DOI: 10.17116/profmed20262907183 ISSN: 2305-4948

A «portrait» of a patient with cerebrovascular pathology: a body composition and phenotypic clusters

M.M. Tanashyan, K.V. Antonova, N.E. Spryshkov, A.A. Panina

Cerebrovascular diseases (CVD) are associated with various metabolic risk factors. The critical role of visceral obesity in the context of vascular brain pathology underscores the need to transition from a purely body mass index (BMI)-based assessment to a phenotype-oriented evaluation. Objective. To delineate the clinical and phenotypic characteristics of patients with cerebrovascular diseases, while accounting for body composition, demographic details, and metabolic features. Materials and methods. This cross-sectional study included 307 participants: 205 with CVD and 102 subjects without CVDs. All subjects underwent a series of clinical and laboratory assessments, alongside a comprehensive body composition analysis. Results. The findings revealed that patients with CVD exhibited a higher prevalence of obesity and other vascular risk factors. Notable alterations in body composition were associated with increased visceral fat area and decreased phase angle values. Three distinct phenotypes of CVD patients were identified: the first phenotype predominantly consisted of women exhibiting overweight and grade I obesity, a high prevalence of abdominal obesity (AO), and a history of strokes. The second phenotype primarily included men with chronic CVDs, presenting with grade II—III obesity, maximum visceral fat area values, and notable metabolic disorders. The third phenotype, mostly represented by men, was characterized by normal body weight or mild overweight, lacking severe obesity as determined by BMI; however, these individuals displayed a high prevalence of AO, existing vascular risk factors, and chronic CVDs. Conclusion. Cerebrovascular diseases are closely linked with significant metabolic comorbidities, predominantly visceral obesity. A thorough evaluation of body composition helps identify phenotypic diversity among patients with these conditions and underscores the limitations of using BMI as a universal obesity marker.

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