Impact of blood pressure control on left ventricular hypertrophy regression: a one-year retrospective study at a Military Hospital in Meknes, Morocco

¹Service de Cardiologie, Hôpital Militaire Moulay Ismail, Meknes, Morocco

^&Corresponding author
Sara Aouame, Service de Cardiologie, Hôpital Militaire Moulay Ismail, Meknes, Morocco

Introduction    

Hypertension is a major cardiovascular risk factor, affecting over one billion adults worldwide. One of its most deleterious cardiac complications is left ventricular hypertrophy (LVH), an adaptive myocardial response to sustained pressure overload that becomes structurally and prognostically detrimental. Left ventricular hypertrophy is a powerful independent predictor of myocardial infarction, heart failure, arrhythmia, and sudden death, doubling to quadrupling the associated cardiovascular risk [1,2]. The pathophysiology of LVH involves myocyte hypertrophy, increased interstitial tissue, and progressive myocardial fibrosis [3]. This fibrosis drives diastolic stiffness, conduction disturbances, and worsening prognosis. Importantly, LVH is reversible: numerous studies have demonstrated that effective blood pressure control can induce regression, or even normalization, of left ventricular mass [4]. This regression is associated with decreased fibrosis, improved diastolic function, and a significant reduction in cardiovascular event risk [5]. International guidelines have progressively lowered blood pressure targets, particularly for high-risk patients, recognizing the importance of optimal control for target organ protection [6]. However, in real-life settings, the degree of LVH regression and its determinants remain subjects of active investigation. The respective roles of different antihypertensive drug classes, the impact of comorbidities such as type 2 diabetes, and the optimal blood pressure level to achieve maximal regression are clinically important questions that require further real-world evidence. This study aimed to evaluate the impact of blood pressure control on LVH regression over a one-year period in patients with hypertension, and to identify the clinical and therapeutic factors independently associated with significant LVH regression.

Methods     

Study design and setting: we conducted a retrospective, observational, single-center study at the Cardiology Department of the Military Hospital Moulay Ismail, Meknes, Morocco, over a three-year period (January 2020 - December 2023). This hospital serves as a tertiary referral center for cardiovascular disease in the Meknes region.

Study population: we consecutively included 400 adult patients (age > 18 years) followed for essential hypertension and presenting with documented LVH on echocardiography at baseline. Patients with secondary hypertension, established ischemic heart disease (history of myocardial infarction or revascularization), significant valvular disease, or primary cardiomyopathy were excluded. No formal sample size calculation was performed for this retrospective analysis; all eligible patients during the study period were included.

Data collection: data were extracted from electronic medical records. At baseline (T0) and after one year of follow-up (T1), the following parameters were systematically collected: demographic and clinical data (age, sex, body mass index (BMI), smoking status, type 2 diabetes, dyslipidemia, chronic kidney disease [60 mL/min/1.73 m² >eGFR < 60 mL/min/1.73 m²]); clinic blood pressure measurements performed according to standard recommendations; antihypertensive treatment classes prescribed (RAS blockers [ACE inhibitors or ARBs], beta-blockers, calcium channel blockers, diuretics, mineralocorticoid receptor antagonists); and echocardiographic parameters (left ventricular mass (LVM) calculated by the Devereux formula, indexed to body surface area [LVMi]).

Definitions: left ventricular hypertrophy was defined as LVMi > 115 g/m² in men and > 95 g/m² in women, per ASE/EACVI recommendations [7]. Significant LVH regression was defined as a relative decrease in LVMi of more than 10% between T0 and T1. Optimal blood pressure control was defined as BP < 140/90 mmHg (or < 130/80 mmHg for patients with high cardiovascular risk under 65 years, per 2023 ESH guidelines [6]). Type 2 diabetes was defined using standard diagnostic criteria.

Statistical analysis: statistical analyses were performed using SPSS software (version 26.0, IBM Corp., Armonk, NY, USA). Continuous variables are expressed as mean ± standard deviation and categorical variables as frequencies and percentages. Comparisons between patients with and without LVH regression used Student´s t-test for continuous variables and Chi-squared test for categorical variables. Univariable logistic regression was first performed to screen all candidate predictors of LVH regression. Variables with p < 0.10 in univariable analysis were then entered into a multivariable logistic regression model using a forward stepwise approach, adjusted for age, sex, BMI, and baseline LVMi. Results are expressed as adjusted odds ratios (aOR) with 95% confidence intervals (CI). A two-tailed p-value < 0.05 was considered statistically significant.

Ethical considerations: this study was approved by the Institutional Ethics Committee of the Military Hospital Moulay Ismail, Meknes, Morocco (reference number: HMMIM-2020-EC-07). All patients provided written informed consent before inclusion. Data were anonymized before analysis in compliance with national data protection regulations.

Results     

Population characteristics: the mean age was 62 ± 11 years; 58% of patients were male. Common comorbidities included type 2 diabetes (30%), dyslipidemia (45%), and obesity (BMI > 30 kg/m², 35%). At baseline, mean blood pressure was 155/95 mmHg and mean LVMi was 128 ± 18 g/m². Baseline characteristics are summarized in Table 1.

