Physical Activity, Inactivity and Sleep in Individuals with Hypertrophic Cardiomyopathy

Key words

myopathy - cardiology - physical activity - sleep

Introduction

Hypertrophic cardiomyopathy (HCM) is a global and common genetic heart disease with a prevalence estimated at 1 in 200 in the general population [1] [2] [3]. HCM is clinically characterized by left ventricular hypertrophy without any secondary causes [1]. There is great variability in disease severity for HCM with many able to fulfill a normal life expectancy without increased risk of premature death whereas others experience significant disease burden after diagnosis [1] [4]. Similar to the general population guidelines for physical activity [5], it is recommended by the American Heart Association/American College of Cardiology 2020 [1] that most individuals with HCM should participate in mild to moderate-intensity exercise. Mild and moderate-intensity exercise programs in individuals with HCM are reported to be safe and have resulted in both improved functional capacity and quality of life [6].

Regular participation in physical activity regardless of age, sex and race has many cardioprotective effects [7]. However, over 50% of individuals with HCM are not meeting the physical activity guidelines [5] [8]. Consequently, overweight and obesity are highly prevalent (70%) in individuals with HCM [9]. Physical activity presents an important cornerstone in the management and care of individuals with HCM. This study firstly evaluated the physical activity, inactivity and sleep patterns of individuals with HCM compared to age and sex-matched healthy controls, using wrist-worn triaxial accelerometry, and secondly assessed the associations between acceleration categories and exercise capacity, clinical biomarkers and quality of life in individuals with HCM only.

Materials and Methods

Participants

Twenty-one individuals with HCM (52±15 years old, body mass index (BMI): 29.98±6.72 kg/m²) were recruited from a tertiary center (Newcastle upon Tyne Hospitals NHS Foundation Trust, UK) and were part of the SILICOFCM study (NCT03832660) with the inclusion and exclusion criteria described elsewhere [10]. Age and sex-matched healthy controls (n=21, 51±14 years old, BMI: 24.97±3.65 kg/m²) were recruited through advertisements at Newcastle University, UK, and participants self-reported no history of chronic diseases and were not prescribed any long-term medication. The healthy controls were representative of a healthy population, and did not report any cardiovascular conditions; they completed the same length of monitoring (7 days) and completed the monitoring in a time period similar to the clinical population [11]. Demographic characteristics (sex and age) of the individuals with HCM were recorded and then individually matched to the healthy control individuals’ age and sex demographic characteristics. The SILICOFCM study protocol was approved by Research Ethics Committee of the National Health Service, North-East England – Tyne and Wear South (18/NE/0318) and the healthy control study was approved by Newcastle University Ethics Committee (2901/2017). All participants provided written informed consent. All clinical investigations were conducted according to the principles expressed in the Declaration of Helsinki.

Study protocol and measurements

Participant age (years) was recorded as a decimal value. Standing height (to the nearest 0.1 cm) and body weight (to the nearest 0.1 kg) were measured using the SECA stadiometer and scales (North East Weighing & Calibration Ltd.). Body mass index (BMI) was calculated using the equation: BMI=body mass (kg)÷stature²(m²). Participants with HCM visited the clinical research facility at the Royal Victoria Infirmary, Newcastle upon Tyne, as part of the SILICOFCM study [10]. Transthoracic echocardiography was used to measure cardiac function and dimensions, which included: left ventricular outflow tract maximum pressure (mmHg), interventricular septum diameter (mm), posterior wall diameter (mm), left atrial diameter (mm), left atrial volume index (ml/m²) and E/E’ ratio. Peak oxygen consumption (ml/kg/min) was calculated to determine exercise capacity and was measured on a cycle ergometer. NTproBNP (ng/L) was recorded via venous sample. The Minnesota Living with Heart Failure (MLHF) questionnaire was recorded to determine disease severity.

