Pediatric Cardiology (2018) 39:869–883
https://doi.org/10.1007/s00246-018-1881-0
REVIEW ARTICLE
Heart Rate Variability and Cardiopulmonary Dysfunction in Patients
with Duchenne Muscular Dystrophy: A Systematic Review
Talita Dias da Silva1,2 · Thais Massetti3 · Tânia Brusque Crocetta4 · Carlos Bandeira de Mello Monteiro3
Alex Carll2 · Luiz Carlos Marques Vanderlei5 · Carlie Arbaugh6 · Fernando Rocha Oliveira7 ·
Luiz Carlos de Abreu7 · Celso Ferreira Filho8 · John Godleski2 · Celso Ferreira8
·
Received: 4 December 2017 / Accepted: 4 April 2018 / Published online: 25 April 2018
© Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract
Duchenne muscular dystrophy (DMD) is a genetic recessive disorder with progressive muscle weakness. Despite the general
muscle wasting, degeneration and necrosis of cardiomyocytes have been the main causes of morbidity and death in individuals with DMD. Cardiac failure is generally preceded by disturbances in heart rate variability (HRV), and non-invasive
measurement of the autonomic nervous system has been an important tool to predict adverse cardiovascular events. Hence,
the application of HRV to study autonomic modulation in DMD individuals, and the establishment of correlations between
HRV and heart/lung diseases, age, and mortality will have the potential to improve quality of life and life expectancy of
individuals with DMD. In order to evaluate the state of the art in this field, we conducted a systematic search in Medline/
PubMed and BVS (virtual library in health) databases. We selected 8 studies using pre-defined criteria and meta-analysis
revealed decreased parasympathetic activity and increased sympathetic predominance in individuals with DMD as major
observations. Moreover, there is a strong association between diminished HRV and myocardial fibrosis with DMD. These
patterns are evident in patients at early-stage DMD and become more prominent as disease severity and age increase. Thus,
data minning clearly indicates that HRV assessment can be used as a predictor for sudden death in individuals with DMD.
The use of the HRV, which is inexpensive, ubiquitously available in clinics and hospitals, and a non-invasive analysis tool,
can save lives and decrease the morbity in DMD by alerting care givers to consider autonomic nervous system intervention.
Keywords Duchenne muscular dystrophy · Cardiomyopathy · Heart rate variability · Autonomic modulation
Abbreviations
DMD
Duchenne muscular dystrophy
HRV
Heart rate variability
BVS
Virtual library in health
Mean RR Mean of the RR intervals
RMSSD
Square root of the mean of squared differences
between successive beat intervals
SDNN
Standard deviation of all normal RR interval
SDANN
Standard deviation of the means of normal-tonormal heart periods obtained from all 5-min
periods throughout the whole data series
SDNNi
Average of the standard deviations of all
normal-to-normal intervals calculated from all
5-min periods of a 24-h recording period
* Talita Dias da Silva
ft.talitadias@gmail.com
Extended author information available on the last page of the article
pNN50
CVrr
PaCO2
LF
HF
VLF
ANS
BNP
FS
TTE
TD
MRI
cMR
LGE
WMA
QMT
ACE
Percentage of differences between RR intervals with an absolute value greater than 50 ms
Coefficient of variation of the RR interval
Partial pressure of carbon dioxide (CO2) in the
arterial blood
Low frequency
High frequency
Very low frequency
Autonomic nervous system
Brain natriuretic peptide
Fractional shortening
Trans-thoracic echocardiography
Tissue doppler imaging
Magnetic resonance imaging
Cardiac magnetic resonance
Late gadolinium enhancement
Wall motion analysis
Quantitative muscle testing
Angiotensin-converting enzyme inhibitors
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Vol.:(0123456789)
870
PRISMA
PICO
SMD
SD
Pediatric Cardiology (2018) 39:869–883
Preferred reporting items for systematic
reviews and meta-analyses
Population intervention comparison outcome
Standard mean differences
Standard deviation
for better therapies for individuals with DMD. Despite the
relevance of this subject, there have been no meta-analyses
on the relationship of DMD and HRV focusing upon the
prognosis of cardiac decline. Thus, this work aims to synthesize our knowledge of autonomic modulation in individuals
with DMD and establish correlations with heart diseases and
progression of DMD.
Introduction
Duchenne muscular dystrophy (DMD) is a X-linked recessive disorder affecting approximately 1 in 5000 males [1, 2].
The disease is characterized by progressive muscle wasting,
which affects to a variable extent the functionality of appendicular and axial muscles. Furthermore, muscles controlling
vital functions, such as respiration and cardiac movement,
are frequently affected [3]. In this context, the main cause
of death in DMD patients was respiratory failure, but the
development of personal devices for respiratory support
have significantly increased life expectancy of patients with
DMD. More recently, progressive cardiac disorders are the
main cause of DMD patient loss and morbity [4, 5].
Degeneration and necrosis of cardiomyocytes are among
the main traits of the Duchenne syndrome. Interestingly,
the majority of DMD patients are free of cardiovascular
symptoms, which limits the use of conventional diagnostic
methods to prevent heart failure and death of individuals.
However, DMD patients often exhibit abnormalities in circadian rhythm and heart rate variability (HRV), progressing
to severe congestive heart failure [4, 6–11]. Thus, assessment of cardiac electrophysiology could provide patterns of
dysfunction that could forecast the course of decline [12].
Accordingly, resting heart rate is a simple measurement with
important prognostic implications [13, 14]. In addition, HRV
provides a well-characterized, non-invasive means to quantitatively and indirectly assess the autonomic nervous system
(ANS) that controls cardiac physiology. The approach is
based on fluctuations of intervals between consecutive heart
beats (RR intervals) [13]. Indeed, alteration in HRV has been
demonstrated to predict adverse cardiovascular events .
