Impact of metabolic syndrome on cardiac function and myocardial fibrosis in hypertrophic obstructive cardiomyopathy following septal myectomy assessed by cardiac magnetic resonance

Introduction

Hypertrophic cardiomyopathy (HCM) is one of the most common inherited myocardial diseases, is characterized by myocardial hypertrophy, and has a reported prevalence of 1:500 to 1:200 (1,2). Hypertrophic obstructive cardiomyopathy (HOCM), the predominant phenotypic variant of HCM, is characterized by asymmetric left ventricular (LV) hypertrophy, dynamic left ventricular outflow tract obstruction (LVOTO), and concomitant mitral regurgitation (MR) (3). These pathological features drive disease progression and are associated with major adverse outcomes, including heart failure, arrhythmias, and sudden cardiac death (4). Recent advances in therapeutic interventions have significantly alleviated the symptoms and improved the prognosis of patients with HCM. For HOCM patients with severe symptoms that are refractory to medical therapy, septal myectomy (SM) remains the gold-standard treatment (5). A novel surgical approach—transapical beating-heart septal myectomy (TA-BSM)—has recently been developed, which allows for precise septal resection under real-time visualization, without the need for cardiopulmonary bypass (6). This approach has demonstrated promising perioperative safety and reduced procedural risk in early clinical applications (7).

Growing evidence suggests that metabolic abnormalities adversely affect left atrial (LA) and ventricular function in HCM patients, thereby exacerbating cardiovascular risk (8-10). Metabolic syndrome (MetS) is a global epidemic and a major public health concern, characterized by a cluster of metabolic abnormalities including abdominal obesity, hypertension, dyslipidemia, and impaired glucose metabolism (11,12). Despite evidence linking MetS to the progression of HCM, its impact on myocardial recovery and reverse remodeling following surgical intervention in HOCM patients remains poorly understood.

Cardiac magnetic resonance (CMR) has emerged as the gold-standard non-invasive imaging modality in contemporary cardiology for comprehensively evaluating cardiac anatomy, function, perfusion, and tissue characteristics (13). Its ability to non-invasively quantify fibrosis via late gadolinium enhancement (LGE) and T1 mapping, combined with myocardial strain analysis via CMR tissue tracking, provides critical insights into disease severity, therapeutic response, and patient prognosis (14,15).

This study aimed to investigate the impact of MetS on myocardial fibrosis and left heart function in HOCM patients after SM using CMR, and to identify predictors of postoperative myocardial recovery and reverse remodeling to guide individualized management strategies. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1631/rc).

Methods

Study population

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Tongji Hospital (IRB No. TJ-IRB20230914). The requirement of written informed consent was waived due to the retrospective nature of the study and the anonymized data collection.

Between April 2022 and December 2024, we consecutively screened HOCM patients who underwent TA-BSM with pre- and postoperative CMR examinations at Tongji Hospital (Figure 1). HCM was diagnosed according to the 2024 American Heart Association (AHA)/American College of Cardiology (ACC) guideline (16) as a maximum end-diastolic ventricular wall thickness of ≥15 mm in adults without another identifiable cause of hypertrophy, or a wall thickness of 13–14 mm in those with a family history of HCM or a known pathogenic sarcomere gene mutation. The indications for TA-BSM were as follows: (I) severe symptoms despite optimal medical therapy; and (II) resting or provoked left ventricular outflow tract gradient (LVOTG) ≥50 mmHg. The exclusion criteria were as follows: (I) suboptimal CMR quality due to arrhythmia or respiratory artifacts; (II) missing baseline or follow-up data; (III) postoperative adverse events; (IV) age younger than 18 years; (V) prior cardiac interventions of alcohol septal ablation, radiofrequency ablation, valve replacement, pacemaker implantation, or cardiac surgery; and/or (VI) concomitant severe coronary heart disease, valvular disease, or other cardiomyopathies. After the exclusion criteria were applied, a total of 305 HOCM patients were enrolled in the study.