All participants completed 7-day monitoring using wrist-worn triaxial accelerometers (GENEActiv, ActivInsights Ltd, UK). Accelerometer data was processed in R using R-package GGIR (Version 2.7.0) [12] [13] [14]. Signals were inspected and corrected for calibration error [15] and only days with at least 16 hours of valid data were retained for further analysis. Participants were required to have worn the accelerometer for a minimum wear time of at least three days (including one weekend day) [16]. The average magnitude of wrist acceleration per 5-second epoch was calculated with metric ENMO as previously described (1 mg=0.001 x gravitational acceleration) [12]. Monitor non-wear was detected as described previously [12] and replaced by the average accelerometer data on similar time points on different days of the measurement [17] [18]. The following acceleration categories were calculated: Inactivity (<40 mg), light physical activity (40–100 mg) and moderate-vigorous physical activity (MVPA) (>100 mg) [19] [20]. Time spent in 5 to 10-minute (MVPA-5 min) and 10-minute (MVPA-10 min) bouts of MVPA, as well as time spent in 30-minute inactivity (inactivity-30min) bouts, was calculated. Estimated total sleep duration (minutes) and sleep efficiency (%) were calculated after sleep onset with the analysis described elsewhere [21].

Data analysis

Data were analyzed using R (version 4.1) [14] and SPSS (version 27, SPSS, Inc., Chicago, IL, USA). The level of significance was set at p<0.05. Data are described as median (interquartile range) unless otherwise stated. Prior to statistical analysis, data were screened for normality and outliers by Shapiro-Wilks and boxplots. Although the groups were age and sex-matched, we were unable to match by BMI, which is important given that sustained bouts of physical activity are associated with lower levels of obesity as measured by BMI [22]. Significant differences in BMI were found between individuals with HCM and healthy controls (p<0.01). To ensure our findings accounted for these differences, we adjusted our analysis for BMI with differences in acceleration categories between groups being assessed by analysis of covariance (ANCOVA). For individuals with HCM only, relationships between acceleration categories and clinical measures (left atrial diameter and volume, peak oxygen consumption, NTproBNP and MLHF) were assessed using either Spearman’s rank or Pearson’s correlation coefficient (r).

Results

Participant demographics, clinical characteristics and medications list are presented in [Table 1]. BMI was significantly different between individuals with HCM and healthy controls (p<0.01). Differences in acceleration categories between individuals with HCM and healthy controls is described in [Table 2]. After adjusting for BMI, individuals with HCM engaged in less MVPA (86 (55–138) vs. 140 (121–149) minutes/day, p<0.05) compared to healthy controls. Time spent in MVPA-5 min bouts (6 (2–15) vs. 27 (23–37) minutes/day, p<0.01) and MVPA-10 min bouts (9 (0–19) vs. 35 (17–54) minutes/day, p<0.01) were also lower in individuals with HCM versus healthy controls. There were no significant differences in inactivity, sleep duration or sleep efficiency between individuals with HCM versus healthy controls. Inactivity time and bouts (inactivity-30min) were higher in individuals with HCM compared to healthy controls, whereby those with HCM spent over 6 hours/day in 30-minute inactivity bouts. As detailed in [Table 3], for individuals with HCM only, peak oxygen consumption was positively correlated with MVPA (r=0.60, p<0.01) and MVPA-5 min bouts (r=0.47, p<0.05). The MLHF score was positively correlated with sleep duration (r=0.45, p<0.05). No other significant correlations were found.