Since 1995, several studies have assessed HRV of individuals with DMD. Reviewing the role of HRV in DMD
has considerable merit to identify common influences of
sympathetic and parasympathetic branches of the ANS,
pulmonary diseases, age and/or stage of the disease, influence of medication on improving autonomic modulation,
and the use of HRV as a predictor of sudden death. Since
heart failure has recently been identified as the leading cause
of death in DMD patients, a current working hypothesis is
that HRV may provide a reliable tool not only for assessing
autonomic-cardiac modulation, but also for predicting risk
of heart failure and mortality in DMD patients. The goal
of this review is to improve our understanding of the influence of DMD on the ANS and, thereby, provide support
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Method
This review was performed according to the Preferred
reporting items for systematic reviews and meta-analyses
(PRISMA) guidelines, thus providing a comprehensive
framework which objectively assesses indicators of quality
and risk of biases of included studies [15]. The protocol for
this review was not previously registered.
The scientific works were screened in the Medline/PubMed and BVS (virtual library in health) databases for the
following inclusion criteria: study populations with diagnosis of DMD and analysis of heart rate variability. There
were no restrictions on minimum sample size. Articles were
excluded if they (1) were not data-based (e.g., books, theoretical papers, or secondary reviews), (2) were not written
in the English language, (3) had populations not explicitly
identified as having a diagnosis of DMD, or (4) did not
include heart rate variability analysis.
All identified studies were collected in EndNote Web
(Thomson Reuters) and duplicates were removed. The article
search occurred in Medline/PubMed, PubMed Central, and
Web of Sciences databases, through keywords that should
be in all fields. We included articles that showed the terms:
“Muscular Dystrophy, Duchenne” AND “heart rate
variability”
“Muscular Dystrophy, Duchenne” AND “heart rate
variability” OR “autonomic nervous system”
Finally, reference lists of retrieved studies were thoroughly searched for additional relevant studies. Key words
and combinations of key words were used to search the electronic databases and were organized following the Population Intervention Comparison Outcome (PICO) model. In
this model, the search strategy was organized based on the
topics: population (P), intervention (I), control group (C),
and outcome (O), and several searches in the aforementioned
databases.
To select the articles, we used three steps as outlined in
Fig. 1: (Step 1) looking for articles in databases and reading
the titles and abstracts; (Step 2) exclusion of works by analysis of title, abstract, and other inclusion criteria; and (Step 3)
full-text analysis of findings within eligible articles [16, 17].
After performing the initial literature searches, each study
title and abstract was screened for eligibility according to
Pediatric Cardiology (2018) 39:869–883
871
Fig. 1 Steps used in study
selection
the inclusion criteria by TDS. Full texts of all potentially
relevant studies were subsequently retrieved and further
examined for eligibility. The PRISMA flow diagram (see
Fig. 2) provides more detailed information regarding the
selection process of studies.
Although the Cochrane Collaboration tool for assessing
the risk of bias can be useful when studies on a review topic
are numerous, given the relatively low number of papers on
HRV and DMD, we believe that this tool would prohibitively
diminish the number of papers in this review. We believe
that in the future the use of this tool would be feasible in an
updated review of the topic.
Data Analysis
We conducted a meta-analysis (using metafor package in
R software, version 3.1.2) to compare “DMD” to “Control” subjects in the studies that presented absolute values of mean standard deviation of all normal RR intervals
(SDNN), square root of the mean of squared differences
Fig. 2 Procedures for determination of eligibility. Adapted
from Moher et al. [18]
13
872
between successive beat intervals (RMSSD) and percentage
of differences between RR intervals with an absolute value
greater than 50 ms (pNN50), (mean ± SD) using “standard
mean differences” (SMD) ± 95% confidence intervals (CI).
Random effects models were used, as were appropriate tests
for heterogeneity.
Results
Study Selection
Distinct databases were searched and 38 works focused on
DMD and HRV were identified. Next, the 38 articles were
evaluated based on the redundancy, originality, and language
(English). These criterions excluded 25 out the 38 papers.
Further analysis screened out five works that did not include
any analysis of HRV indices. The remained 8 studies were of
an empirical nature designed as a cross-sectional case control [4, 11, 19, 20], cross-sectional [5, 21], prospective case
control cohort [19], and a prospective cohort [7] (Table 1).
Together, the dataset comprises 549 DMD and 142 healthy
participants, and covers distinct ethnic groups: Japanese [5,
7, 19, 22], German [21], Indian [4], Italian [11], and American [20].
The study conducted by Yotsukura et al. [19] was the first
study to analyze HRV in DMD patients. They investigated
whether HRV and circadian rhythm were useful in assessing autonomic dysfunction in DMD by comparing patients
with different stages of DMD (mild, moderate, and severe)
to normal patients. They found significant increases in relative sympathetic influence and decreases in parasympathetic
modulation. The pattern was highly associated with disease
progression and severity, and indicated that HRV and circadian rhythm of HRV are useful in assessing autonomic
dysfunction in DMD. These findings were later validated
[22] with a broader case control cohort study. Specifically,
they observed progression of autonomic imbalance in DMD
over a 9-year period as indicated by decreases in multiple
linear HRV parameters. Specifically, the authors determined
that progression of DMD was accompanied by a significant
progressive reduction in LF and HF indices, denoting an
increase in sympathetic tone and reduced vagal activity.
The most interesting finding was that there was a significant
decrease in the Mean RR, SDNN, and SDNN index in the
patients with DMD who died within 6 months.
The relationship between HRV and respiratory function
was examined by Lanza et al. [11] and Mochizuki et al. [5].
