Abstract
Background
A paradigm shift has emerged regarding exercise participation in patients with hypertrophic cardiomyopathy (HCM), with recent studies suggesting that structured training may improve functional capacity and cardiopulmonary responses. However, the effects of structured exercise interventions in HCM have not been comprehensively synthesized.
Aim
The main objective was to determine the effect of exercise training on bodyweight, functional capacity, echocardiography, blood pressure, heart rate (HR), double product, and NT-proBNP in HCM patients.
Methods
Randomized controlled trials (RCTs) and non-randomized individualized endurance and concurrent training interventions including cardiopulmonary exercise test and echocardiographic measures in adult (≥ 18 years) obstructive and non-obstructive HCM patients were extracted from PubMed, Web of Science, and Cochrane in December 2025. Random-effects meta-analyses and meta-regressions were performed, and risk of bias was assessed using the ROBINS-I V2 tool for internal validity.
Results
Data from 8 studies (3 RCTs) with 205 low to moderate risk patients showed that training significantly (all p < 0.05) increased [mean (95% CI)]: peak VO2 (pVO2) [2.3 (0.76, 3.83) mL kg−1 min−1], predicted pVO2 [8.1 (2.7, 13.4) %], exercise time [1.0 (0.5, 1.5) min], peak HR [5.2 (0.04, 10.3) bpm], and HR reserve (HRR) [5.5 (2.5, 8.5) bpm]; and decreased body mass index [− 1.12 (− 2.13, − 0.11) kg m−2], and rest HR [− 3.1 (− 5.7, − 0.4) bpm]. A lower baseline HRR was associated with broader increments in pVO2 [1.3 (0.8, 1.9) mL kg−1·min−1, R2 = 0.86, p < 0.05, per 10-unit decrease]. A small between-group difference in maximal wall thickness was observed in controlled data compared to usual care [− 0.9 (− 1.7,− 0.1) mm, p < 0.05, k = 3]. Other echocardiographic features, blood pressure, and NT-proBNP did not change. There were no differences between endurance and concurrent training. No adverse events were reported in these cohorts.
Conclusion
Individualized exercise interventions in low to moderate risk HCM patients were associated with improvements in functional capacity, exercise tolerance, cardiac adaptability, and chronotropic competence. The effect of beta-blockers on HRR and subsequent functional adaptations to training warrants future research.
Limitations
Results should be interpreted cautiously due to heterogeneous study populations, predominantly mild/low-risk HCM phenotypes, the limited number of interventions, and restricted generalizability beyond individualized, guided, and mostly on-site supervised exercise settings.
Trial registration The protocol was registered in PROSPERO: CRD420251058384.
Infographic
Supplementary Information
The online version contains supplementary material available at 10.1186/s40798-026-01059-0.
Keywords: Physical activity, Functional capacity, Imaging, Cardiopulmonary exercise test, Cardiac rehabilitation
Lay Summary
Exercise training is emerging as a promising therapeutic strategy for individuals with hypertrophic cardiomyopathy (HCM). This study systematically reviewed and analyzed evidence from eight clinical trials including 205 low to moderate risk patients with obstructive and non-obstructive phenotypes. Importantly, all interventions were individualized, guided, and followed up by the researchers and no adverse events were reported in these cohorts.
The available evidence suggests that structured exercise programs are associated with meaningful improvements in multiple areas of health. Participants showed increased functional capacity, reflected by higher peak oxygen consumption (pVO2) and longer exercise time. These increases were significantly higher compared to control groups consisting in usual care, and similar between endurance-only and concurrent endurance + resistance training interventions. Exercise training was also associated with improved heart rate responses during physical activity, including higher peak values, greater reserve, and lower resting heart rate.
Importantly, no adverse structural or functional changes in heart imaging were observed, confirming that short to mid-term exercise programs were not associated with adverse changes in cardiac morphology in HCM. Moreover, a small between-group reduction in maximal wall thickness (~ 1 mm) was observed compared to usual care.
Overall, structured exercise programs lasting approximately 2–3 months or longer may be sufficient to induce positive adaptations. These findings support the emerging role of individualized exercise as a potential component of HCM management in selected patients, while more research on longer programs and greater cohorts is warranted.
Supplementary Information
The online version contains supplementary material available at 10.1186/s40798-026-01059-0.
Key Points
Exercise increases pVO2, exercise time, and heart rate adaptability.
Training reduces resting heart rate and body mass index.
Exercise training was not associated with any adverse changes in heart structure or function in patients with hypertrophic cardiomyopathy.
No adverse events were reported in these cohorts participating in individualized and mostly supervised exercise interventions, conditions that may have contributed to the favorable outcomes observed.
Supplementary Information
The online version contains supplementary material available at 10.1186/s40798-026-01059-0.
Introduction
Hypertrophic cardiomyopathy (HCM) is the most common form of cardiomyopathy (1:500 individuals), and is defined by the presence of left ventricular hypertrophy, with a maximal wall thickness (MWT) ≥ 15 mm, in the absence of other primary causes [1, 2]. Over the past decade, a paradigm shift has emerged advocating for the incorporation of physical exercise in the clinical management of HCM patients [3, 4]. Physical activity may confer benefits on the HCM phenotype and improve mid- to long-term outcomes through multiple mechanisms [5]. On one hand, physical activity itself (other than structured training) helps managing weight [6]. A meta-analysis of 11,672 HCM patients reported an average body mass index (BMI) of 26.9 ± 6.5 kg/m2 [7]. Excess body weight has been associated with a worse phenotype a poorer prognosis, and an increased cardiac workload [8, 9]. Moreover, a significant and positive association between functional capacity and long-term prognosis and event-free survival has been demonstrated [10, 11]. Current evidence suggests that different training types including endurance-only or concurrent resistance and endurance training elicit positive functional adaptations including an increase in peak oxygen consumption (pVO2) [12]. Specifically related to cardiopulmonary exercise test (CPET)-derived parameters, the latest study on the topic highlighted that fit HCM individuals show impaired ventilatory efficiency compared to healthy athletes [13]. Authors observed an excessive ventilatory response with increased early VE/VCO2 slope and end-tidal CO2 at the second ventilatory threshold (VT2), and a higher VE/VCO2 nadir. These abnormalities may be attributable to hyperpnea resulting from altered chemoreflex sensitivity and/or a mismatch in ventilation–perfusion [14]. Although exercise may attenuate these impairments, its specific effects remain unclear. A previous meta-analysis and pilot intervention study by our group stated that most of the publications on the topic were theoretical rather than actual training interventions [12, 15]. However, eight interventional studies have been published within the past decade, with four emerging in the past year alone, demonstrating promising outcomes [15–22]. Despite the growing body of evidence, a comprehensive synthesis of the available literature is lacking and is necessary to consolidate the current knowledge and to guide future intervention strategies, particularly in light of the increasing clinical and scientific interest in this area.
Accordingly, the main aim of the present study was to analyze the results of exercise training programs conducted to date in patients with HCM. Additionally, we sought to identify which variables are associated with the improvements observed following exercise and to determine the extent and direction of the relationship with the baseline values of the variables of interest. We hypothesized that structured training would allow improvements in functional capacity and cardiac function, and that patients with a lower baseline pVO2 would benefit more.
Methodology
The protocol for this study was registered in PROSPERO (CRD420251058384), and this review was conducted and reported in accordance with the PRISMA [23] and MOOSE [24] reporting guidelines (Supplemental Table 1).