Figure 1 Flow diagram of the study. CMR, cardiac magnetic resonance; HOCM, hypertrophic obstructive cardiomyopathy; MetS, metabolic syndrome; TA-BSM, transapical beating-heart septal myectomy.

According to the 2009 Joint Interim Statement by the International Diabetes Federation Task Force on Epidemiology and Prevention and collaborating bodies, a clinical diagnosis of MetS is confirmed when at least three of the following five criteria are met (12): (I) elevated waist circumference, using population- and country-specific thresholds; (II) elevated triglycerides (TG) [≥150 mg/dL (1.7 mmol/L)] or specific treatment for hypertriglyceridemia; (III) reduced high-density lipoprotein cholesterol (HDL-c) [<40 mg/dL (1.0 mmol/L) in males; < 50 mg/dL (1.3 mmol/L) in females] or specific treatment for this lipid abnormality; (IV) elevated blood pressure [systolic blood pressure (SBP) ≥130 mmHg and/or diastolic blood pressure (DBP) ≥85 mmHg] or anti-hypertensive drug treatment for a patient with a history of hypertension; and (V) elevated fasting blood glucose (FBG) [>100 mg/dL (5.6 mmol/L)] or a history of type 2 diabetes mellitus (T2DM). When waist circumference was unavailable, a body mass index (BMI) >25 kg/m² served as a surrogate criterion for MetS diagnosis (17,18). Ultimately, 305 patients were enrolled in the study, of whom 185 were assigned to the HOCM (MetS−) group and 120 were assigned to the HOCM (MetS+) group.

We extracted comprehensive clinical data from patients’ digital medical records, including demographic characteristics (age and sex), lifestyle factors (smoking history and alcohol consumption), comorbidities [hypertension, T2DM, and atrial fibrillation (AF)], biochemical parameters [FBG, glycated hemoglobin (HbA1c), serum lipid levels, N-terminal pro-brain natriuretic peptide (NT-proBNP), and cardiac troponin T (cTnT)], physiological measurements [BMI, SPB, DBP, and heart rate (HR)], renal function [estimated glomerular filtration rate (eGFR)], as well as symptom profiles and complete medical histories. Hypertension was defined as SBP ≥140 mmHg and/or DBP ≥90 mmHg at rest on ≥ two occasions, or the use of anti-hypertensives (19). T2DM was diagnosed according to the American Diabetes Association standards outlined in the 2024 Standards of Care in Diabetes (20). Additionally, the triglyceride-glucose (TyG) index was calculated as follows: TyG index = Ln [fasting TG (mg/dL) × fasting glucose (mg/dL)/2] (21).

Echocardiographic data

Transthoracic echocardiography was performed preoperatively and during follow-up by a single experienced sonographer using GE Vivid E95 (M5Sc transducer; GE Healthcare, Chicago, IL, USA) with a standardized protocol (22). The key parameters included: LVOTG (measured via continuous-wave Doppler); MR severity (graded 1–3; 1: none/mild; 2: moderate; 3: severe); and systolic anterior motion (SAM) (binary assessment: present/absent). LV diastolic function was assessed using two crucial ratios (23): the ratio of early diastolic mitral inflow velocity to diastolic mitral annulus velocity (E/e’), and the ratio of peak early (E) to late (A) diastolic mitral inflow velocities (E/A).

CMR scanning protocol

All CMR examinations were performed on a 3.0 T scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany). The imaging protocol included balanced steady-state free precession cine sequences, native/post-contrast T1 mapping, T2 mapping, and LGE imaging (Appendix 1).

CMR image analysis

All CMR images were analyzed using CVI42 software (version 5.14.0, Circle Cardiovascular Imaging, Calgary, Canada) by two experienced radiologists who were blinded to the patients’ clinical information. Representative examples are presented in Figure 2.