The study made by lanza et al. [11] showed weak correlations between forced vital capacity and HRV indices, while
Mochizuki et al. [5] found that HRV index [CVrr coefficient
of variation of the RR interval (%)] was negatively correlated with PaCO2. Based on the results, the authors proposed
13
Pediatric Cardiology (2018) 39:869–883
that low HRV may indicate respiratory insufficiency in
patients with DMD, since 73% of those with CVrr < 3%
had hypercapnia, and 47% of them had severe hypercapnia.
Lanza et al. [11] also found no correlation between HRV
and left ventricular ejection fraction. However, Thomas et al.
[20] concluded that HRV decreased, manifesting as a predominance of sympathetic modulation (decreased SDANN,
SDNN, RMSSD, and LF) and decreased parasympathetic
modulation (decreased HF) prior to the onset of heart failure
and associated with myocardial fibrosis. The authors suggest
that the persistent activation of the sympathetic nervous system in DMD can be a driving force in the pathological formation of myocardial fibrosis. The authors also evaluated the
effect of beta blocker use on HRV and found no significant
difference on the HRV indices between DMD patients using
beta blockers and DMD patients who did not; however, the
authors did not appear to control for age or disease severity.
Dittrich et al. [21] evaluated Holter ECG and HRV
parameters, Brain natriuretic peptide (BNP), trans-thoracic
echocardiography (TTE), tissue Doppler imaging (TD), and
magnetic resonance imaging (MRI) with late gadolinium
enhancement (LGE) and segmental wall motion analysis
(WMA) to assess diagnostic procedure efficiency of cardiac
dysfunction in DMD. They concluded that MRI with segmental LGE and WMA were better than TTE and TD in
exploring regional distribution and severity of myocardial
damage. ECG and HRV abnormalities were common in their
DMD population, but not highly predictive for segmental
and global left ventricular dysfunction. Another important
finding of this study was that 76% of DMD patients had
altered HRV, and the authors concluded that the clinical pattern of cardiomyopathy in DMD patients aged 6–20 years
was heterogeneous and not strictly age-dependent.
Inoue et al. [7] compared HRV indices with serum levels
of BNP and Fractional Shortening (FS), finding that even
when BNP and FS were normal, DMD patients presented
with decreased SDNN. The mean heart rate at night was
71 beats/min, compared to the mean heart rate throughout
the day of 57 beats/min. This heart rate difference had higher
sensitivity and specificity compared to other measures in
predicting abnormalities in SDNN. Also, the power of HF
and pNN50 decreased with age, but LF/HF and SDNN did
not vary with age. These findings again indicated HRV
decreases with the severity of the disease and age.
Dhargave et al. [4] and Mochizuki et al. [5] were the
only research groups to use short-term HRV measures (5
and 3 min, respectively) in DMD patients. Both found that
short-term HRV was as reliable as long-term analysis and
indicated relative sympathetic dominance in DMD patients
compared to controls.
The studies reviewed presented heterogeneous samples with
regard to age, level of disease, and medication. Some studies encouraged patients to avoid medication for 48 h before
Reference
Nature
Sample
Instrument
HRV Indices
1. Dittrich et al. [36]
Cross-sectional study
39 males with DMD;
No controls
Age
6–20 years old
Electrocardiogram (24-h
Holter)
2. Thomas et al. [35]
Cross-sectional case control
study
Electrocardiogram (24-h
74 boys with DMD;
Holter)
17 controls
Age
DMD—5–20 (12.6 ± 3.4) years
old;
Controls—11.1 ± 4.3 years
3. Dhargave et al. [4]
Cross-sectional case control
study
124 boys with DMD;
50 controls
Age
DMD—5–10 (7.9 ± 1.5) years
old;
Controls—5–10 years old
Cardiomyopathy was present in
Linear indices:
DMD patients 6–20 years old
Time domain: SDNN, SDANN,
independent of age. SDNN fell
SDNNi, rMSSD, and pNN50
below normal range in 76%
Frequency domain: None
of patients, as did SDANN in
Non-linear indices: None
68%, SDNNi in 49%, rMSSD
Time of analysis: 24 h
in 22%, and pNN50 in 27%,
indicating relative sympathetic
dominance over the heart
Decreased HRV in DMD
Linear indices:
patients compared to controls,
Time domain: SDNN, rMSSD,
as demonstrated by predomiand pNN50
nance of sympathetic modulaFrequency domain: LF, HF,
tion (increased SDANN,
and LF/HF ratio
SDNN, RMSSD, and LF) and
Non-linear indices: None
decreased parasympathetic
Time of analysis: 24 h
modulation (decreased HF).
The decreased HRV is present
even before heart failure, and
its decrease is negatively associated with myocardial fibrosis.