Eligibility Criteria
The eligibility criteria to include articles were (a) the sample included adult (> 18 years) patients with obstructive or non-obstructive phenotypes of HCM; (b) patients had a confirmed phenotypic HCM defined by a maximal LV wall thickness ≥ 15 mm in the absence of other primary causes of LV hypertrophy or ≥ 13 mm in first-degree relatives carrying a definite or likely disease-causing genetic variant; (c) interventions were based on either resistance or endurance training, or a combination of both; (d) functional capacity was assessed through CPET and pre- and post-exercise values were provided whether in maximal oxygen consumption (mL kg−1 min−1) or metabolic equivalents (MET); (e) studies included pre- and post-training echocardiography; and (f) the training was designed, individualized, guided, and followed up by the researchers (not self-reported physical activity). Randomized controlled trials (RCTs) and non-randomized interventions were included. Observational studies where patients were followed up after performing a self-reported physical activity were excluded. When studies compared different training protocols in separated groups, each group was individually included (i.e., moderate and high intensity). Only trials with humans were accepted. Manuscripts had to be original research (not a review or conference abstract) and be written in English.
Search Strategy
A systematic review of the literature was conducted (AB, BB) on PubMed, Web of Science, and the Cochrane Library in December 2025. The search equation included topics related to HCM and exercise and is presented in the Supplemental Table 2. Two investigators (AB, BB) independently screened for inclusion the articles retrieved from the search. The original search yielded 10,621 studies. After deduplication and initial screening, titles and abstracts of 2428 articles were independently read and reviewed by three authors (AB, BB, JG). Eight studies [15–22] were selected for inclusion (Fig. 1) and their reference list was checked for any missing study of interest. When disagreements occurred, a consensus was reached with the rest of the authors. One study was excluded because training was not individualized, guided, and followed up by researchers [6]. The methodological quality of exercise training interventions was independently assessed by two reviewers (AB, BB) using the TESTEX scale [25], with a 100% inter-reviewer agreement.
Fig. 1.
PRISMA flow chart of the search
Data Extraction and Synthesis
Variables regarding weight and body composition, CPET, imaging features, blood pressure (BP), HR, double product (DP), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were extracted and classified in a Microsoft Excel sheet. Those reported in at least three studies were included in quantitative analysis. Data synthesis was performed according to the Cochrane Handbook for Systematic Reviews of Interventions [26] and can be consulted in the Supplemental Methods.
Meta-analyses
Random-effects meta-analyses were conducted in Review Manager V.5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014) on the change in each study outcome mentioned in the data extraction section. Effect sizes are presented as mean difference (MD) with means and 95% CIs for body weight and BMI, CPET parameters, imaging features, arterial pressure, HR, and NT-proBNP. The complete list of variables can be found in the results section. Given the inclusion of three RCTs, we also conducted random-effects meta-analyses to evaluate between-group differences in pre- to post-intervention changes. These analyses were restricted to variables for which data were available from both intervention and control groups in at least two of the three RCTs.
Heterogeneity and Risk of Bias
Heterogeneity was assessed by χ2 and I2 and significance was set at p < 0.05. The internal validity of each study was assessed through domain-based evaluation to quantify risk of bias for each study using the ROBINS-I V2 tool [26, 27] and was independently performed by two investigators (AB, BB). The data included in the meta-analyses were restricted to studies with two or less reported high or unclear risk domains (Supplemental Table 3). Formal assessment of publication bias was not possible considering the limited number of studies (< 10), but funnel plots were generated and visually inspected for exploratory purposes (Suppl. Figure 1). Multiple sensitivity analyses were performed to determine if any of the results were influenced by the studies that were removed.
Meta-regression
In an effort to understand the sources of heterogeneity meta-regressions were performed on the dependent variables: BMI, pVO2, pVO2 (% predicted), peak HR, rest HR, and HRR (HRR: peak HR–resting HR) because they were statistically significant and had enough studies (≥ 6). Meta-regression was used in addition to subgroup analyses to allow for the inclusion of more than one covariate at a time. Eleven covariates (baseline values) were chosen as independent variables a priori to be included in our meta-regression: BMI, weight, pVO2, pVO2 (% pred), MWT, LVOT at rest, LVEF (%), E/E’ ratio, rest SBP, rest HR, and HRR because there is evidence that all can influence CPET-derived parameters [10, 11] and there was sufficient data (n ≥ 4 training groups) to perform the analyses according to the inclusion criteria. These covariates were meta-regressed individually in univariate models in a random-effects meta-regression model using IBM SPSS Statistics, v.25 (IBM Corp., Armonk, NY, USA) and a weighted least squares model.
Subgroup Analyses
Subgroup analyses were conducted in RevMan (Review Manager, V.5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014). Subgroup analyses were performed on variables with data of at least three studies on each subgroup with the type of training (endurance-only or concurrent) as the subgroup to generate forest plots and neatly present type of training as a categorical variable. Subgroup analyses were performed on changes in BMI, pVO2 (mL kg−1 min−1 and % of predicted), and maximal wall thickness MWT.
Sensitivity Analyses
Sensitivity analyses were conducted to evaluate the influence of each individual study on the overall estimate (Suppl. Results) due to the small number of studies included some of which had small sample sizes. These can disproportionately affect the overall results by increasing their weight, which may lead to an overestimation of the effect size [26, 28].
The weight of each study was calculated using the inverse variance method and subsequently leave-one-out analysis were performed, excluding individual studies to examine the effect on the pooled effect size and its 95% CI. A study was considered for exclusion if it met the three following criteria: (1) its weight exceeded twice the expected average weight of the studies, where the average weight is 100%/n, and n is the number of studies, (2) its inclusion caused a change in MD and 95% CI greater than 25%; and (3) its inclusion changed the significance of the results.
Results
Participants’ Characteristics
A total of 8 studies [15–22] with 9 training groups met the inclusion criteria (Fig. 1). Three studies were randomized controlled trials and five were non-randomized interventions. Publications ranged from 2015 to 2025, and the study quality from 6 to 14 points (out of 15) using the TESTEX scale (Suppl. Table 4). A total of 205 HCM participants (142 men and 63 women) were studied out of 2196 screened for inclusion and after an average study completion of 85% (mean ± SD): age 51 ± 11 years, BMI 30 ± 1.6 kg/m2, pVO2 21.3 ± 4.6 mL kg−1 min−1 and 73.8 ± 13.2% of predicted, MWT: 19.6 ± 3.3 mm, and LVEF: 63 ± 7%. The majority had low to moderate SCD risk profiles. Further participant details and outcomes are presented in Table 1. Inclusion and exclusion criteria, data regarding patient selection, and SCD-risk calculation [29] of each study are presented in Suppl. Table 5. Medications varied across studies and are displayed in Suppl. Table 6.
Table 1.