Blood pressure control and LVH regression: after one year of follow-up, mean blood pressure decreased from 155/95 mmHg to 132/82 mmHg. A total of 260 patients (65%) achieved optimal blood pressure control. Significant LVH regression (decrease in LVMi > 10%) was observed in 220 patients (55%). Mean LVMi decreased from 128 ± 18 g/m² to 110 ± 15 g/m² (p < 0.001).

Factors associated with LVH regression: in univariable analysis, LVH regression was significantly associated with better blood pressure control, use of a RAS blocker, lower baseline LVMi, and absence of type 2 diabetes. In multivariable logistic regression, after adjustment for age, sex, BMI, and baseline LVMi, three factors remained independently associated with LVH regression: magnitude of systolic blood pressure reduction (per 5 mmHg decrease: aOR 1.25, 95% CI: 1.15-1.35; p < 0.001), use of a RAS blocker (aOR 2.1, 95% CI: 1.4-3.1; p < 0.001), and absence of type 2 diabetes (aOR 1.8, 95% CI: 1.2-2.7; p = 0.004). Full results of univariable and multivariable logistic regression are presented in Table 2.

Discussion     

This study aimed to evaluate the impact of blood pressure control on LVH regression over one year in patients with hypertension, and to identify its independent determinants. Our principal findings are that 65% of patients achieved optimal blood pressure control and 55% experienced significant LVH regression. In multivariable analysis, three factors independently predicted LVH regression: the magnitude of systolic blood pressure reduction, use of a RAS blocker, and absence of type 2 diabetes. Our finding that each 5 mmHg reduction in systolic blood pressure was independently associated with a 25% increase in the odds of LVH regression reinforces the concept that every millimeter of mercury counts for target organ protection. The SPRINT trial demonstrated that an intensive systolic blood pressure target of < 120 mmHg reduced cardiovascular events and mortality [8], and a SPRINT substudy showed significantly greater LVMi regression in the intensive treatment group [9]. However, recent guidelines advocate individualized blood pressure targets, recommending < 130/80 mmHg for most patients under 65 years while adopting a more cautious approach in elderly or frail individuals, where aggressive lowering may increase the risk of hypotension, syncope, and acute renal failure [6,10].

The identification of RAS blockers as an independent predictor of LVH regression is consistent with established pathophysiology and large meta-analyses [11,12]. Beyond their antihypertensive effect, ACE inhibitors and ARBs exert direct antifibrotic and antihypertrophic actions on the myocardium by inhibiting the profibrotic effects of angiotensin II and aldosterone, including down-regulation of TGF-β1 [13,14]. Emerging agents, including angiotensin receptor-neprilysin inhibitors (ARNIs) such as sacubitril/valsartan and mineralocorticoid receptor antagonists (MRAs) such as spironolactone, further extend the antifibrotic therapeutic armamentarium [15,16]. The negative impact of type 2 diabetes on LVH regression is a clinically important and mechanistically grounded finding. Chronic hyperglycemia and insulin resistance promote myocardial fibrosis through mechanisms largely independent of blood pressure, including formation of advanced glycation end-products, activation of the polyol pathway, oxidative stress, and protein kinase C activation [17,18]. The resulting “stiff heart” phenotype, characteristic of diabetic cardiomyopathy, renders the myocardium less compliant and less capable of structural regression even when blood pressure is adequately controlled. This underscores the need for strict glycemic control and early antifibrotic treatment in patients with both hypertension and type 2 diabetes.

Left ventricular hypertrophy regression should be viewed not merely as an anatomical goal but as a validated surrogate of improved cardiovascular prognosis. A major meta-analysis demonstrated that each 10% reduction in LVMi is associated with a 22% reduction in cardiovascular event risk [5]. Functional improvements accompanying regression include improved diastolic function, increased global longitudinal strain, and reduction in left atrial volume. Cardiac magnetic resonance imaging (MRI) with T1 mapping and extracellular volume (ECV) quantification now offers the most sensitive non-invasive assessment of diffuse myocardial fibrosis, and emerging data suggest that ECV reduction may be an even more powerful prognostic marker than LVM regression alone [19]. This study has several limitations that should be acknowledged. The retrospective single-center design limits generalizability to other populations and settings. The absence of ambulatory blood pressure monitoring may have introduced measurement variability. Cardiac MRI was not performed, precluding fibrosis quantification. The study period of three years and the absence of a formal sample size calculation are additional limitations. Despite these limitations, the large number of consecutively included patients, the standardized echocardiographic protocol, and the rigorous multivariable statistical analysis are notable strengths of this work.

Conclusion     

Blood pressure control is the primary driver of LVH regression, with 55% of patients achieving significant regression after one year of antihypertensive treatment. Renin-angiotensin system blocker use and absence of type 2 diabetes are independent predictors of this regression. Indexed left ventricular mass should be systematically monitored as a modifiable therapeutic target in patients with hypertension, providing a clinically meaningful marker of treatment success and long-term cardiovascular risk reduction.

Competing interests     

The author declare no competing interests.

Authors' contributions     

Conception and study design: Sara Aouame. Data collection: Sara Aouame. Data analysis and interpretation: Sara Aouame. Manuscript drafting: Sara Aouame. Manuscript revision: Sara Aouame. Guarantor of the study: Sara Aouame. The author have read and agreed to the final manuscript.

Tables     

Table 1: baseline characteristics of the study population (n = 400)

Table 2: univariable and multivariable logistic regression analysis of factors associated with LVH regression

References