There was no difference
between DMD patients with or
without a beta blocker
Linear indices:
HRV parameters were signifiTime domain: SDNN, RMSSD,
cantly altered in DMD patients
and pNN50
compared to controls. SDNN,
Frequency domain: LF (ms2
RMSSD, NN50, pNN50, and
total power were reduced in
and nu), HF (ms2 and nu),
DMD patients suggesting
and LF/HF ratio
overall reduction in autonomic
Non-linear indices: None
regulation of the heart. HF
Time of analysis: 5 min
power and HF.nu were reduced,
whereas LF.nu and LF/HF
ratio were increased, further
suggesting diminished vagal
influence
Electrocardiogram
Main outcomes
Pediatric Cardiology (2018) 39:869–883
Table 1 Articles included on the eligibility criteria
873
13
874
13
Table 1 (continued)
Nature
Sample
Instrument
HRV Indices
4. Inoue et al. [7]
Prospective cohort study
57 males with DMD;
No controls
Age
8–27 (15.3 ± 4.5) years old
Electrocardiogram
Linear indices:
Time domain: SDNN, pNN50
Frequency domain: HF (ms2),
and LF/HF ratio
Non-linear indices: None
Time of analysis: 24 h
5. Mochizuki et al. [5]
Cross-sectional study
73 boys with DMD;
No controls
Age
6–44 years old
Electrocardiogram
6. Lanza et al. [16]
Cross-sectional case control
study
60 males with DMD;
28 healthy controls
Age
DMD—16.8 ± 4.8 years old
Controls—15.2 ± 4.6 years old
Holter
Main outcomes
In DMD, HRV (especially
SDNN) was frequently
abnormal, although conventional clinical examinations
of cardiac function (BNP and
–FS) were normal. HF power
and pNN50 decreased with
age. Both parameters decreased
sharply after 15 years of age
and were abnormal in almost
all cases after 20 years of
age. LF/HF and were abnormal since childhood. After
approximately 20 years of age,
HF, pNN50, and SDNN were
severely decreased in most
DMD patients, and mean heart
rate during night provided the
highest sensitivity and specificity for predicting decreases in
SDNN
Decreased CVrr in DMD
Linear indices:
patients suggest sympathetic
Time domain: CVrr (coefficient
dominance. Inverse correlation
of variation of RR interval)
between CVrr and respiratory
Frequency domain: None
rate suggest hypercapnia may
Non-linear indices: None
drive decreases in CVrr
Time of analysis: 3 min
The authors proposed that
abnormally low CVrr (< 3%)
indicates respiratory insufficiency in patients with DMD
Linear indices:
Among multiple HRV indices
Time domain: SDNN, SDNNi,
only LF and LF/HF ratio
SDANN, rMSSD, and pNN50 correlated with age. A modFrequency domain: Total
est correlation between left
amplitude, VLF, LF (ms2), HF ventricular ejection fraction
and HF and LF/HF, as well
(ms2), and LF/HF ratio
as between respiratory forced
Non-linear indices: None
vital capacity and SDNN,
Time of analysis: 24 h
RMSSD, pNN50, HF, and LF/
HF, indicating that sympathetic
dominance increases with the
progression of cardiac and
respiratory dysfunction
Pediatric Cardiology (2018) 39:869–883
Reference
Reference
Nature
Sample
Instrument
Electrocardiogram
7. Yotsukura et al. [18] Prospective case control cohort 17 males with DMD;
study
27 healthy controls
Age
DMD group in the beginning of
the study: 7–18 (11.8 ± 3.1)
years old
DMD group in the end of the
study: 16–27 (20.8 ± 3.1)
years old
Control A (age matched with
DMD at the beginning):
11.8 ± 3.1 years old
Control B (age matched
with DMD in the end):
20.6 ± 1.4 years old
Holter
55 boys with DMD;
8. Yotsukura et al. [17] Cross-sectional case control
study
20 healthy controls
Age
DMD group: 10–24 (18 ± 4)
years old
Controls: 9–23 (16 ± 14)
HRV Indices
Main outcomes
Linear indices:
DMD patients had increasing
Time domain: SDNN, SDNNi,
sympathetic dominance as their
SDANN, rMSSD, and pNN50 disease progressed. The authors
Frequency domain: LF (ms2),
suggest that autonomic imbalance begins at an early stage
HF (ms2), and LF/HF ratio
of DMD, leading to cardiopulNon-linear indices: None
monary dysfunction. However,
Time of analysis: 24 h
with progressive inactivity,
deconditioning, and/or increasing age, this cardiopulmonary
dysfunction can worsen even
more, contributing further to
autonomic imbalance
Linear indices:
Time domain: Mean RR, CVrr,
SDNN, and pNN50
Frequency domain: LF (ms2),
HF (ms2), and LF/HF ratio
Non-linear indices: None
Time of analysis: 24 h
Pediatric Cardiology (2018) 39:869–883
Table 1 (continued)
The autonomic abnormalities in
DMD corresponded with an
increase in relative sympathetic
influence and a decrease in
parasympathetic modulation,
as indicated by decreases in
the following specific HRV
parameters: Mean RR, SDNN,
RMSSD, pNN50 and HF,
and an increase in LF/HF.
Circadian rhythm appeared
disrupted, as LF/HF was higher
at night than day for DMD
patients, whereas the inverse
was true for control patients.
Autonomic abnormalities
occurred early in the disease
process, increasing with the
disease severity. Thus, HRV
and circadian rhythm seemed
to be related and both were
useful in assessing autonomic
imbalance in DMD
875
13
DMD Duchenne muscular dystrophy, HRV heart rate variability, SDNN standard deviation of all RR intervals, SDNNi (index) mean of standard deviations of all RR intervals for all 5-min segments, SDANN standard deviation of mean RR interval of all 5-min segments, RMSSD square root of mean squared differences of successive RR intervals, pNN50 percentage of differences
between adjacent RR intervals > 50 ms, LF low frequency, HF high frequency, LF/HF low frequency/high frequency ratio, %RR50 percentage of adjacent normal RR intervals that were > 50 ms
different for the entire 24-h recording, CVrr coefficient of variation of RR interval, ACE inhibitor, angiotensin-converting-enzyme
876
Pediatric Cardiology (2018) 39:869–883
measurement [19, 22]. In the study conducted by Inoue et al.
[7], patients did not receive medication during the duration of
the study. Thomas et al. [20] compared DMD patients with
and without beta blockers and found no differences between
the two groups.
Meta‑analyses—Synthesis of Results
Meta-analyses of experimental outcomes, including the calculation of weighted mean effect sizes (Cohen’s d), 95% CI, I2%,
heterogeneity, and p values from a random effects model, were
assessed with the metafor package in R (http://CRAN.Rproj
ect.org/package=metafor) [23]. All error bars in random forest plots are 95% CI; random forest plots were generated with
metafor and custom R scripts. The indices SDNN, RMSSD,
and pNN50 were chosen for being the indices present (with
mean and standard deviation values) in the four articles with
control group evaluation.