Mean (SD) pre- and post-training values for each variable of the participants in each study and training group
| Variable | Basu [22] | Bayonas-Ruiz [15] | Gudmundsdottir [21] | Klempfner [16] | Limongelli [19] | MacNamara (HIT) [20] | MacNamara (MIT) [20] | Saberi [17] | Wasserstrum [18] | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Pre | Post | Pre | Post | Pre | Post | Pre | Post | Pre | Post | Pre | Post | Pre | Post | Pre | Post | Pre | Post | |
| Participants (men–women) | 33 (30–3) | 2 (2–0) | 26 (19–7) | 20 (14–6) | 20 (13–7) | 7 (5–2) | 8 (5–3) | 57 (32–25) | 32 (22–10) | |||||||||
| Study design | RCT | Intervention | RCT | Intervention | Intervention | Intervention | Intervention | RCT | Intervention | |||||||||
| Age (years) | 48 (8) | 61.5 (2) | 56 (11) | 62 (13) | 45 (12) | 42 (8) | 52 (7) | 50.5 (13) | 58 (13) | |||||||||
| Weight and BMI | ||||||||||||||||||
| Weight (kg) | 82 (20) | 84 (19) | 92.5 (12) | 86.8 (11) | 85 (16) | 86 (16) | 98.4 (11) | 96.6 (9) | 91 (18) | 88 (19) | ||||||||
| BMI (kg m−2) | 28.1 (4) | 27.4 (4) | 29.7 (5) | 30.3 (5) | 32.4 (3) | 30.4 (3) | 29.1 (6) | 29.4 (6) | 32.7 (5) | 32 (4) | 30.6 (6) | 29.8 (6) | ||||||
| CPET | ||||||||||||||||||
| pVO2 ( mL kg−1 min−1) | 28.3 (9) | 30.2 (9) | 28.5 (5) | 32.5 (5) | 20.2 (6) | 22.0 (7) | 16.5 (8) | 25 (10) | 16.9 (5) | 17.2 (4) | 25 (8) | 26.6 (9) | 23.8 (6) | 24.9 (6) | 21.3 (6) | 22.7 (7) | 18.7 (7) | 23.6 (8) |
| pVO2 (L min−1) | 2.3 (0) | 2.6 (0) | 1.5 (0) | 1.4 (0) | 2.1 (1) | 2.2 (1) | 2.3 (0) | 2.3 (0) | 1.9 (1) | 1.9 (1) | ||||||||
| pVO2 (% of predicted) | 85 (27) | 91 (28) | 102 (10) | 117 (6) | 71 (22) | 77 (24) | 64 (30) | 98 (38) | 57 (15) | 59 (13) | 70 (16) | 74 (24) | 83 (18) | 87 (21) | 78 (19) | 83 (22) | 69 (27) | 87 (30) |
| VO2 at VT2 ( mL kg−1 min−1) | 23 (8) | 25 (9) | 25 (0) | 29.5 (2) | 13.6 (4) | 14.1 (4) | ||||||||||||
| VE/VCO2, at peak effort | 28 (3) | 29 (4) | 26.4 (3) | 27.4 (3) | 33 (5) | 31 (4) | 30.5 (4) | 29.3 (3) | 29.3 (5) | 29.6 (5) | ||||||||
| RER, peak | 1.1 (0) | 1.1 (0) | 1.1 (0) | 1.1 (0) | 1.1 (0) | 1.1 (0) | 1.1 (0) | 1.1 (0) | ||||||||||
| Exercise time (min) | 11.5 (2) | 13.5 (4) | 8.4 (0) | 9.2 (0) | 6.4 (3) | 8.2 (2) | 9 (2) | 9.8 (2) | ||||||||||
| HR, peak (bpm) | 140 (1) | 145 (7) | 114 (19) | 117 (22) | 105 (18) | 110 (21) | 161 (13) | 162 (14) | 162 (7) | 163 (7) | 110 (23) | 120 (23) | ||||||
| SBP, peak (mmHg) | 140 (20) | 147 (24) | 182 (21) | 171 (19) | 195 (21) | 199 (35) | 144 (24) | 152 (30) | ||||||||||
| Imaging | ||||||||||||||||||
| MWT (mm) | 16 (4) | 15.9 (4) | 16 (1.4) | 16 (1.4) | 21 (6) | 20.7 (6) | 24 (7) | 23 (8) | 23 (7) | 23 (7) | 21.1 (8) | 20.5 (6) | 17.7 (7) | 16.4 (3) | ||||
| Posterior wall diam. (mm) | 9.1 (1) | 10.3 (0) | 12 (6) | 10 (1) | 11 (1) | 10 (2) | 13.1 (7) | 11 (2) | ||||||||||
| LA size (mm) | 46.5 (2) | 44 (6) | 47.9 (6) | 47.1 (6) | 43.2 (8) | 43.6 (7) | 30 (10) | 32 (10) | ||||||||||
| LVEDD (mm) | 47.5 (5) | 48.3 (6) | 46 (3) | 50.5 (1) | 38 (8) | 41 (7) | 44 (7) | 47 (9) | 47 (7) | 44 (14) | ||||||||
| LVEF (%) | 75.5 (4) | 69.8 (2) | 58 (10) | 55.7 (8) | 67 (4) | 67 (7) | 62 (7) | 62 (7) | 71 (4) | 70 (4) | 60 (13) | 59 (13) | ||||||
| LVOT, at rest (mmHg) | 9 (6) | 10 (6) | 19 (24) | 17 (21) | 12 (5) | 13 (12) | 10 (7) | 11 (8) | 15 (14) | 18 (30) | ||||||||
| LVOT, peak effort (mmHg) | 20 (11) | 20 (11) | 57 (48) | 53 (49) | 41 (31) | 39 (40) | 48 (44) | 44 (52) | ||||||||||
| LVEDV index ( mL m−2) | 52 (17) | 52.4 (4) | 126 (28) | 143 (38) | 141 (23) | 140 (21) | 79 (13) | 83 (14) | ||||||||||
| LVESV index ( mL m−2) | 12.4 (2.3) | 15.8 (0) | 42 (12) | 46 (15) | 54 (16) | 53 (13) | 29.6 (9) | 30.6 (8) | ||||||||||
| LAVI ( mL m−2) | 47 (6) | 44.5 (6) | 45 (10) | 44 (10) | 47 (14) | 46 (15) | ||||||||||||
| E/A ratio | 1.3 (0) | 1.3 (1) | 1.6 (1) | 1.3 (1) | 1.3 (1) | 1.4 (1) | 1.2 (1) | 1.2 (1) | 1 (0) | 1 (0) | ||||||||
| E/E′ ratio | 7.5 (3) | 7.3 (3) | 13 (3) | 7.8 (3) | 8 (4) | 7.8 (3) | 11.1 (5) | 10.9 (4) | 14.7 (6) | 13.8 (4) | 12.3 (4) | 13 (6) | ||||||
| Arterial pressure | ||||||||||||||||||
| SBP, at rest (mmHg) | 122 (17) | 112 (19) | 136 (17) | 157 (9) | 119 (15) | 118 (14) | 131 (15) | 127 (18) | 130 (12) | 131 (12) | 121 (19) | 124 (20) | ||||||
| DBP, at rest (mmHg) | 80 (10) | 78 (14) | 86 (3) | 95 (1) | 77 (12) | 74 (12) | 76 (5) | 74 (6) | ||||||||||
| Heart rate | ||||||||||||||||||
| HR, at rest (bpm) | 72 (3) | 65 (0) | 66 (16) | 66 (11) | 66 (9) | 64 (8) | 74 (12) | 73 (11) | 78 (13) | 77 (10) | 68 (14) | 68 (11) | ||||||
| HRR (bpm) | 68 (4) | 80 (7) | 48 (8) | 51 (13) | 38 (19) | 45 (20) | 84 (6) | 88 (6) | 86 (8) | 89.3 (5) | 42 (12) | 52 (14) | ||||||
| Double product | ||||||||||||||||||
| DP, at rest (mmHg bpm) | 23,018 | 24,215 | 14,700 | 16,170 | 29,439 | 27,784) | 31,674 | 32,480 | 15,840 | 18,240 | ||||||||
| DP, peak eff. (mmHg bpm) | 9792 | 10,205 | 7854 | 7552 | 9694 | 9271 | 10,140 | 10,087 | 8228 | 8420 | ||||||||
| Biomarkers | ||||||||||||||||||
| NT-proBNP (pg/mL) | 248(204) | 298(281) | 329(262) | 262(28) | 50(46) | 32(57) | 469(270) | 478(296) | 79(118) | 94(91) | ||||||||
pVO2 peak oxygen consumption, VT2 second ventilatory threshold, RER respiratory exchange ratio, SBP/DBP systolic/diastolic blood pressure, LVEDD left ventricular end-diastolic dimension, LVEF LV ejection fraction, LVOT left ventricular outflow tract obstruction, LVEDV/LVESV left ventricular end-diastolic/end-systolic volume, LAVI left atrial volume index, DP double product, NT-proBNP N-terminal brain natriuretic peptide
Training Characteristics
Training protocols and their characteristics are presented in Table 2. Interventions ranged from 3 to 18 months and 2–5 sessions per week, with most of them consisting of 3 months with 2–3 weekly training days. All of them included endurance training in bike ergometers or treadmill, and some included resistance exercises [15, 19, 21, 22], especially those published in the last year [15, 21, 22]. Intensity was controlled mostly based on HRR and self-perceived exertion (RPE) using the Borg scale [30]. Resistance training intensity was unevenly controlled using RPE or more precise methods such as percentage of estimated 1-repetition maximum.