Figure 2 Measurement of LV strain, LA strain, and LV tissue characteristics. LV strain was assessed by delineating endocardial and epicardial borders at end-diastole in short-axis (A) and two-, three-, and four-chamber long-axis views (B-D). LA strain was assessed from two- and four-chamber views (E,F). (G) LV global strain-time curve; (H,I) LA strain-time and strain rate-time curves; (J) pre-contrast T1 map; (K) ECV map; (L) LGE image. ECV, extracellular volume; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; LA, left atrial; LGE, late gadolinium enhancement; LV, left ventricular; SRa, peak late negative strain rate; SRe, peak early negative strain rate; SRs, peak positive strain rate; εa, active strain; εe, passive strain; εs, total strain.

LV volume and function: LV endocardial and epicardial borders were automatically delineated and manually adjusted on short-axis cine images at end-systole and end-diastole, excluding trabeculations and papillary muscles. The following parameters were derived: left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), stroke volume (SV), cardiac output (CO), left ventricular mass (LVM), and left ventricular maximum wall thickness (LVMWT). The Mosteller formula was used to calculate body surface area (BSA). Subsequently, partial LV parameters were standardized and corrected to yield the following indexed parameters: left ventricular end-diastolic volume index (LVEDVI), left ventricular end-systolic volume index (LVESVI), stroke volume index (SVI), cardiac index (CI), and left ventricular mass index (LVMI). Global radial strain (GRS), global circumferential strain (GCS), and global longitudinal strain (GLS) were computed using the tissue tracking module. Peak global diastolic strain rates (PDSRs) in corresponding directions [i.e., the radial diastolic strain rate (RDSR), circumferential diastolic strain rate (CDSR), and longitudinal diastolic strain rate (LDSR)] were also computed. The left ventricular remodeling index (LVRI) was calculated as the ratio of LVM to LVEDV (LVRI = LVM/LVEDV) (24). The left ventricular global function index (LVGFI) was calculated using the following formula: (25)

LVGFI=(LVSVLVEDV+LVESV2+LVM1.05)×100%[1]

LA volume and function: LA volumes and phasic functions were evaluated using the biplane area-length method from two- and four-chamber cine views. The contours of the endocardium and epicardium in the left atrium were automatically traced and manually corrected at end-diastole and end-systole. LA-GLS included total strain (εs; corresponding to atrial reservoir function), passive strain (εe; corresponding to atrial conduit function), and active strain (εa; corresponding to atrial contractile booster pump function). The corresponding strain rates were peak positive strain rate (SRs), peak early negative strain rate (SRe), and peak late negative strain rate (SRa). The left atrial anteroposterior diameter (LAAPD) was measured at the center of the LA body at end-systole on the three-chamber view. Volumetric indices of phasic LA function were obtained at LV end-systole [maximum left atrial volume (LAVmax)], just before LA contraction [passive left atrial volume (LAVbac)], and at the late LV end-diastole after LA contraction [minimum left atrial volume (LAVmin)]. LAVmax, LAVbac, and LAVmin were indexed to BSA. The left atrial emptying fractions (LAEFs) were calculated as follows (26):

TotalLAEF=LAVmax−LAVminLAVmax×100%[2]

PassiveLAEF=LAVmax−LAVbacLAVmax×100%[3]

BoosterLAEF=LAVbac−LAVminLAVbac×100%[4]

The left atrioventricular coupling index (LACI) was defined as the ratio of LA end-diastolic volume to LV end-diastolic volume, expressed as a percentage (27).

LGE quantification: LGE was performed by setting the signal intensity threshold at five standard deviations (SDs) above the mean intensity of a reference myocardium region without visible enhancement. The LGE extent was expressed as the percentage of the total LV mass.

T1/T2 mapping and ECV: LV endocardial and epicardial contours were automatically delineated and manually corrected on native T1 and T2 maps at three short-axis levels (basal, middle, and apical). Regions of interest were manually drawn in the intracavitary blood pool of the left ventricle, avoiding papillary muscles and trabeculae. These T1 map delineations were subsequently copied onto corresponding post-contrast T1 maps with stringent adjustments applied to avoid artifacts. Extracellular volume (ECV) fraction measurements were derived from the following formula:

ECV=(1−Hematocrit)×(1T1myopost−1T1myonative1T1bloodpost−1T1bloodnative)[5]

Hematocrit was collected at each study visit.