The results of standardized mean difference (SMD) and
95% CI for each comparison are shown in Table 2.
HRV Analysis
Modulation of heart rate depends on the integration of sympathetic and parasympathetic input, and this is best reflected
by short-term oscillations in beat intervals [24]. HRV analyses
may be performed by several methods, including time domain,
frequency domain, and non-linear analysis [10, 12, 13, 25].
However, the studies analyzed by this review only used linear
indices: time and frequency domains.
Time Domain
The most common time domain indices were: RMSSD (ms),
pNN50 (%), SDNN (ms), SDANN, and SDNNi.
RMSSD is the square root of the mean of squared differences between successive beat intervals and calculated according to the following equation [26]:
�
∑N−1
(RRi − RRi+1 )2
i=1
,
RMSSD =
N−1
Table 2 Outcome measures
in the meta-analysis of
comparisons between all
Duchenne muscular dystrophy
patients and healthy control
subjects in HRV measures
where RRi is any individual RR interval and N is the number
of RR intervals in the series of selected data. Along with
pNN50, defined as the percentage of differences between
RR intervals with an absolute value greater than 50 ms,
RMSSD positively correlates with relative parasympathetic
dominance over cardiac rhythm. SDNN, which represents
sympathetic and parasympathetic activity, is the standard
deviation of the mean for all normal RR intervals expressed
in milliseconds. The SDANN (ms) is the standard deviation
of the means of normal-to-normal heart periods obtained
from all 5-min periods throughout the whole data series,
and the SDNN index (ms) is the average of the standard
deviations of all normal-to-normal intervals calculated from
all 5-min periods of a 24-h recording period [27–29]. A
study by Mochizuki et al. [5] also reported the index CVrr,
which is the coefficient of variation of RR interval (SDNN/
MeanRR*100), which is considered to reflect overall HRV
(i.e., sympathetic and parasympathetic activity) [30].
Frequency Domain
The most common frequency domain indices were low
frequency (LF), high frequency (HF), very low frequency
(VLF), and LF/HF ratio (low frequency/high frequency
ratio).
Power spectral analysis describes the periodic oscillations
of the heart rate decomposed at different frequencies and
amplitudes by Fast Fourier Transformation [31], with regard
to oscillations in cardiovascular parameters. The HF component (0.15–0.4 Hz) is considered to indicate vagal influence
over the heart, while the LF component (0.04–0.15 Hz) is
believed to reflect both sympathetic and vagal influence and
has been correlated with baroreflex sensitivity [25, 28]. The
etiology of changes in VLF (< 0.003–0.004 Hz) remains
unclear, but VLF has been shown to predict adverse cardiac
events in heart failure patients [20]. The LF/HF ratio is an
index for overall sympatho-vagal balance. A ratio greater
than one is an estimate of sympathetic dominance, while a
LF/HF ratio less than one is associated with parasympathetic
dominance [22, 31, 32].
Outcome
SMD (95% CI);
p value
Heterogeneity
I2 %
Number of
patients
Number
of studies
SDNN
RMSSD
pNN50
−1.70 (− 2.76, − 0.65); p = 0.0015
− 0.97 (− 1.59, − 0.36); p = 0.0018
− 1.03 (− 1.55, − 0.51); p = 0.0001
< 0.0001
0.0006
0.0024
93.1
82.6
75.8
384
384
384
4
4
4
SDNN standard deviation of all RR intervals, RMSSD square root of mean squared differences of successive RR intervals, pNN50 percentage of differences between adjacent RR intervals > 50 ms
13
Pediatric Cardiology (2018) 39:869–883
Time Domain Analysis (SDNN, RMSSD, pNN50)
A total of four studies provided analyzable data for time
domain analysis of HRV (SDNN, RMSSD, and pNN50)
with 384 patients. A statistical difference was observed
in SDNN, RMSSD, and pNN50 (Figs. 3, 4 and 5, respectively). During analysis, heterogeneity (p < 0.01) of the
combined data was found for all time domain parameters.
One study, in which only the mean values were reported,
was not included in the analysis. Four studies did not
include a control group, and therefore, were not included
in the analysis.
For SDNN, DMD patients are estimated to present with
an SDNN that is on average about one and half standard deviations below the SDNN of controls (µ^ = − 1.70
with 95% CI − 2.76 to − 0.65), but there is a considerable
amount of heterogeneity in the findings (as indicated by
the large estimate of τ2 = 1.05, the large Ι2 = 93.1% value,
and the significant Q(df = 3) = 55.1438, p < 0.0001).
Meta-analysis of SDNN effect sizes on DMD and controls is shown as a forest plot of standardized effect sizes
(Cohen’s d). Error bars indicate the 95% confidence intervals of d. The weighted average mean effect size of all
studies is represented by the central vertices of a black
diamond; the outer vertices indicate the 95% confidence
intervals. Control and DMD samples sizes (n), mean and
Fig. 3 Meta-analysis comparing Duchenne muscular dystrophy
(DMD) to “Control” subjects for studies, which presented absolute
values of SDNN (mean ± SD in ms) using “Standard mean differences” (SMD) ± 95% confidence intervals (CI). Effect sizes and confidence intervals are based on standardized mean differences in dis-
877
standard deviations SDNN (SD) of the studies are given.
The I2 of 93.1% indicates a high level of heterogeneity.