Table 2.
Training protocols and characteristics of each study and group
| Author, year | Duration, sessions | Endurance training | Resistance training | Additional measures |
|---|---|---|---|---|
| Klempfner, 2015 | 2 sessions/week, (41 h in total), no more details on duration/schedule | 50–85% of HRR and 13–15 points of RPE, progression not detailed | Not included | Holter, physical examination and echocardiography |
| Saberi, 2017 | 16 weeks, 4–7 sessions/week | 60–70% of HRR and 12–14 points of RPE, progression detailed | Not included | Electrocardiogram, echocardiography, blood tests, CMR, genetic testing |
| Wasserstrum, 2019 | 3–4 months, 2 sessions/week | 60–70% of HRR and 13 points of RPE, progression not detailed | Not included | Electrocardiogram, echocardiography |
| Limongelli, 2021 | 18 months, 3 sessions/week | 60–80% of pVO2, progression not detailed | Exercises poorly defined. Intensity at 65% of 1RM but no 1RM estimation nor volume, rest, etc., explained | Holter, physical exam, CMR, blood tests, echo-electro cardiography |
| MacNamara, 2023 | 5 months, 3–5 sessions/week | Two groups with 2%HR based on peak HR and MSS from CPET; progression well detailed | Not included | Echocardiography, body composition, blood tests |
| Bayonas-Ruiz, 2024 | 3 months, 2 sessions/week | 1 fartlek session with 14–25′: VT2 -5/10 bpm (from CPET) and 1 session 25–50′ at VT1 + 5/10 bpm | Exercises well defined with intensity 55–70% of 1RM, volume, rest, and level of effort well explained | Echocardiography, electrocardiogram, body composition, blood tests |
| Basu, 2025 | 3 months, 2 sessions/week | 70–85% of HRR. Volume and intensity progression not well detaileda | Exercises well defined with intensity up to each patient; volume, and rest well detailed | Echocardiography, electrocardiogram, CMR, quality of life, blood tests |
| Gudmundsdottir, 2025 | 3 months, 3 sessions/week | 10′ warm-up and 30′ continuous or interval training with 12–14 points of RPE, Progression detailed | Exercises somehow defined; at 60% of self-perceived max workload with 3 × 15 reps and RPE: 12–14 | Echocardiography, electrocardiogram, blood tests, right heart catheterization |
Progression refers to weekly changes in volume, intensity (value and changes/constant intensity), and duration of each bout of exercise. Table updated from Bayonas-Ruiz et al. [15]
CMR cardiac magnetic resonance, CPET cardiopulmonary exercise test, HRR heart rate reserve, MSS maximum steady state, RPE rate of perceived exertion, 1RM 1-repetition maximum
a: Basu et al. stated that the volume and intensity progression was shown in their Supplementary Table 6; however, the link to the Supplementary Material was not useful to reach the content. The corresponding author and the Editorial Board of the Journal were contacted to access such information but did not answer
Heterogeneity and Risk of Bias
Significant heterogeneity was found for changes in DBP at rest (χ2 = 14.1, I2 = 79%, p = 0.003), although the MD of the changes was non-significant in the meta-analysis. Heterogeneity in VO2 at VT2 stood close to significance (χ2 = 5.91, I2 = 66%, p = 0.05), although changes were not significant either. None of the studies initially included for qualitative and quantitative analysis were removed based on risk of bias (Suppl. Table 4).
Body Weight and BMI
Changes in body weight after training did not reach significance (MD = − 3.31 kg, 95% CI [− 7.58, 0.96], p = 0.13, I2 = 0%, n = 4 studies and 94 patients), but BMI was significantly reduced (MD = − 1.12 kg/m2, 95% CI [− 2.13, − 0.11], p = 0.03, I2 = 0%, n = 6 studies and 153 patients, Table 3). The reduction was significantly higher in the exercise training group compared to usual care (between-groups MD = − 0.80 kg/m2, 95% CI [− 1.60,− 0.00], p < 0.05, I2 = 0%), with no differences between endurance-only and concurrent training (Suppl. Tables 7–8). Patients with lower pVO2 and LVEF at baseline reduced their BMI to a greater extent (p < 0.05, Table 4).
Table 3.
Mean differences, 95% CI, heterogeneity, and significance values in the changes from pre- to post-exercise variables of body composition, CPET, echocardiography, arterial pressure, heart rate and cardiac biomarkers
| Variable | Studies (n) | Meta-analysis | Heterogeneity | ||
|---|---|---|---|---|---|
| M.D. (95% CI) | p value | I2 | p value | ||
| Body composition | |||||
| Weight (kg) | 5 (n = 94) | − 3.31 (− 7.58, 0.96) | 0.13 | 0% | 0.93 |
| BMI (kg m−2) | 6 (n = 127) | − 1.12 (− 2.13, − 0.11) | 0.03 | 0% | 0.93 |
| CPET | |||||
| pVO2 (mL kg−1 min−1) | 9 (n = 205) | 2.30 (0.76, 3.83) | < 0.01 | 20% | 0.27 |
| pVO2 (L min−1) | 5 (n = 94) | 0.04 (− 0.10, 0.19) | 0.55 | 0% | 0.70 |
| pVO2 (% of predicted) | 9 (n = 205) | 8.06 (2.69, 13.44) | < 0.01 | 32% | 0.56 |
| VO2 at VT2 (mL kg−1 min−1) | 3 (n = 92) | 2.13 (− 0.56, 4.82) | 0.12 | 66% | 0.05 |
| VE/VCO2, at peak effort | 5 (n = 138) | − 0.21 (− 1.32, 0.91) | 0.72 | 21% | 0.28 |
| RER, peak | 4 (n = 74) | − 0.00 (− 0.02, 0.01) | 0.94 | 0% | 0.95 |
| Exercise time (min) | 4 (n = 112) | 1.02 (0.52, 1.52) | < 0.001 | 13% | 0.32 |
| HR, peak (bpm) | 5 (n = 87) | 5.18 (0.04, 10.31) | < 0.05 | 0% | 0.83 |
| SBP, peak (mmHg) | 4 (n = 67) | 4.23 (− 4.09, 12.55) | 0.32 | 0% | 0.48 |
| Imaging | |||||
| MWT (mm) | 7 (n = 159) | − 0.41 (− 1.51, 0.69) | 0.47 | 0% | 0.99 |
| Posterior wall diameter (mm) | 4 (n = 49) | − 0.64 (− 2.21, 0.92) | 0.42 | 47% | 0.13 |
| Left atrial size (mm) | 4 (n = 111) | 0.30 (− 1.62, 2.22) | 0.76 | 0% | 0.64 |
| LVEDD (mm) | 5 (n = 82) | 1.54 (− 0.79, 3.87) | 0.20 | 19% | 0.29 |
| LVEF (%) | 6 (n = 126) | − 0.71 (− 2.03, 0.61) | 0.29 | 0% | 0.62 |
| LVOT, at rest (mmHg) | 5 (n = 118) | 1.03 (− 1.64, 3.69) | 0.45 | 0% | 0.64 |
| LVOT, peak exercise (mmHg) | 4 (n = 98) | − 0.55 (− 6.11, 5.01) | 0.85 | 0% | 0.97 |
| LVEDV index (mL m−2) | 4 (n = 74) | 3.06 (− 1.54, 7.66) | 0.19 | 0% | 0.85 |
| LAVI (mL m−2) | 3 (n = 79) | − 1.31 (− 5.15, 2.53) | 0.50 | 0% | 0.96 |
| E/A ratio | 5 (n = 76) | 0.03 (− 0.12, 0.17) | 0.74 | 0% | 0.98 |
| E/E’ ratio | 6 (n = 96) | − 0.40 (− 1.41, 0.61) | 0.44 | 0% | 0.52 |
| Arterial pressure | |||||
| SBP, at rest (mmHg) | 6 (n = 102) | − 1.29 (− 7.32, 4.74) | 0.68 | 38% | 0.16 |
| DBP, at rest (mmHg) | 4 (n = 50) | 1.08 (− 5.48, 7.63) | 0.75 | 79% | 0.003 |
| Heart rate | |||||
| HR, at rest (bpm) | 6 (n = 95) | − 3.06 (− 5.68, − 0.44) | < 0.05 | 0% | 0.41 |
| HRR (bpm) | 6 (n = 95) | 5.53 (2.51, 8.54) | < 0.001 | 10% | 0.35 |
| Double product | |||||
| DP, at rest (mmHg bpm) | 5 (n = 69) | − 71 (− 630, 488) | 0.80 | 0% | 0.93 |
| DP, peak exercise (mmHg bpm) | 5 (n = 69) | 1398 (− 20, 2816) | 0.05 | 0% | 0.59 |
| Biomarkers | |||||
| NT-proBNP (pmol/L) | 5 (n = 138) | − 4.59 (− 26.70, 17.50) | 0.68 | 0% | 0.59 |
Studies (n) study groups included in the meta-analysis (n = participants), BMI body mass index, CPET cardiopulmonary exercise test, M.D. Mean Difference, pVO2 peak oxygen consumption, VT2 second ventilatory threshold, RER respiratory exchange ratio, HR heart rate, MWT maximal wall thickness, SBP systolic blood pressure, DBP diastolic blood pressure, LVEDD left ventricular end-diastolic diameter, LVEF left ventricular ejection fraction, LVOT LV outflow tract gradient, LVEDV LV end-diastolic volume, LAVI left atrial volume index, HRR heart rate reserve, DP double product, NT-proBNP N-terminal pro brain natriuretic peptide
Table 4.
