach more definitive conclusions about the behavior of HRV during physical conditioning in Chagas heart disease.

Study Association

This article is part of the thesis of Doctoral submitted by Márcia Maria Oliveira Lima, from Universidade Federal de Minas Gerais.

Sources of Funding

This study was funded by CNPq, FAPEMIG and CAPES.

Author contributions

Conception and design of the research: Nascimento BR, Lima MMO, Rocha MOC, Ribeiro AL; Acquisition of data: Lima, MMO, Nunes MCP, Alencar MCN, Costa HS, Pinto Filho MM, Cota VES; Analysis and interpretation of the data: Nascimento BR, Lima MMO, Pinto Filho MM, Cota VES; Obtaining financing: Rocha MOC, Ribeiro AL; Writing of the manuscript: Nascimento BR, Lima MMO; Critical revision of the manuscript for intellectual content: Rocha MOC, Ribeiro AL.


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Received: December 27, 2013; Revised: May 12, 2014; Accepted: May 13, 2014

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