For RMSSD, similar to SDNN above, DMD patients
are estimated to present with a RMSSD that is on average
about one standard deviation below the RMSSD of controls (µ^ = − 0.97 with 95% CI − 1.59 to − 0.36), but there
is a considerable amount of heterogeneity in the findings
(as indicated by the large estimate of τ2 = 0.31, the large
Ι2 = 82.6% value, and the significant Q(df = 3) = 17.4120,
p = 0.0006).
Considering pNN50, similar to SDNN and RMSDD
above, DMD patients are estimated to present with a pNN50
that is on average about one of the standard deviations below
the pNN50 of controls (µ^ = − 1.03 with 95% CI − 1.55 to
− 0.51), but there is a considerable amount of heterogeneity in the findings (as indicated by the large estimate of
τ2 = 0.21, the large Ι2 = 75.8% value, and the significant
Q(df = 3) = 14.3906, p = 0.0024).
Discussion
The studies that met our meta-analysis criteria showed that,
even with heterogeneity in the results, the indices evaluated
(SDNN, RMSSD, and pNN50) were very significantly different in DMD patients when compared to controls. It is well
crimination (d’). The polygon at the bottom of the panel represents
the summary effect calculated using a random effects model. The
square marker size indicates weight within the model. Weights are
from the random effects analysis
13
878
Pediatric Cardiology (2018) 39:869–883
Fig. 4 Meta-analysis comparing Duchenne muscular dystrophy
(DMD) to “Control” subjects for studies which presented absolute
values of RMSSD (mean ± SD in ms) using “Standard mean differences” (SMD) ± 95% confidence intervals (CI). Effect sizes and con-
fidence intervals are based on standardized mean differences in discrimination (d’). The polygon at the bottom of panel represents the
summary effect calculated using a random effects model. The square
marker size indicates weight within the model
Fig. 5 Meta-analysis comparing Duchenne muscular dystrophy
(DMD) to “Control” subjects for studies which presented absolute
values of RMSSD (mean ± SD in ms) using “Standard mean differences” (SMD) ± 95% confidence intervals (CI). Effect sizes and con-
fidence intervals are based on standardized mean differences in discrimination (d’). The polygon at the bottom of panel represents the
summary effect calculated using a random effects model. The square
marker size indicates weight within the model
known that RMSSD and pNN50 are measurements that predominantly reflect parasympathetic modulation of the heart,
and all studies found pNN50 to be lower in DMD patients
than in controls suggesting sympathetic dominance in DMD.
SDNN reflects overall variability and when lower is
described as a strong predictor of death, stroke, and myocardial infarction [25]. All studies analyzed in this meta-analysis showed lower SDNN in DMD patients when compared to
13
Pediatric Cardiology (2018) 39:869–883
controls. We can conclude—in agreement with Inoue et al.
[7]—that HRV impairment may be considered as a preclinical marker of cardiovascular dysfunction in DMD patients.
Given that heart failure has recently been identified as
responsible for most of the deaths among DMD patients,
it is essential to obtain an early diagnosis in order to prolong life expectancy and quality of life for these patients.
As a result, we found it necessary to conduct a systematic
review to characterize HRV in males with DMD, and gain a
better understanding of autonomic modulation and perhaps
prognosis.
All studies included in the review evaluated just linear
indices, as we can see in the time domains (rMSSD, SDNN,
SDNNi, SDANN, and pNN50) and frequency domains
(LF, HF, and LF/HF ratio). SDNN and HF were the indices
that were abnormal in the most papers reviewed [4, 7, 11,
19–22], suggesting restricted tone of the parasympathetic
system for people with DMD and reduced overall heart rate
variability.
Chu et al. [33] conducted a study with mice also demonstrating a preeminence of sympathetic modulation and
suggesting that the etiology of cardiac muscle disease might
be caused by autonomic dysfunction. However, none of the
papers conducted non-linear analysis, which can better
express the complex nature of heart rate variability; linear
methods can not detect this as well [12].
Furthermore, the studies analyzed in this review showed
restricted tone of the parasympathetic system and/or predominance of sympathetic tone in children as young as
5 years of age (Table 1).
HRV × Age—Disease Stage
Thomas et al. [20] showed decreased HRV in DMD patients
as young as 5 years old. Yotsukura et al. [19] showed
decreased HRV when compared to controls, a difference
that increased with disease stage. Yotsukura et al. [22]
showed that LF and HF power decreased and LF/HF ratio
increased in advanced stages of DMD. All the time domain
parameters were lower in DMD patients when compared to
controls. These three studies demonstrate that autonomic
impairment is present in patients with DMD in an early age/
disease stage, but heart failure and dyspnea (present in a late
stage of the disease) seems to increase the sympathetic activity. Inoue et al. [7] also found that HF power and pNN50
decreased with age. Mochizuki et al. [5] found a correlation with HR and age, but no correlation with CVrr(%).
Lanza et al. [11] showed that HF decreased and LF/HF ratio
increased with age.
Taken together, we can speculate that disregarding the
presence of an autonomic imbalance at an early stage, age
and disease severity highly contribute to the worsening of
this imbalance.
879
HRV and Heart Failure Induced by Myocardial
Fibrosis
The study by Thomas et al. [20] demonstrated decreased
HRV in DMD patients prior to the onset of heart failure, and
found an inverse correlation between HRV (SDANN) and
myocardial fibrosis. The authors demonstrated that by using
the association between positive Late Gadolinium Enhancement (LGE) on cMR (cardiac Magnetic Resonance) and
SDANN, age, and maximal HR, the persistent activation of
the sympathetic nervous system seems to be a driving force
in the pathologic formation of myocardial fibrosis. In other
words, HRV can be associated with heart failure and it is a
useful tool to predict cardiac dysfunction that can lead to
early death, thus making it possible to predict prognosis and
consider treatment, aiming to increase the life expectancy of
patients with DMD, as occurred after treatment for respiratory insufficiency.