Results of the univariate regression models
| Variable | BMI (kg m−2) | Peak VO2 (mL kg−1 min−1) | ||||||
|---|---|---|---|---|---|---|---|---|
| N | Coeff. (95% CI) | Adj. R2 | p val. | N | Coeff. (95% CI) | Adj. R2 | p val. | |
| BMI | N.E | 5 | − 0.14 (− 0.34, 0.05) | 0.41 | 0.25 | |||
| Weight | 6 | − 0.33 (− 0.61, − 0.06) | 0.59 | 0.07 | 8 | − 0.44 (− 1.12, 0.23) | 0.22 | 0.25 |
| pVO2 | 6 | 0.20 (0.07, 0.33) | 0.71 | 0.04 | N.E | |||
| pVO2 (% pred.) | 6 | 0.05 (0.04, 0.06) | 0.96 | 0.00 | 9 | − 0.01 (− 0.16, 0.14) | 0.00 | 0.88 |
| MWT | 6 | − 0.08 (− 0.17, 0.01) | 0.40 | 0.18 | 9 | − 0.49 (− 0.96, − 0.02) | 0.61 | 0.08 |
| LVOT | 5 | − 0.08 (− 0.16, 0.01) | 0.51 | 0.17 | 6 | − 0.09 (− 0.16, − 0.02) | 0.60 | 0.07 |
| LVEF | 6 | 0.07 (0.03, 0.12) | 0.74 | 0.03 | 9 | − 0.14 (− 0.41, 0.13) | 0.13 | 0.33 |
| E/E' | 5 | 0.25 (− 0.13, 0.63) | 0.36 | 0.29 | 6 | − 0.32 (− 0.61, − 0.02) | 0.52 | 0.11 |
| Resting SBP | 4 | 0.05 (− 0.02, 0.12) | 0.50 | 0.30 | 7 | − 0.30 (− 0.60, − 0.00) | 0.44 | 0.11 |
| Resting HR | 4 | − 0.18 (− 0.28, − 0.08) | 0.87 | 0.07 | 7 | − 0.38 (− 0.79, 0.03) | 0.50 | 0.13 |
| HRR | 3 | − 0.03 (− 0.08, 0.02) | 0.63 | 0.42 | 6 | − 0.13 (− 0.18, − 0.08) | 0.86 | 0.01 |
| Variable | peak VO2 (% of predicted) | Peak HR (bpm) | ||||||
|---|---|---|---|---|---|---|---|---|
| N | Coeff. (95% CI) | Adj. R2 | p val. | N | Coeff. (95% CI) | Adj. R2 | p val. | |
| BMI | 6 | − 0.84 (− 1.50, − 0.18) | 0.68 | 0.09 | – | N.E | ||
| Weight | 8 | − 1.90 (− 4.19, 0.38) | 0.31 | 0.15 | 4 | 13.43 (3.97, 22.89) | 0.80 | 0.11 |
| pVO2 | N.E | 5 | − 0.13 (− 0.76, 0.51) | 0.05 | 0.72 | |||
| pVO2 (% pred.) | 9 | 0.14 (− 0.25, 0.53) | 0.06 | 0.51 | 5 | 0.00 (− 0.19, 0.20) | 0.00 | 0.99 |
| MWT | 9 | − 1.55 (− 3.18, 0.08) | 0.33 | 0.11 | 5 | − 0.79 (− 1.35, − 0.23) | 0.72 | 0.07 |
| LVOT | 6 | − 0.26 (− 0.47, − 0.04) | 0.58 | 0.08 | N.E | |||
| LVEF | 9 | − 0.07 (− 0.82, 0.67) | 0.01 | 0.85 | 5 | − 0.03 (− 0.38, 0.32) | 0.01 | 0.88 |
| E/E' | 6 | 0.23 (− 1.30, 1.75) | 0.02 | 0.78 | 3 | − 0.32 (− 1.39, 0.76) | 0.25 | 0.67 |
| Resting SBP | 7 | − 0.50 (− 1.59, 0.59) | 0.14 | 0.41 | 5 | − 0.18 (− 0.59, 0.22) | 0.21 | 0.44 |
| Resting HR | 7 | 0.07 (− 1.45, 1.59) | 0.00 | 0.93 | 5 | − 0.53 (− 1.35, 0.28) | 0.35 | 0.29 |
| HRR | 6 | − 0.58 (− 0.83, − 0.34) | 0.82 | 0.01 | 5 | − 0.12 (− 0.24, 0.00) | 0.58 | 0.14 |
| Variable | Resting HR (bpm) | HRR (bpm) | ||||||
|---|---|---|---|---|---|---|---|---|
| N | Coeff. (95% CI) | Adj. R2 | p val. | N | Coeff. (95% CI) | Adj. R2 | p val. | |
| BMI | 3 | 0.01 (− 0.16, 0.18) | 0.02 | 0.92 | 3 | − 0.14 (− 0.67, 0.39) | 0.20 | 0.70 |
| Weight | 5 | − 0.02 (− 0.45, 0.40) | 0.01 | 0.92 | 5 | − 0.54 (− 2.59, 1,52) | 0.08 | 0.65 |
| pVO2 | 6 | − 0.14 (− 0.44, 0.16) | 0.17 | 0.41 | 6 | 0.46 (0.05, 0.86) | 0.55 | 0.09 |
| pVO2 (% pred.) | 6 | − 0.04 (− 0.12, 0.05) | 0.14 | 0.46 | 6 | 0.17 (0.07, 0.27) | 0.73 | 0.03 |
| MWT | 6 | 0.11 (− 0.26, 0.49) | 0.08 | 0.59 | 6 | − 1.06 (− 1.36, − 0.76) | 0.92 | 0.00 |
| LVOT | 3 | − 0.05 (− 0.28, 0.17) | 0.17 | 0.73 | 3 | 0.14 (0.11, 0.16) | 0.99 | 0.05 |
| LVEF | 6 | − 0.08 (− 0.25, 0.09) | 0.16 | 0.43 | 6 | 0.27 (0.07, 0.46) | 0.64 | 0.06 |
| E/E' | 4 | − 0.11 (− 0.56, 0.34) | 0.11 | 0.67 | 4 | 0.17 (− 0.75, 1.08) | 0.06 | 0.76 |
| Resting SBP | 6 | − 0.06 (− 0.32, 0.21) | 0.04 | 0.71 | 6 | − 0.50 (− 1.02, 0.01) | 0.48 | 0.13 |
| Resting HR | N.E | 6 | − 0.21 (− 0.82, 0.40) | 0.11 | 0.53 | |||
| HRR | 6 | − 0.01 (− 0.06, 0.04) | 0.05 | 0.71 | N.E | |||
BMI body mass index, pVO2 peak oxygen consumption, pVO2 (pred.) pVO2 expressed as percentage of the predicted value, MWT maximal wall thickness, LVOT left ventricular outflow tract gradient, LVEF left ventricular ejection fraction, SBP systolic blood pressure, HR heart rate, HRR heart rate reserve (peak HR minus resting HR); bpm beats per minute, N.E. multivariate analysis not estimable because either an infinite or a large positive number was obtained due to an exact fit
Cardiopulmonary Performance
Training significantly improved pVO2 (MD = 2.3 mL kg−1 min−1, 95% CI [0.8, 3.8], p = 0.003, I2 = 20%, Table 3 and Fig. 2A) and % of predicted pVO2 (MD = 8%, 95% CI [3, 13], p = 0.003, I2 = 32%, Fig. 2B). Exercise training resulted in greater increases than usual care (between-groups MD = 2.1 mL kg−1 min−1, 95% CI [0.8, 3.5]; and 7% predicted, 95% CI [2, 11]; p < 0.01 all, Suppl. Table 7). No differences were found between endurance-only and concurrent training (Suppl. Table 8). Patients with lower baseline HRR had greater pVO2 increases (R2 = 0.855 and 0.822, respectively, p < 0.05 all, Fig. 3A and B). CPET time augmented (MD = 1 min, [0.5, 1.5], p < 0.001) to a greater extent with training compared to usual care (p < 0.01). VE/VCO2 at peak exercise, VO2 at VT2, and RER remained unaltered after training (p > 0.05 all). No differences in VO2 at VT2 and VE/VCO2 were present between training and usual care.
Fig. 2.
