Hypertrophic cardiomyopathy (HCM) is a commonly encountered inherited
heart disease with an estimated prevalence of 1:200 to
1:5001. Approximately 30-40% of those patients
diagnosed with HCM will experience adverse events (sudden cardiac death
[SCD], heart failure, atrial fibrillation). Risk stratification for
arrhythmias in HCM has been typically based upon five traditional
noninvasive pillars (syncope, left ventricular hypertrophy
>30mm, non-sustained VT, family history of sudden cardiac
death, and abnormal blood pressure response to exercise). There has been
some evolution in our understanding of risk, with the demotion of some
to risk modifiers and identification of new risk markers/predictive
scoring strategies (LGE on CMR, apical aneurysms, EF <50%).
In HCM patients, comorbidities (obesity, hypertension, obstructive sleep
apnea) have been identified as significant modifiers of disease
penetrance, severity, and clinical course, particularly in relation to
symptoms and heart failure 2-4. The relationship of
comorbidities to arrhythmias is less explored, but population-level data
in non-HCM patients suggests that comorbidities can influence arrhythmia
risk 5,6. Therefore, in HCM patients, if there were a
positive association, this would provide an additional tool to refine
arrhythmia risk.
In this issue of the Journal of Cardiovascular Electrophysiology ,
Sridharan et al.7 explore and attempt to answer this
important question - what is the association of comorbidities in HCM
patients with arrhythmia risk? This paper studies a large cohort of 2269
patients of >18 years evaluated between 2004 and 2018. The
mean age was 54 ± 15 years, with 1392 (61%) male, and a follow-up
average of 4.0 ± 3.4 years. 1702 (75%) had ≥1 medical comorbidity, and
50% of patients had ≥2 comorbidities, most commonly obesity (43%),
hyperlipidemia (39%), and hypertension (27%). 198 (11%) HCM patients
developed new-onset AF over follow-up at a rate of 2.6% per year. On
univariate analysis, obesity was associated with a 1.7-fold increase in
risk for AF development compared to patients with normal BMI (95% CI
1.0, 2.7, p=0.03). In addition, 12% of obese patients developed AF
(rate of 3.3%/year) compared to just 7% with normal BMI (rate of
1.6%/year; p=0.006). No other comorbidities were significant by
univariate analysis. However, importantly on multivariate analysis,
obesity did not show an association with AF (OR 1.3 [95% CI 0.95,
1.79, p=0.10). Concerning SCD, 72 (3%) of patients experienced a SCD
event during the following up period (0.8%/year). There was no
association between any comorbidities and the risk of SCD. While this is
a large cohort study, the major limitation that one must consider is
that past medical history was assessed at the initial clinical
evaluation. It, therefore, does not reflect the development of new
comorbidities over the follow-up period (which may have a different
impact on arrhythmia risk). Additionally, a major comorbidity,
obstructive sleep apnea, was not examined, which has important
pathogenesis links to arrhythmias. Lastly, the number of patients with
adjudicated SCD was low and may be underpowered to detect associations
between comorbidities and ventricular arrhythmias.
The authors should be congratulated for completing this important study
which demonstrates that in this cohort of HCM patients, comorbidities
did not play a significant role in risk of arrhythmias (atrial or
ventricular). This adds and confirms previous publications that failed
to establish a strong association between obesity and adverse arrhythmic
outcomes3,8. The data presented in this paper is
important and surprising. The lack of association with arrhythmic risk
given the plethora of data on patient comorbidities in non-HCM cohorts,
and especially considering that obesity in HCM can lead to a more severe
phenotype and worse disease progression9 is not
entirely understood and requires further exploration.
One potential explanation is the application of body mass index (BMI) to
define obesity. Although BMI is largely ingrained as the most
conventional and convenient method to define obesity, it can be an
imprecise measurement as it defines
overall adiposity and doesn’t consider the different elements of
adiposity distribution such as abdominal vs. epicardial adipose tissue
(EAT). EAT is an evolving area of interest given its proximity to
cardiac tissue, and its presence and size have been associated with
cardiac arrhythmias, particularly atrial
fibrillation10. EAT is proposed to play a role in
arrhythmogenesis by altering the electrical and structural properties of
the cardiac myocardium11. Specifically, direct
infiltration and promotion of fibrosis can set up the correct
environment for reentry. Further, paracrine effects by adipokines can
lead to ion channel modulation and alteration of cell-cell electrical
coupling. Our knowledge of the role of EAT in HCM is limited. Muhib et
al.12 in a cohort of 62 patients, showed an increased
incidence of AF related to an increase in EAT, even when adjusted for
baseline characteristics. Further examination of this in larger cohorts
may be insightful.
Overall, the authors provide a thought-provoking paper that adds
critical data to the HCM literature. As we broaden our understanding of
the elements and measurement of obesity and other comorbidities, perhaps
it will become an important risk stratification tool. Until then, the
role of comorbidities and its impact on AF or SCD in this subset of
patients with HCM remains unclear and further research is warranted.
References:
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Diagnosis and Treatment of Patients With Hypertrophic Cardiomyopathy: A
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