Table 1 Participant demographics, clinical characteristics and medications for individuals with hypertrophic cardiomyopathy and healthy controls

	HCM (n=21)	Healthy controls (n=21)
Demographics
Age (years) (mean±SD)	52±15	51±14
Sex (male/female)	15/6	15/6
Body weight (kg)	86 (80–92)*	80 (68–86)
BMI (kg/m2)	29 (25–31)**	25 (22–27)
Clinical characteristics
ICD, N (%)	7 (33)
IVSD (mm)	16 (13–18)
PWD (mm)	10 (9–10)
LVOTmaxPG (mmHg)	4.5 (3.1–6.8)
LAD (mm)	38 (36–41)
LAVi (ml/m2)	30 (27–42)
E/E’	8.7 (5.9–9.8)
NTproBNP (ng/L)	325 (103–826)
Exercise capacity and quality of life
Peak oxygen consumption (ml/kg/min)	19 (16–21)
Minnesota Living with Heart Failure (total score)	16 (6–30)
Medications, N (%)
Beta-adrenergic blocker	11 (52)
Calcium channel blocker	5 (24)
Diuretics	2 (10)
Anti-arrhythmia	4 (19)
Anti-anginal	1 (5)
Diabetes	1 (5)
Anti-inflammatory	3 (14)
Anti-depressant	3 (14)
Statins	4 (19)
Anti-coagulants	6 (29)

Data described as median (interquartile range) unless otherwise stated. Significant difference *p<0.05, ** p<0.01. Abbreviations: BMI: Body mass index; HCM: Hypertrophic cardiomyopathy; ICD: Implantable cardioverter defibrillator; IVSD: Interventricular septum diameter; LAD: Left atrial diameter; LAVi: Left atrial volume index; LVOTmaxPG: Left ventricular outflow tract maximum pressure; PWD: Posterior wall diameter.

Table 2 Acceleration categories (physical activity, inactivity and sleep variables) separated by individuals with hypertrophic cardiomyopathy vs. age and sex-matched healthy controls

	HCM (n=21)	Healthy controls (n=21)	p-value (adjusted for BMI)
Acceleration categories
Wear time (minutes/day)	1440 (1440–1440)	1440 (1440–1440)
Waking hours (minutes/day)
Inactivity	657 (643–749)	593 (547–708)	0.724
Light physical activity	197 (174–222)	225 (179–286)	0.286
MVPA	86 (55–138)	140 (121–149)	0.048*
Bouts of activity during waking time (minutes/day)
Inactivity 30-minute	376 (308–484)	242 (193–348)	0.241
MVPA 5-minute	6 (2–15)	27 (23–37)	0.009**
MVPA 10-minute	9 (0–19)	35 (17–54)	0.000**
Sleep
Sleep duration (minutes/day)	411 (366–437)	400 (363–435)	0.175
Sleep efficiency (%)	88 (80–92)	88 (86–90)	0.272

Data described as median (interquartile range) unless otherwise stated. Significant difference *p<0.05, ** p<0.01. Abbreviations: HCM: Hypertrophic cardiomyopathy; MVPA: Moderate-vigorous physical activity.

Table 3 Correlations between acceleration categories and clinical parameters for individuals with hypertrophic cardiomyopathy only

		Inactivity	LPA	MVPA	MVPA-5 min	MVPA-10 min	Inactivity-30 min	Sleep duration	Sleep efficiency
Left atrial diameter (mm)	r	0.19	−0.32	−0.21	−0.30	−0.08	0.36	−0.12	−0.38
	p	0.42	0.16	0.37	0.19	0.74	0.11	0.61	0.09
	N	21	21	21	21	21	21	21	21
Left atrial volume index (ml/m2)	r	−0.20	−0.13	0.15	−0.07	0.38	−0.13	−0.05	−0.22
	p	0.38	0.59	0.51	0.77	0.09	0.58	0.83	0.35
	N	21	21	21	21	21	21	21	21
Peak oxygen consumption (ml/kg/min)	r	−0.19	0.08	0.60**	0.47*	0.03	−0.30	−0.18	−0.09
	p	0.43	0.74	0.01	0.04	0.90	0.21	0.47	0.72
	N	19	19	19	19	19	19	19	19
NTproBNP (ng/L)	r	−0.18	−0.02	−0.01	−0.03	0.16	−0.24	0.19	−0.17
	p	0.47	0.94	0.97	0.89	0.51	0.32	0.43	0.48
	N	19	19	19	19	19	19	19	19
MLHF (total score)	r	−0.26	0.21	−0.13	0.02	−0.14	−0.27	0.45*	0.12
	p	0.25	0.36	0.57	0.92	0.55	0.23	0.04	0.61
	N	21	21	21	21	21	21	21	21