Forest plot of the mean differences in pre- to post-training values of pVO2 (A) and pVO2 expressed as a percentage of the predicted value (B). Each square represents an individual study, with the size of the square proportional to its relative weight in the meta-analysis. Horizontal lines indicate 95% confidence intervals. The solid vertical line represents the line of no effect (zero), while the dashed vertical line indicates the overall pooled effect estimate from the meta-analysis
Fig. 3.
Bubble plots of the meta-regression analyses examining the relationship between baseline heart rate reserve (HRR) and A the mean difference (MD) in pVO2, and B the MD in pVO2 expressed as a percentage of the predicted value. Each bubble represents a study, with bubble size proportional to the inverse of the variance (i.e., study weight) in the meta-analysis. The regression lines represent the estimated linear relationship with the corresponding 95% confidence intervals
Echocardiographic Features
Echocardiographic parameters did not show significant changes after training (Table 4). LVOT remained unchanged at rest and at peak exercise (p > 0.05 all) in both the exercise and control groups (Suppl. Table 7). MWT and posterior wall diameter were also unaltered (p > 0.05 all). However, the change in MWT was significantly different in the exercise training group compared to usual care favoring training (between-groups MD = − 0.9 mm, 95% CI [− 1.7, − 0.1], p < 0.05, I2 = 0%, Suppl. Table 7), with no differences between endurance-only vs. concurrent (Suppl. Table 8). Left atrial size, left atrial volume index (LAVI), and left ventricular end-diastolic dimension (LVEDD) showed no changes. LVEF and diastolic function (left ventricular end-systolic and end-diastolic volume index, E/A, and E/E′) did not change with exercise. Changes in E/A and E/E′ were compared for exercise vs. usual care and no significant differences were found.
Heart Rate and Heart Rate Reserve
Resting HR was reduced with training (MD = − 3 bpm, [− 5.7,− 0.4], p = 0.02), while peak HR augmented (MD = 5.2 bpm, [0.04, 10.3], p < 0.05) with no differences in the RER (MD = − 0.00, [− 0.02, 0.01], p = 0.94). The difference between both parameters significantly widened after training as observed by a higher HRR (MD = 5.5 bpm, 95% CI [2.5, 8.5], p < 0.001, Fig. 4). No significant univariate regression results were found regarding rest and peak HR. MWT and pVO2 (% predicted) were significantly associated to changes in HRR (R2 = 0.921 and 0.733, respectively p < 0.05 all, Table 4).
Fig. 4.
Forest plot of the mean differences in pre- to post-training values of heart rate reserve (HRR). Each square represents an individual study, with the size of the square proportional to its relative weight in the meta-analysis. Horizontal lines indicate 95% confidence intervals. The solid vertical line represents the line of no effect (zero), while the dashed vertical line indicates the overall pooled effect estimate from the meta-analysis
Blood Pressure
Exercise interventions did not produce significant changes at rest or at peak exercise (Table 3). SBP (MD = − 1.3 mmHg, 95% CI [− 7.3, 4.7], p = 0.68, I2 = 38%) and DBP at rest (MD = 1.0 mmHg, 95% CI [− 5.4, 7.6], p = 0.75, I2 = 79%) showed no changes and presented considerable heterogeneity. Peak SBP also remained unchanged (MD = 4.2 mmHg, 95% CI [− 4.1, 12.6], p = 0.32, I2 = 0%).
Double Product
Double product at rest did not change with training (MD = − 71 mmHg bpm, [− 630, 488], p = 0.80) but a tendency to augment at peak effort after interventions was observed (MD = 1398 mmHg bpm, 95% CI [− 20, 2816]), p = 0.05).
NT-proBNP
Changes in NT-proBNP after training were uneven, and mean differences on each individual study ranged from − 67 pg/mL [− 431, 298] to 50 pg/mL [− 69, 168], with no overall significant change (MD = 5 pg/mL, [− 27, 18], p = 0.68) and no differences in the exercise vs. control groups (between-groups MD = 13 pg/mL, 95% CI [− 20, 46], p > 0.05, Suppl. Table 7).
NYHA Class
Although NYHA functional class was not included in meta-analysis due to the reduced data, two studies reported significant improvements: 2.7 ± 0.5–2.1 ± 0.5 [16] and 2.4 ± 0.5–2.1 ± 0.6 [19] from pre- to post-exercise interventions in addition to the other objective measures of functional status.
Discussion
With the goal of synthesizing the existing evidence on the effects of exercise interventions in HCM patients, this study meta-analyzed and meta-regressed the pre- and post-training data of eight studies with obstructive and non-obstructive HCM patients with a focus on weight and BMI, CPET-derived parameters, echocardiography, arterial pressure, HR, DP, and NT-proBNP. No adverse events occurred in any study, although it is important to highlight that patients were highly selected (~ 10% of those screened for inclusion), had mostly low to moderate SCD risk (Suppl. Table 5), and that interventions were individualized, guided, and mostly supervised on-site. Moreover, the average compliance was 85%, which could represent an additional selection process by drop-out of patients due to discomfort or related reasons. Noteworthily, training protocols focused on endurance training at first, but added resistance exercises especially in the last year [15, 21, 22].