Intra- and inter-observer reproducibility analysis

To assess intra-observer variability, one investigator repeated measurements of myocardial strain and fibrosis parameters in 20 randomly selected cases after a one-month interval. Inter-observer variability was evaluated by comparing these results with independent measurements performed by a second blinded investigator on the same dataset.

Statistical analysis

The statistical analyses were performed in SPSS (version 29.0.1.0, IBM, Armonk, NY, USA). Graphs were generated using GraphPad Prism (version 10.2.0, GraphPad Software, San Diego, CA, USA). The continuous variables were presented as the mean ± SD for normally distributed data or as the median with the interquartile range (IQR) for non-normally distributed data. The categorical variables were presented as the frequency and percentage and were compared using the chi-squared test or Fisher’s exact test. Comparisons between the MetS(+) and MetS(−) groups were performed using independent samples t-tests for normally distributed variables and Mann–Whitney U tests for non-normally distributed variables. For comparisons between the preoperative and postoperative parameters, paired t-tests were used for normally distributed differences, while Wilcoxon signed-rank tests were employed for non-normally distributed variables. The change in each variable was denoted by the Delta value (Δ), calculated as follows: Δ = preoperative value − postoperative value. The rate of change was calculated as follows: rate of change = (Δ/preoperative value) × 100%. Myocardial recovery was assessed by the rate of change in GLS and LA strain after SM. Univariable and multivariable linear regression analyses were used to identify predictors of postoperative myocardial recovery. In the multivariable regression analyses, we adjusted for potential confounders, including sex, age, hypertension, hyperlipidemia, and AF. Variables with P values <0.1 in the univariable analysis were entered into the multivariable analysis, while those with a variance inflation factor >5 were excluded to avoid multicollinearity. The remaining variables were included in the multivariable analysis. The intraclass correlation coefficient (ICC) was used to assess the inter- and intra-observer reproducibility of myocardial strain and fibrosis parameters. A two-tailed P value <0.05 was considered statistically significant.

Results

Baseline characteristics

The baseline demographic and clinical characteristics of the study cohort are summarized in Table 1. A total of 305 patients (120 with MetS and 185 without MetS) were included in the study. Postoperative CMR was performed between 3.0 and 22.3 months after myectomy. Compared to the HOCM (MetS−) group, the HOCM (MetS+) group exhibited significantly higher BMI, SBP, FBG, HbA1c, TC, TG, LDL-c, and TyG index values (all P<0.05), whereas age, sex, DBP, HR, smoking and drinking history, eGFR, NT-proBNP, or cTnT did not differ significantly between the two groups. The HOCM (MetS+) group also had higher rates of hypertension, diabetes mellitus, hypercholesterolemia, and AF (all P<0.01), along with more severe clinical presentations. These included a greater proportion of patients with New York Heart Association (NYHA) class III/IV and moderate or severe MR, elevated LVOTG [70.5 (50.3, 109.0) vs. 66.0 (31.2, 99.5) mmHg, P=0.014], and increased septal E/e’ ratios [18.3 (14.3, 21.0) vs. 15.5 (11.8, 19.8), P=0.004].

Comparison of CMR-derived LV parameters

The LV functional and strain parameters are presented in Table 2. At baseline, the HOCM patients with MetS had significantly lower LVEF and LVGFI values, along with higher LVMWT, LVMI, LVESVI, and LVRI values (all P<0.05). There were no statistically significant differences in the LVEDVI, SVI, or CI values between the two groups (P>0.05). Regarding myocardial deformation, the patients with MetS demonstrated significantly impaired GRS and GLS, as well as reduced PDSRs in both radial and longitudinal directions (all P<0.05) (Figure 3). Further, baseline ECV and LGE values were higher in the MetS+ group (both P<0.05), while the native T1 and T2 values did not differ significantly between the two groups. Although most between-group differences in the LV parameters diminished postoperatively, the patients with MetS continued to exhibit larger LVRI, ECV, and LGE values, as well as lower LVGFI and GLS values. Representative CMR images of HOCM patients with and without MetS are shown in Figure 4.