Significant difference *p<0.05, **p<0.01. Abbreviations: LPA: Light physical activity; MLHF: Minnesota Living with Heart Failure; MVPA: Moderate-vigorous physical activity. Inactivity, LPA, MVPA, MVPA-5 min, MVPA-10 min, Inactivity-30 min; sleep duration measured in minutes/day; sleep efficiency measured as %.

Discussion

The major findings of this study were individuals with HCM do not accumulate bouts of MVPA (MVPA-5 min and MVPA-10 min) and are spending less time in this intensity when compared to age and sex-matched healthy controls. For individuals with HCM only, significant positive associations existed between peak oxygen consumption and MVPA and MVPA-5 min bouts. These findings highlight that physical fitness is strongly related to time spent in moderate-intensity activity. Interestingly, the relationships found between the MLHF score and sleep duration suggests that a more severe disease burden is associated with longer sleep duration. These findings provide new insights into short-term MVPA patterns of individuals with HCM.

Individuals with HCM continue to follow a sedentary lifestyle due to the fear of sudden cardiac death [6] [23]. Thirty-three percent of individuals with HCM had an implantable cardioverter defibrillator (ICD) in this study. Anxiety towards suffering an ICD shock is associated with not meeting the physical activity guidelines in individuals with HCM [24]. No differences in accelerometry-measured physical activity has been found between HCM individuals with or without ICD [24]. Physical activity interventions have been deemed safe and beneficial for this population [6]. For example, the randomized controlled RESET-HCM trial, which included high-risk individuals with HCM (i. e.>30% fitted with ICD) reported no major adverse events including appropriate ICD shocks in either the exercise training or usual activity groups [25]. The amount of time spent in bouts of MVPA (MVPA-5 min and MVPA-10 min) was significantly lower in individuals with HCM versus healthy controls in this current study when controlled for BMI. Similarly, individuals who have both Type 2 diabetes and cardiovascular disease have consistently lower MVPA-10 min bouts compared to healthy controls [19]. Interestingly, in individuals with cardiovascular disease, a protective association has been found between accumulating at least 10-minute bouts of MVPA and lower frailty, which was not noted in individuals without cardiovascular diseases [26]. Our current findings are noteworthy as this population were relatively well with a median peak oxygen consumption of 19 ml/kg/min, NTproBNP of 325 ng/L and LAVi of 30 ml/m² suggesting that in a mildly diseased population of HCM patients, activity bouts remain poor.

The prevalence of overweight and obesity is high in individuals with HCM, which is associated with disease progression, atrial fibrillation and heart failure onset [9]. In this current study, individuals with HCM had a significantly higher BMI than healthy controls, which suggested overweight or pre-obesity. Sustained bouts of at least moderate-intensity physical activity lasting 10 minutes or more are associated with lower levels of obesity markers such as BMI and waist circumference [22]. Regular engagement in MVPA in middle-aged individuals with HCM has been found to be an important indicator of lower all-cause and cardiovascular mortality [27]. In this current study, engagement in MVPA was higher than expected for individuals with HCM when compared to other studies [28] [29], but this may have resulted from the sporadic arm movements captured on the accelerometer, which is difficult to discount from true physical activity [19]. Therefore, it is more informative to look at MVPA in bouts when looking at associations with clinical parameters [19].

Peak oxygen consumption was positively associated with both MVPA and MVPA-5 min bouts. These positive associations are similar to the findings from the MAVERICK-HCM Study, who noted positive correlations for peak oxygen uptake with both average daily accelerometer units and step counts in individuals with symptomatic non-obstructive HCM [30]. Likewise, positive associations have been previously found between self-reported exercise capacity and moderate and vigorous intensity physical activity [31]. Moderate-intensity exercise training has resulted in positive increases in peak oxygen consumption in individuals with HCM [25]. However, this is the first study to report these associations with accelerometry measured MVPA bouts in this clinical population.