Body Weight and BMI
Exercise interventions promoted a significant decrease of BMI despite no changes in body weight (BW). This outcome may be attributable to the limited evidence: BW was reported in four studies (n = 93), whereas BMI was assessed in six studies (n = 153). The smaller sample size for BW may have reduced the statistical power to detect a significant reduction. Overweight has a negative impact in the HCM phenotype, represents an increased workload for the heart [31], and is common in HCM patients [7]. It is worth considering that training regimes themselves might not be the only reason for underlying BMI reductions, since patients included in these interventions may have felt more motivated to engage in healthier lifestyles overall. In this regard, the effect of training on body composition (other than BW alone) remains unexplored, since only two studies reported changes in fat mass or muscle mass [15, 20]. On one hand, patients in MacNamara et al. did not change fat mass or lean body mass, while Bayonas-Ruiz et al. reported an increase in muscle mass and reduction of body fat in two patients. However, the first consisted of endurance-only training, while the latter included resistance training also. Future research should consider the addition of resistance exercise and anthropometric measures to elucidate adaptations in muscle and fat mass. A preserved or increased skeletal muscle mass content is a better survival and life expectancy predictor than BW alone [32], and muscle mass might play an important endocrine role and reduce the peripheral workload for the circulatory system [33]. Guidance for future research on resistance training for exercise selection, training volume, distribution, intensity, and rest intervals is presented in Bayonas-Ruiz et al. [15].
Cardiopulmonary Performance
Regarding CPET, the average increase in pVO2 was 2.3 mL kg−1 min−1 [95% CI 0.8, 3.8] and 8% of the predicted pVO2 [95% CI 3, 13]. This change is slightly lower than that reported in a meta-analysis of three studies [12]. Importantly, the observed increase is of substantial clinical relevance, exceeding the pooled effect size reported for pharmacological interventions (+ 1.1 mL kg−1 min−1; 95% CI 0.0–2.3) [12], as well as the improvements achieved with novel cardiac myosin inhibitors in major randomized clinical trials including both obstructive and non-obstructive patient populations [34–36]. Subgroup analyses comparing endurance and concurrent training revealed no significant differences in the pVO2 increases, suggesting that endurance training alone may be sufficient to improve functional capacity. However, resistance exercise provides additional benefits in body composition [15]. Nonetheless, this hypothesis warrants further investigation in larger populations, incorporating anthropometric assessments and standardized resistance training protocols.
In addition to assessing peak functional capacity, recent research has emphasized the clinical relevance of submaximal exercise efficiency, particularly at the VT2 [37]. This approach may yield valuable insights for guiding exercise prescription and stratifying the risk of adverse events [13, 38]. However, the available evidence regarding ventilatory efficiency following exercise training remains limited. Although changes in VO2 at VT2 did not reach significance, two of the three available studies reported increases following training [15, 22]. Similarly, VE/VCO2 slope did not significantly change and findings across studies were inconsistent, with some reporting slight increases and others reductions after training [15, 17, 19, 21, 22], without significant differences compared to control groups (Suppl. Table 7). These discrepancies may be attributable to differences in training protocols and exercise intensity. Given the prognostic relevance of ventilatory efficiency in HCM, further research in larger cohorts is warranted to better characterize the effects of exercise training on submaximal cardiopulmonary responses [10, 39].
Echocardiographic Features
The groups in this meta-analysis included patients with mean LVOT values of non-obstructive phenotypes at rest, yet some mean ± SD data suggest that a proportion of patients likely presented with resting or dynamic obstruction, although not consistently reported. Both LVOT at rest and at peak exercise remained unaltered after the interventions. This finding may suggest that the exercise modalities and intensities applied were sufficient to improve functional capacity and HRR without adversely affecting obstruction in the short- to mid-term. While some authors hypothesize that exposure to chronic pressure and volume overload through exercise may exacerbate myocardial hypertrophy or activate modifier genes involved in hypertrophic signaling pathways [40], our analysis found no significant changes in parameters such as MWT or posterior wall diameter in the pooled estimates or any individual study. These findings align with previous longitudinal data from cohorts of HCM patients who self-reported regular participation in sports (e.g., football, cycling, soccer, tennis) after long-term follow-ups, in which no significant structural remodeling of the LV occurred [41–44]. A significant between-group difference in MWT changes was observed favoring the exercise group compared with controls (MD = − 0.9 mm, 95% CI [− 1.7, − 0.1], p < 0.05; Suppl. Table 7). Although this analysis is performed on a limited number of studies (k = 3) and highly selected low to moderate risk patients in short and mid-term interventions, the findings are promising. Even in the absence of significant reductions in MWT in the pooled analysis, the lack of exercise-associated wall thickening over the short- to mid-term may itself represent a clinically reassuring finding since MWT augmentation is associated to increased 5-year SCD risk and poorer prognosis [29, 45]. However, the small between-group difference observed in controlled comparisons should be interpreted cautiously and requires confirmation in larger and longer-term training interventions. In this context, no signs of LV dysfunction were detected in the cohorts, consistent with the absence of changes in key echocardiographic parameters in our analysis, including LVEF, LVEDD, LVEDV, LAVI, E/E′, and E/A. Although an increase in LA size was reported in one study [41], it was also present in patients who had discontinued exercise, suggesting LA enlargement reflects the natural HCM progression or is driven by mechanisms independent of exercise-induced stimulus. Similarly, the short and mid-term training programs analyzed in our meta-analysis did not result in cavity enlargement or adverse remodeling in these cohorts.
Heart Rate and Blood Pressure
The hemodynamic response to training was another topic of interest in this study. SBP and DBP remained unaltered both at rest and peak exercise, consistent with previous evidence [41, 43, 46]. In contrast, resting HR decreased after training (− 3 bpm, 95% CI − 5.7, − 0.4) while peak HR increased by ~ 5 bpm without changes in peak RER, suggesting improved exercise tolerance and testing performance under comparable maximal effort conditions. Therefore, the observed increase in HRR, with reduced HR at rest and increased peak HR, may reflect improved cardiovascular adaptability and chronotropic competence. This finding is of clinical and prognostic relevance since chronotropic incompetence and reduced HRR are associated to a worse HCM phenotype and increased risk of death independent of obstruction, age, and MWT [47, 48]. Nonetheless, it is important to highlight that medications including beta-blockers or calcium channel blockers varied across studies (Suppl. Table 6), potentially influencing both baseline physiological status and training adaptations.
Another exploratory finding was the association observed between baseline HRR and pVO2 improvements in the meta-regression analyses. Lower baseline HRR values were associated with greater gains in pVO2 following training. However, given the limited number of study groups and the absence of individual patient data, these findings should be interpreted cautiously and viewed as hypothesis-generating rather than predictive evidence. Future research on the influence of beta-blocker therapy is warranted to better understand its impact on training-induced adaptations. Prior evidence shows that pharmacological agents like myosin heavy chain inhibitors and calcium channel blockers elicit greater improvements in pVO2 compared to beta-blockers, which have low or no effect (MD = 0.3 mL kg–1 min–1, 95% CI − 4.0, 4.7) [12]. Despite remaining a standard therapy in HCM, the impact of beta-blockers on exercise tolerance and long-term outcomes remains an area of ongoing debate [49]. Future research is warranted to address the interaction of exercise training and beta-blocker therapy to elucidate their combined effect.
Univariate regression analyses estimated that HRR improved ~ 1 bpm less for each extra 1 mm of MWT and ~ 1.5 bpm more for every extra 10% of predicted pVO2 at baseline. These preliminary findings may shed light on the notion that individuals with greater LV hypertrophy and reduced pVO2 at baseline might experience attenuated improvements in cardiovascular adaptability following training, although the observed difference of 1–1.5 bpm is likely of limited clinical relevance and needs to be further explored in larger cohorts.