Figure 3 Comparative analysis of LV global strains (A-C), LVRI (D), myocardial fibrotic parameters (E,F) and LA strains (G-I) between the HOCM (MetS+) group and HOCM (MetS−) group. ns, P≥0.05 (no significance); *, P<0.05; **, P<0.01; ***, P<0.001. ECV, extracellular volume; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; HOCM, hypertrophic obstructive cardiomyopathy; LA, left atrial; LGE, late gadolinium enhancement; LV, left ventricular; LVRI, left ventricular remodeling index; MetS, metabolic syndrome; εa, active strain; εe, passive strain; εs, total strain.

Figure 4 The representative CMR images of a HOCM (MetS−) patient and a HOCM (MetS+) patient. CMR, cardiac magnetic resonance; ECV, extracellular volume; HOCM, hypertrophic obstructive cardiomyopathy; LGE, late gadolinium enhancement; MetS, metabolic syndrome.

In the overall cohort, pre- to postoperative comparisons revealed significant reductions in the LVMWT, LVEF, SVI, CI, LVMI, and LVRI values (all P<0.001). The LVESVI increased significantly after surgery (P<0.001), whereas the LVEDVI showed no significant change (P=0.063). Postoperative changes in strain were component-specific. GLS improved from –13.2%±3.8% to –14.4%±5.6% (P<0.001), but GRS (28.8%±7.5% vs. 25.8%±6.7%, P<0.001) and GCS (–17.3%±3.3% vs. –15.7%±3.1%, P<0.001) decreased. Regarding diastolic function, the longitudinal PDSR improved, whereas the radial and circumferential PDSR declined (all P<0.05). Myocardial tissue characterization in the overall cohort revealed significant reductions in native T1, T2, and LGE postoperatively. The ECV increased from 30% (27–32%) to 31% (28–34%) (P<0.001), potentially reflecting residual diffuse fibrosis. Additional details are provided in Table S1.

Comparison of CMR-derived LA parameters

LA structural and functional parameters are shown in Table 3. At baseline, the MetS+ group exhibited significantly larger LAAPD, LAVI, and LACI values, along with reduced total LAEF, εs, and εe (all P<0.05). After surgery, most differences between groups were attenuated. However, the patients with MetS still showed higher LACI, larger LAVI, and lower εs and εe values than their non-MetS counterparts.

In the overall cohort, SM resulted in significant reductions in the LAAPD, LACI, LAVImax, LAVIbac, and LAVImin values (all P<0.001). Reservoir function improved postoperatively, as indicated by increases in the total LAEF, εs, and SRs values (P<0.001). Conduit function also improved, as evidenced by significant increases in the εe and SRe values (P<0.001), although passive LAEF did not change significantly. For the booster function, active LAEF, εa, and SRa improved significantly (P<0.05). Table S1 provides additional information.

Univariable and multivariable linear regression analyses of GLS and LA strains

Table S2 shows the univariable correlations of the rate of change in GLS and LA strains. In the overall cohort of HOCM patients, male sex, presence of MetS, and HDL-c were significantly associated with ΔGLS%. The presence of MetS and SBP were positively associated with Δεs%. FBG was negatively associated with Δεe%. No significant predictors of Δεa% were identified in either the univariable or multivariable analysis.

The multivariable analysis results are presented in Table 4. Multivariable linear regression analyses showed that the presence of MetS (β=0.264, P<0.001) and HDL-c (β=0.122, P=0.033) were independent predictors of ΔGLS%. For LA strain, MetS (β=0.135, P=0.030) independently predicted Δεs%.