In this current study, associations were found between the MLHF score and sleep duration. Sleep disorders are highly prevalent in individuals with HCM [1]. Pedrosa (2010) [32] found individuals with HCM had longer sleep duration but self-reported worse sleep quality, longer sleep latency, more sleep disturbances and daytime dysfunctions leading to a negative impact health-related quality of life. Possible reasons for longer sleep duration in individuals with HCM has been linked to higher consumption of antidepressants or more diseased patients spending more time in bed [32]. However, there were no significant differences in sleep duration between individuals with HCM and healthy controls but those individuals with HCM who reported a higher disease burden spent more time asleep.

In conclusion, individuals with HCM are consistently not accumulating MVPA in either 5 or 10-minute bouts. The positive associations found between peak oxygen consumption and the MVPA variables highlight the importance of physical activity intensity to physical fitness. Higher disease burden was prominent in those with longer sleep duration in this study, which warrants further investigation. Individuals with HCM should be encouraged to engage in at least moderate-intensity physical activity in minimum bouts of 5 and 10 minutes to benefit physical fitness and limit the periods of inactivity to potentially improve exercise tolerance and reduce disease burden.

• References

• 1 Ommen SR, Mital S, Burke MA. et al. 2020 AHA/ACC guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy. Circulation 2020; 142: e558-e631
• 2 Maron BJ. Hypertrophic cardiomyopathy: An important global disease. Am J Med 2004; 116: 63-65
• 3 Semsarian C, Ingles J, Maron MS. et al. New perspectives on the prevalence of hypertrophic cardiomyopathy. J Am Coll Cardiol 2015; 65: 1249-1254
• 4 Maron BJ, Casey SA, Poliac LC. et al. Clinical course of hypertrophic cardiomyopathy in a regional United States cohort. JAMA 1999; 281: 650-655
• 5 Bull FC, Al-Ansari SS, Biddle S. et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med 2020; 54: 1451-1462
• 6 Gati S, Sharma S. Exercise prescription in individuals with hypertrophic cardiomyopathy: What clinicians need to know. Heart 2022; heartjnl 2021-319861
• 7 Lavie CJ, Ozemek C, Carbone S. et al. Sedentary behavior, exercise, and cardiovascular health. Circ Res 2019; 124: 799-815
• 8 Sweeting J, Ingles J, Timperio A. et al. Physical activity in hypertrophic cardiomyopathy: prevalence of inactivity and perceived barriers. Open Heart 2016; 3: e000484
• 9 Fumagalli C, Maurizi N, Day SM. et al. Association of obesity with adverse long-term outcomes in hypertrophic cardiomyopathy. JAMA Cardiol 2020; 5: 65-72
• 10 Tafelmeier M, Baessler A, Wagner S. et al. Design of the SILICOFCM study: Effect of sacubitril/valsartan vs lifestyle intervention on functional capacity in patients with hypertrophic cardiomyopathy. Clin Cardiol 2020; 43: 430-440
• 11 Malay S, Chung KC. The choice of controls for providing validity and evidence in clinical research. Plast Reconst Surg 2012; 130: 959-965
• 12 van Hees VT, Gorzelniak L, Dean León EC. et al. Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PloS one 2013; 8: e61691
• 13 Migueles JH, Rowlands AV, Huber F. et al. GGIR: A research community–driven open source R package for generating physical activity and sleep outcomes from multi-day raw accelerometer data. J Meas Phys Behav 2019; 2: 188
• 14 RCoreTeam. R: A language and environment for statistical computing. R Foundation for Statistical Computing. (2021). In Internet: http://www.R-project.org/; (1 November 2022)
