Effects of a cardiometabolic intervention program in population at high cardiovascular risk. A Brazilian cohort.
M Linhares, C Passold, L B B dos Santos, R Z B Kaestner, L Stefanello, B F Bertotti, G GardenghiAbstract
Background
Cardiometabolic risk is associated with the chances of damage to the cardiovascular system when multiple factors occur together. These include visceral obesity, dyslipidemia, hypertension, insulin resistance, and inflammation, all aspects of the pathophysiology of cardiometabolic diseases. Pharmacological or non-pharmacological interventions aim to control and improve clinical stages.
Purpose
The aim of this study is to demonstrate the effect of a multidisciplinary care intervention focused on adjusting cardiometabolic risk factors in a population with a high cardiovascular risk profile.
Methods
This was a cohort study conducted in a specialized outpatient clinic (cardiologist, endocrinologist, nutritionist, and physical training guidance). Individuals underwent a systematic approach including laboratory tests, cardiovascular risk imaging, and bioimpedance analysis for body composition. Dietary patterns, metabolic activity, and pre-existing diseases were established. The protocol included diet (calorie restriction), protein supplementation, resistance training, and gradual drug treatment. After a cardiometabolic diagnosis, an intervention plan was developed with structured feedback and follow-up appointments every 90 days via an app and direct contact with the team. Follow-up lasted six months, with constant reassessments and adjustments. Statistical analysis used a one-way ANOVA (p≤0.05), with Scheffé's post-hoc test when necessary. Data are expressed as mean ± standard deviation.
Results
136 individuals were followed (age: 49.9±11.0 years, 58.1% male, weight: 100.5±16.2 kg). The initial prevalence of risk factors was: coronary artery disease: 31.1%, diabetes: 16.3%, hypertension: 40.7%, dyslipidemia: 85.9%. obesity: 80.1%, sedentary lifestyle: 70.7%. After six months, there was a decrease in BMI (pre: 34.1±4.5 kg/m² vs. post: 31.6±4.7 kg/m², p: 0.03). Bioimpedance showed a decrease in fat mass (pre: 37.7±8.1% vs. post: 33.7±8.3%, p: 0.01) and maintenance of lean mass (pre: 35.2±5.3% vs. post: 36.7±4.8%, p: 0.11). There was also a drop in abdominal circumference (pre: 111.0±12.6 cm vs. post: 103.2±11.1 cm, p: 0.00). LDL decreased (pre: 113.2±47.5 mg/dL vs. post: 77.7±42.2 mg/dL, p: 0.00). The same occurred with triglycerides (pre: 145.2±88.8 mg/dL vs post 96.7±53.0 mg/dL, p: 0.00). Glycated hemoglobin decreased (pre: 5.6±0.7% vs. post: 5.3±0.5%, p: 0.00). HDL showed no significant changes. Statins were used in 73.1% and GLP-1 agonists in 78.7% of the patients. In this subgroup of GLP-1 agonist users, the non-adherence rate was 32.7%.
Conclusion
A care program focused on cardiometabolism has a high potential to alter risk-associated parameters. Longer follow-up is needed to determine definitive adherence and event reduction.