Reproducibility of CMR parameters

As shown in Table S3, the intra- and inter-observer reproducibility for CMR-derived myocardial strain and fibrosis parameters was excellent. The ICCs ranged from 0.919 to 0.979 for intra-observer reproducibility, and from 0.883 to 0.975 for inter-observer reproducibility.

Discussion

The main findings of our study were as follows: (I) HOCM patients with MetS exhibited significantly worse LV function, as evidenced by lower LVEF, LV strain parameters, and LVGFI, along with increased LVRI and LVMI; (II) the myocardial fibrosis burden was significantly higher in the HOCM patients with MetS; (III) LA function was also impaired in the MetS+ group, which exhibited decreased total LAEF, LA εs, and εe, along with increased LAVI and LACI; (IV) MetS was identified as an independent predictor of diminished postoperative improvement in GLS and εs; and (V) lower HDL-c was independently associated with attenuated improvement in GLS. Our research indicated that MetS is associated with worse left heart function and incomplete postoperative myocardial recovery in HOCM patients, potentially increasing cardiovascular risk.

MetS comprises a cluster of interconnected metabolic factors that directly increase the risk of cardiovascular diseases and all-cause mortality (28). The pathophysiology of MetS involves insulin resistance (IR), central obesity, chronic inflammatory state, and neuroendocrine dysregulation (11,29). These factors contribute to structural and functional cardiac impairments through mechanisms such as cardiomyocyte hypertrophy and myocardial fibrosis, largely mediated by proinflammatory cytokines (e.g., tumor necrosis factor-α and interleukin-6) (29). MetS and IR increase the risk of incident HF in apparently healthy individuals and those with diabetes mellitus (30). Previous studies have similarly reported that metabolic disturbances can worsen cardiac function in HCM (8,31).

In our cohort, the HOCM patients with MetS demonstrated significantly worse baseline LV function, including reduced LVEF and LVGFI, and increased LVRI and LVMI. Myocardial strain analysis further confirmed impaired LV mechanics, as evidenced by decreased GRS, GLS, as well as corresponding diastolic strain rates. Regardless of MetS status, postoperative LVEF and SV showed decline but remained within the normal range, suggesting an adaptive remodeling process toward a more physiological state after relief of LVOTO. Conversely, GLS improved postoperatively, reflecting recovery of intrinsic myocardial contractile function at the myocardial fiber level. These findings underscore the detrimental effects of metabolic abnormalities on LV structure and function in HOCM, while highlighting the beneficial myocardial functional recovery following surgical relief of LVOTO.

Myocardial fibrosis burden—quantified by LGE and ECV—was significantly higher in the HOCM patients with MetS. The increased fibrosis burden may partly explain the limited improvement in myocardial deformation observed postoperatively. Fibrosis, a hallmark of HCM, is closely associated with diastolic dysfunction and impaired myocardial relaxation, even when LVEF is preserved (16). The pro-fibrotic milieu in MetS may involve renin-angiotensin-aldosterone system activation, advanced glycation end products accumulation, and mitochondrial dysfunction, further emphasizing the interplay between systemic metabolic abnormalities and myocardial tissue remodeling (29). After myectomy, LGE decreased, while ECV increased. Myocardial fibrosis often accompanies hypertrophy. Surgical resection removes hypertrophied tissue but inevitably leaves residual reparative scar tissue, which is difficult to distinguish from preexisting fibrosis on imaging. The observed reduction in LGE most likely reflects a greater extent of resected fibrotic myocardium relative to the newly formed scar tissue. ECV, derived from pre- and post-contrast T1 values using the blood pool as a reference, quantifies the proportion of extracellular matrix in the myocardium while minimizing intracellular influence. The relative postoperative increase in ECV likely reflects a disproportionate reduction in cellular components compared to the extracellular matrix, as suggested by a previous study (32).