• 15 van Hees VT, Fang Z, Langford J. et al. Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: An evaluation on four continents. J Appl Physiol 1985; 2014: 738-744
• 16 Charman SJ, van Hees VT, Quinn L. et al. The effect of percutaneous coronary intervention on habitual physical activity in older patients. BMC Cardiovasc Disord 2016; 16: 248
• 17 da Silva IC, van Hees VT, Ramires VV. et al. Physical activity levels in three Brazilian birth cohorts as assessed with raw triaxial wrist accelerometry. Int J Epidemiol 2014; 43: 1959-1968
• 18 Sabia S, van Hees VT, Shipley MJ. et al. Association between questionnaire- and accelerometer-assessed physical activity: The role of sociodemographic factors. Am J Epidemiol 2014; 179: 781-790
• 19 Cassidy S, Fuller H, Chau J. et al. Accelerometer-derived physical activity in those with cardio-metabolic disease compared to healthy adults: A UK Biobank study of 52,556 participants. Acta Diabetol 2018; 55: 975-979
• 20 Hildebrand M, Van Hees VT, Hansen BH. et al. Age-group comparability of raw accelerometer output from wrist-and hip-worn monitors. Med Sci Sports Exerc 2014; 46: 1816-1824
• 21 van Hees VT, Sabia S, Anderson KN. et al. A novel, open access method to assess sleep duration using a wrist-worn accelerometer. PLoS one 2015; 10: e0142533
• 22 Strath SJ, Holleman RG, Ronis DL. et al. Objective physical activity accumulation in bouts and nonbouts and relation to markers of obesity in US adults. Prev Chronic Dis 2008; 5: A131
• 23 Okwose NC, O’Brien N, Charman S. et al. Overcoming barriers to engagement and adherence to a home-based physical activity intervention for patients with heart failure: A qualitative focus group study. BMJ Open 2020; 10: e036382
• 24 Sweeting J, Ball K, McGaughran J. et al. Impact of the implantable cardioverter defibrillator on confidence to undertake physical activity in inherited heart disease: A cross-sectional study. Eur J Cardiovasc Nurs 2017; 16: 742-752
• 25 Saberi S, Wheeler M, Bragg-Gresham J. et al. Effect of moderate-intensity exercise training on peak oxygen consumption in patients with hypertrophic cardiomyopathy: A randomized clinical trial. JAMA 2017; 317: 1349-1357
• 26 Kehler DS, Clara I, Hiebert B. et al. The association between patterns of physical activity and sedentary time with frailty in relation to cardiovascular disease. Aging Med (Milton) 2019; 2: 18-26
• 27 Kwon S, Lee HJ, Han KD. et al. Association of physical activity with all-cause and cardiovascular mortality in 7666 adults with hypertrophic cardiomyopathy (HCM): More physical activity is better. Br J Sports Med 2021; 55: 1034-1040
• 28 Sweeting J, Ingles J, Ball K. et al. A control theory-based pilot intervention to increase physical activity in patients with hypertrophic cardiomyopathy. Am J Cardiol 2018; 122: 866-871
• 29 Sweeting J, Ingles J, Ball K. et al. Daily step count as a simple marker of disease severity in hypertrophic cardiomyopathy. Heart Lung Circ 2018; 27: 752-755
• 30 Agarwal P, Shcherbina A, Day S. et al. Abstract 14963: Accelerometer-measured activity in non-obstructive hypertrophic cardiomyopathy: Patient-generated activity measures correlate with, and are convolutional neural network predictors of, clinical parameters in the MAVERICK-HCM Study. Circulation 2020; 142: A14963-A14963
• 31 Reineck E, Rolston B, Bragg-Gresham JL. et al. Physical activity and other health behaviors in adults with hypertrophic cardiomyopathy. Am J Cardiol 2013; 111: 1034-1039
• 32 Pedrosa RP, Lima SG, Drager LF. et al. Sleep quality and quality of life in patients with hypertrophic cardiomyopathy. Cardiology 2010; 117: 200-206