In the study by Inoue et al. [7], HRV data were compared
with serum levels of BNP and the SF of the left ventricle on
echocardiography. Although the BNP and SF were normal,
HRV parameters were frequently abnormal, which shows
that the findings on the HRV indices preceded alterations
in global ventricular function (SF) and neurohumoral factor
(BNP) serum levels.
Posner et al. [34] investigated quantitative muscle testing
(QMT) and the cardiac function (FS) in DMD patients and
they found a significant relationship between skeletal muscle
and cardiac function in DMD patients. The authors suggest
that the cardiac function should be monitored, even when
the primary outcome measures are not cardiac in nature. In
order to explain the physiology of this impairment on cardiac function, in a recent study, Barbin et al. [35] examined
diaphragm degeneration and cardiomyopathy in dystrophindeficient mdx mice, comparing exercised (swimming, to
accelerate the diaphragm degeneration) and sedentary. They
found fibrosis of the diaphragm and right and left ventricle,
as well as increased density of inflammatory cells/degenerating cardiomyocytes in both the right and left ventricles
with right ventricle predominance. There was also increased
wall thickness of the pulmonary trunk and right ventricle
which suggest pulmonary hypertension in those animals.
All those parameters were increased in mice with exercise.
The authors suggested that diaphragm degeneration may be
the main contributor to right ventricle dystrophic pathology.
The increase in sympathetic tone may be a compensatory response to cardiac dystrophy that further drives DMD
patients towards heart failure (HF); it may be the primary
culprit of DMD-associated HF, or it may be a compensatory
mechanism that is mostly just secondary and has little effect
on progression of DMD patients towards failure. Because
these patients have fibrosis, it is certainly possible that the
HF is at least partly induced by increased adrenergic drive.
13
880
HRV and Catecholamines
An important function of the heart is to adapt to increased
needs for tissue perfusion under normal physiological
conditions. This adaptation of the heart is achieved by the
activation of the sympathoadrenergic system (SAS) [36].
Thus, increased sympathetic activity stimulates the adrenal
medulla to produce and secrete increased amounts of adrenaline and noradrenaline, as seen in the study of Dalmaz et al.
[37] in which the authors found increased amounts of urinary catecholamine, mainly in a late stage of DMD, so this
increase in catecholamines seems to happen secondary to
the disease and probably as a compensatory way to improve
the decreased HRV.
In addition, Li et al. [36] stated that the SAS can persistently be activated when the heart is under stress, leading
to a reduced beta-adrenergic response and it also may contribute to the increase in catecholamines. In their study with
Mdx mice, they found that the hearts of Mdx mice partially
lose beta-adrenergic responses from a young age because of
myocyte loss, reduced potential for increasing myocyte contraction in mdx myocytes with enhanced myocyte contractile
function via molecular remodeling, and cellular desensitization in response to the hyperactive SAS.
HRV and Beta Blockers
With a timely prognosis, the question remains if drugs for
regulating cardiac rate or cardiac protection improve HRV
to some degree. In this regard, only Thomas et al. [20] found
no treatment-related differences in HRV among those taking
beta blockers (despite a clear effect on heart rate), angiotensin-converting enzyme inhibitors, or angiotensin II receptor blockers. Mochizuki et al. [5] also found no correlation
between CVrr and beta blocker use in DMD patients. That
is, despite reducing heart rate, beta blockers do not seem
to improve HRV. It is possible that the lack of difference
between HRV parameters in DMD patients with and without
beta blockers can be due to DMD patients who were given
beta blockers likely received it due to signs of heart failure.
As such, the beta blockers may have increased their HRV
to the extent that their HRV improved to be comparable to
DMD patients who did not need a beta blocker.
These findings contradict what is known about beta
blocker therapy: after myocardial infarction [38] and in
heart failure additional beta blocker therapy has been
shown to upregulate the fractal control of HRV in patients
with advanced congestive heart failure [39]. Similarly, de
Hartog et al. [40] found that ambient particulate matter
air pollution decreased HRV in coronary artery disease
patients, but beta blocker use partly inhibited this effect.
They found that for people without beta blockers HRV
was decreased compared to the people with beta blockers.
13
Pediatric Cardiology (2018) 39:869–883
Perhaps beta blocker therapy does not work the same (with
regard to the ANS) in people with DMD as it does in other
populations. More studies are needed to better understand
the underlying physiology and pharmacology.
HRV and Respiratory Failure
The etiology of HRV decreases in DMD patients remains
only speculative. Mochizuki et al. [5] proposed that abnormally low CVrr (coefficient of variation of RR interval < 3%) results from respiratory insufficiency-induced
hypercapnia in patients with DMD [20]. Lanza et al. [11]
found a weak but significant correlation between autonomic impairment and degree of respiratory failure. Potentially corroborating these findings, Reis et al. [41] showed
that cardiac autonomic control of heart rate was associated
with inspiratory muscle weakness in coronary heart failure. Nevertheless, any causality between respiratory and
autonomic dysfunction remains only putative, and the two
may instead derive from a common unidentified mediator.
Taken together, these data suggest that impaired cardioautonomic regulation in patients with DMD likely results
from multiple components, potentially including not only
respiratory and mechanical cardiac dysfunction, but other
factors such as structural and functional abnormalities
of the sinoatrial node, neurohumoral, changes caused by
inactivity of patients, and abnormal mechanoreceptor- and
metaboreceptor-mediated reflexes originating from the diseased skeletal muscles [11, 22].
HRV Analysis Protocol
According to time of analysis, the majority of the studies conducted HRV analyses using Electrocardiogram or
Holter for 24 h. Dhargave et al. [4] and Mochizuki et al.