MetS was also associated with significant LA dysfunction, as reflected by reduced LAEF, LA strains and strain rates, along with increased LAVI and LACI. These alterations reflect impaired atrial-ventricular coupling and diastolic dysfunction, and may contribute to a higher risk of AF (31). As observed in our cohort, AF was more prevalent among patients with MetS. A large meta-analysis involving more than 600,000 individuals showed that every 5-unit increment of BMI confers an additional 19–29% risk of incident AF, a 10% risk of postoperative AF, and a 13% risk of post-ablation AF (33). Chronic inflammation, hemodynamic overload, and metabolic derangements in MetS may lead to atrial fibrosis and remodeling. Importantly, LA dysfunction is closely associated with the prognosis of HCM following myectomy (34). Our findings underscore the importance of comprehensive metabolic and atrial function evaluation in surgical candidates. Future longitudinal studies are warranted to evaluate the impact of MetS on new-onset AF and adverse outcomes following SM.

Our findings demonstrate that MetS and its components are associated with adverse myocardial remodeling in HCM. Patients with MetS often show adverse cardiac remodeling and myocardial dysfunction, even in the absence of overt coronary artery disease or valvular abnormalities (31). HOCM patients with diabetes tend to be older, have more comorbidities, worse exercise tolerance, and more severe heart failure symptoms (10,35). Moreover, they face a higher risk of sudden cardiac death after myectomy (36). A mendelian randomization study suggested that genetic liability to IR, rather than glycemic levels, is associated with adverse changes in LV remodeling, highlighting IR as a potential driver of disease progression (37). Dyslipidemia, especially elevated TG and reduced HDL-c, has also been associated with a higher risk of HCM, particularly in younger individuals (38). Obesity is associated with increased myocardial mass and decreased native T1 in HCM patients, likely reflecting myocardial steatosis in addition to fibrosis (39). Moreover, subclinical myocardial remodeling has been observed in obese individuals regardless of metabolic health status (40).

Multivariable analyses revealed that MetS independently predicted less pronounced postoperative improvement in GLS and LA εs. Among the individual metabolic components, lower HDL-c levels were associated with a reduced improvement in GLS. These results suggest that both the presence of MetS and individual metabolic components significantly influence myocardial recovery and remodeling after surgery. Clinically, these observations support the need for individualized perioperative risk stratification and tailored metabolic management strategies. Early metabolic optimization, including through weight loss, glycemic control, and anti-inflammatory therapies, may enhance the efficacy of SM and improve long-term outcomes in this high-risk subgroup.

Limitations

Several limitations of this study should be acknowledged. First, it was a single-center, retrospective study, which may introduce selection bias, limit generalizability, and preclude causal inference, despite multivariable adjustment. Second, the absence of systematic genotyping prevented us from fully excluding the possibility that underlying genetic factors contribute to both a more severe HCM phenotype and a higher prevalence of MetS. Third, postoperative CMR follow-up was performed at variable time points, which may introduce heterogeneity in remodeling assessment. Fourth, although routine histological examination was performed on surgically resected myocardial specimens, quantitative assessment of fibrosis and formal correlation analyses with CMR-derived parameters were not conducted, precluding the histopathological validation of imaging findings. Finally, the absence of patients undergoing alternative septal reduction procedures (e.g., alcohol septal ablation or the transaortic Morrow procedure), together with the lack of long-term clinical outcomes, precluded direct comparison across therapeutic modalities, as well as correlation analyses between imaging changes and prognosis. Future prospective studies with standardized follow-up and comprehensive metabolic and genetic profiling are warranted to clarify the clinical impact of metabolic intervention in this population.

Conclusions

MetS is associated with worse left heart function and higher myocardial fibrosis in HOCM patients, and independently hinders myocardial recovery and reverse remodeling following SM. These findings underscore the importance of early and individualized metabolic management in HOCM patients. Future prospective studies are warranted to evaluate whether targeted metabolic interventions can translate into improved postoperative myocardial remodeling and clinical outcomes in this population.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1631/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1631/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1631/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by Institutional Review Board of Tongji Hospital (IRB No. TJ-IRB20230914). Informed consent was waived due to the retrospective nature of the study and the anonymized data collection.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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