Double Product
Double product is a validated, non-invasive surrogate of myocardial oxygen consumption, and some studies have also suggested an association with myocardial efficiency, aerobic capacity, or functional reserve [50] , reporting a strong correlation between ventilatory thresholds and DP during CPET and proposing a resting DP value of 7500 to predict exercise tolerance [51] . In our study we did not observe significant changes at rest or peak exercise, although the latter almost reached significance (p = 0.05) to be increased in 1398 mmHg bpm after interventions. Therefore, these findings should be interpreted cautiously and considered exploratory. Future studies are warranted to better characterize the potential relevance of DP-related responses following exercise training in HCM patients.
NT-proBNP
Finally, NT-proBNP, a cardiac biomarker useful to assess disease progression that correlates with event-free survival [52] did not experience significant changes, and uneven values were observed across studies, suggesting that exercise might not have any impact on this variable.
Lastly, based on that discussed, future research should focus on including greater groups to assess which baseline variables predict better adaptations from training as proposed here. Investigations should include anthropometric and body composition assessment to extend the knowledge on the effect of exercise. Myocardial O2 consumption and ventilation efficiency from rest to peak exercise (i.e., rest, VT1, VT2, and peak exercise) are warranted to be studied. The results of this study are limited to the current body of evidence in few groups and 205 highly selected low to moderate risk patients but also promising.
Beyond the interpretation of individual outcomes, it is important to contextualize the clinical relevance of the overall findings. Improvements in pVO2 and exercise time likely represent the most meaningful findings of the present study, given their established association with functional status and prognosis in HCM. In contrast, changes in structural, hemodynamic, chronotropic, and biomarker-related variables should be interpreted more cautiously due to their modest magnitude, exploratory nature, and the limited number of controlled studies currently available. Therefore, while the present findings support the emerging role of individualized exercise training in selected HCM patients, further larger and longer-term studies are warranted to better define the clinical implications of these adaptations.
Strengths and Limitations
The present systematic review, meta-analysis, and meta-regression quantitatively synthesizes the available evidence regarding exercise training interventions in patients with HCM. By evaluating a broad range of functional, hemodynamic, imaging, and biomarker-related outcomes, our analysis provides an integrated perspective on clinically relevant variables associated with exercise tolerance, quality of life, and prognosis. Importantly, pooled within-group analyses and controlled between-group comparisons were consistently presented separately throughout the study, allowing a more balanced interpretation of the available evidence. In addition, the synthesis of current exercise modalities and training protocols provides a practical overview for clinicians and researchers involved in exercise prescription in HCM.
Nevertheless, this study is not exempt from limitations. First, the currently available evidence remains limited, with only three RCTs and relatively small sample sizes. Therefore, several findings, particularly those derived from meta-regression analyses, should be interpreted as exploratory and hypothesis generating. Moreover, analyses were based on aggregate study-level data rather than individual patient data, limiting the ability to adequately control for potential confounders and treatment interactions.
Clinical heterogeneity across studies also represents an important limitation. Inclusion criteria regarding LVOTO varied substantially, and obstructive status was not consistently reported, precluding subgroup analyses according to obstructive versus non-obstructive phenotypes. Differences in symptom severity, exercise modality, intervention duration, imaging methodologies, and medication use may also have influenced baseline physiological responses and training adaptations. In particular, beta-blockers and calcium channel blockers may substantially affect HR responses and exercise performance, although these variables could not be systematically controlled in the pooled analyses.
It is also important to acknowledge that the analyzed interventions included highly selected cohorts with predominantly mild phenotypes and low to moderate risk profiles capable of performing maximal CPET and participating in structured exercise programs. Therefore, generalization of these findings to higher-risk patients or unsupervised real-world exercise settings should be made cautiously.
Lastly, publication bias could not be formally assessed due to the limited number of studies, and some studies reported functional capacity in MET, requiring recalculation into mL kg⁻1 min⁻1.
Conclusion
Individualized, guided exercise training interventions appear to be a feasible short and mid-term option for low to moderate SCD-Risk HCM patients and were associated with reductions in BMI and improvements in functional capacity, exercise tolerance, cardiac adaptability, and chronotropic competence. Endurance and concurrent training elicited similar improvements in pVO2, while the addition of resistance exercise may provide further benefits on body composition and reduce myocardial work. Controlled data showed a small between-group reduction in MWT. Exploratory meta-regression analyses suggested that patients with lower baseline HRR may experience greater improvements in functional capacity, while patients with lower MWT and higher predicted pVO2 may show broader increments in HRR after training. No adverse events were reported in these cohorts participating in highly guided and mostly supervised exercise interventions. The studies included in this meta-analysis indicate that structured training programs lasting approximately three months or longer may be sufficient to induce positive adaptations. The long-term effects of exercise and the impact of the acute benefits in variables associated with long-term event-free survival remain unexplored.
Supplementary Information
Supplementary Material 1. Supplemental Table 1. PRISMA checklist. Supplemental Table 2. Systematic literature search equations and results. Supplemental Table 3. Domain-based assessment of the risk of bias of each study included according to the ROBINS-I V2 tool. Supplemental Table 4. TESTEX scale scores of the studies included in the meta-analysis and meta-regression. Supplemental Table 5. Eligibility and exclusion criteria, patient screening and selection, study completion and HCM Risk-SCD. Supplemental Table 6. Medications of the intervention and control groups in the studies included. Supplemental Table 7. Differences between pre- and post-intervention analyses in the exercise training and usual care groups, and between-group differences. Data are for three randomized controlled trials that included a control (usual care) group. Supplemental Table 8. Subgroup meta-analyses of the pre- to post-intervention differences between endurance-only and concurrent training. Supplemental Fig. 1. Exploratory funnel plots. Each dot represents an individual study group, and the vertical line represents the pooled effect estimate. Funnel plots are presented for descriptive purposes. Supplemental Methods. Data synthesis. Supplemental Results. Sensitivity analyses.
Acknowledgements
Not applicable.
Author contributions
AB, JG, and BB carried out conceptualization and investigation; AB and BB performed data curation and formal analysis; JG, MS, and BB were involved in funding acquisition, project administration, and supervision; AB contributed to methodology and writing—original draft; MS, FM, and BB provided resources; AB, JG, FM, MS, and BB did validation; JG, FM, MS, and BB were involved in writing—review and editing. All authors read and approved the final version.
Funding
All authors are supported by a research grant “Investigación en Cardiopatías Familiares y/o Genética cardiovascular Dr. William J. Mckenna” from the Spanish Society of Cardiology (SECSCFG-INV-CFG 24/02). Adrián Bayonas-Ruiz is supported by a pre-doctoral fellow contract at University of Murcia from the Spanish Ministry of Universities (FPU22/04352).
Data availability
The data underlying this article are available in this article and in its online supplementary material. The data can be also accessed in each individual study [15–22] .
Declarations
Competing interests
The authors have no financial or non-financial interests to disclosure and certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1. Supplemental Table 1. PRISMA checklist. Supplemental Table 2. Systematic literature search equations and results. Supplemental Table 3. Domain-based assessment of the risk of bias of each study included according to the ROBINS-I V2 tool. Supplemental Table 4. TESTEX scale scores of the studies included in the meta-analysis and meta-regression. Supplemental Table 5. Eligibility and exclusion criteria, patient screening and selection, study completion and HCM Risk-SCD. Supplemental Table 6. Medications of the intervention and control groups in the studies included. Supplemental Table 7. Differences between pre- and post-intervention analyses in the exercise training and usual care groups, and between-group differences. Data are for three randomized controlled trials that included a control (usual care) group. Supplemental Table 8. Subgroup meta-analyses of the pre- to post-intervention differences between endurance-only and concurrent training. Supplemental Fig. 1. Exploratory funnel plots. Each dot represents an individual study group, and the vertical line represents the pooled effect estimate. Funnel plots are presented for descriptive purposes. Supplemental Methods. Data synthesis. Supplemental Results. Sensitivity analyses.
Data Availability Statement
The data underlying this article are available in this article and in its online supplementary material. The data can be also accessed in each individual study [15–22] .