[5] used 5- and 3-min analyses, respectively, but the results
were consistent with previous studies which used longer
(24-h) recording. Thus, it seems that short-term HRV analysis is a good tool to investigate for evidence of cardiac
autonomic dysfunction in children with DMD [4]. Shortterm analysis has been used recently by several researchers [13, 14, 42] who used a heart rate monitor for the RR
interval recording and consequently HRV analysis. This
method proved to be reliable and does not require patient
admission to a hospital for analysis (i.e., can be done on
an outpatient basis).
With 24-h analysis, Lanza et al. [11] and Inoue et al. [7]
affirm that mean heart rate during night provided the highest sensitivity and specificity for predicting abnormalities of
SDNN. Moreover, high frequency HRV was disproportionately diminished during the night.
Pediatric Cardiology (2018) 39:869–883
HRV as a Predictor of Death
Yotsukura et al. [19] showed that Mean RR, SDNN, and
SDNNi were significantly decreased in DMD patients within
6 months prior to death. These indices should be analyzed
carefully through long-term HRV measurement.
Future studies should evaluate the influence of beta blockers, angiotensin-converting enzyme inhibitors (ACE), and
steroid use on improving cardiac status of DMD patients [4].
It is important to evaluate HRV in people with DMD using
non-linear indices to predict and correlate heart failure and/
or muscle function, since these indices better express the
complex nature of HRV [12]. Without treatment, DMD tends
to culminate with fatal cardiorespiratory compromise in the
early- to mid-teens [43]. The aforementioned studies suggest
that HRV provides a useful and practical tool for predicting
DMD exacerbation and may help reveal effective therapies
by elucidating mechanisms of DMD-induced mortality.
Conclusion
A relative sympathetic dominance was evident in DMD
patients from an early stage of disease, and appeared to
become more prominent with an increase in disease severity and age. Although a few studies have observed correlations between reduced HRV and pulmonary function, several
more have demonstrated worsening cardiac dysfunction with
age and disease severity. Thus, since a primary role for autonomic imbalance in DMD is not well supported, continued
study is needed to fully define this possibility. Also medication to counteract the cardiac damage of this disease remains
unidentified.
Caution is needed in interpreting these results as the ChiSquare tests demonstrated large statistical heterogeneity.
However, there were differences in SDNN, RMSSD, and
pNN50 between DMD and controls in all studies. Moreover,
HRV can be used as a preclinical marker of cardiovascular
complications in DMD patients, thereby enhancing diagnosis. Lastly, HRV assessment seemed to be a predictor of
sudden death through evaluation of the Mean RR, SDNN,
and SDNNi indices.
Acknowledgements The authors thank CNPq (National Council for Scientific and Technological Development, process number
142280/2015-1), CAPES (Coordination for the Improvement of Higher
Education Personnel, Process No. 99999.014604/2013-02) for support
of this work.
Author Contributions TDS, TM, FRO, and TBC participated in the
acquisition of data and TDS, AC, CBMM, CA, LCA, LCMV, CFF,
JG, and CF participated in the revision of the manuscript. TDS, TM,
CBMM, CF determined the design, interpreted the data and all authors
881
helped on draft the manuscript. All authors read and gave final approval
for the version submitted for publication.
Data Availability The data from metanalysis of the current study are
available upon request.
Compliance with Ethical Standards
Conflict of interest All authors report no conflict of interest.
Informed Consent The current study does not contain any data from
individual persons.
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Affiliations
Talita Dias da Silva1,2 · Thais Massetti3 · Tânia Brusque Crocetta4 · Carlos Bandeira de Mello Monteiro3
Alex Carll2 · Luiz Carlos Marques Vanderlei5 · Carlie Arbaugh6 · Fernando Rocha Oliveira7 ·
Luiz Carlos de Abreu7 · Celso Ferreira Filho8 · John Godleski2 · Celso Ferreira8
·
1
Paulista School of Medicine, Federal University of São
Paulo, Rua Napoleão de Barros, 715, Vila Clementino,
São Paulo, SP CEP: 04024-003, Brazil
2
Department of Environmental Health, Harvard TH Chan
School of Public Health, 677 Huntington Ave, Boston,
MA 02115, USA
3
Graduate Program in Rehabilitation Sciences, Faculty
of Medicine, University of São Paulo, Rua Cipotânea, 51,
São Paulo, SP 05360-000, Brazil
Luiz Carlos Marques Vanderlei
lcmvanderlei@fct.unesp.br
4
Faculty of Medicine of ABC, Avenida Príncipe de Gales,
821, Santo André, SP 09060-950, Brazil
Carlie Arbaugh
cja62@cornell.edu
5
Sao Paulo State University - UNESP, Rua Roberto Símonsen,
305, Presidente Prudente, SP 19060-900, Brazil
Fernando Rocha Oliveira
oliveira.fernando.rocha@hotmail.com
6
Stanford University School of Medicine, 450 Serra Mall,
Stanford, CA 94305, USA
Luiz Carlos de Abreu
luizcarlos@usp.br
7
School of Public Health, University of São Paulo, Avenida
Dr. Arnaldo, 715, São Paulo, SP 01246-904, Brazil
Celso Ferreira Filho
dr.celso@uol.com.br
8
Graduate Program in Medicine (Cardiology), Paulista School
of Medicine, Federal University of São Paulo, Rua Napoleão
de Barros, 715, São Paulo, SP 04024-003, Brazil
Thais Massetti
thaismassetti@gmail.com
Tânia Brusque Crocetta
taniabrusque@gmail.com
Carlos Bandeira de Mello Monteiro
carlosmonteiro@usp.br
Alex Carll
alex.carll@louisville.edu
John Godleski
jgodlesk@hsph.harvard.edu
Celso Ferreira
doutorcelsoferreira@gmail.com
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