Body composition of metabolically unhealthy normal-weight patients with aortic stenosis: a prospective cohort study

BMC Cardiovasc Disord. 2024 Dec 23;24(1):739. doi: 10.1186/s12872-024-04400-1.

Abstract

Background: The aim of this study was to evaluate the prognostic impact of computed tomography (CT)-based body composition parameters in metabolically unhealthy normal-weight patients (MUHNW) with aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR).

Methods: This prospective cohort study involved adults with normal weight scheduled for TAVR. Patients were divided into two groups: metabolically healthy normal-weight (MHNW) and MUHNW. The primary outcome was major adverse cardiovascular events (MACEs), and the secondary outcomes were all-cause mortality and prolonged hospital stay. Logistic regression was used to explore the relationships between variables and outcomes, and Cox regression models were applied to examine the effects of different parameters on patient prognosis. Incremental discriminative improvement (IDI) and the C-index were used to determine the influence of hybrid parameters on the predictive efficiency of the model.

Results: The cohort study included 182 patients divided into two groups: MHNW metabolically healthy normal-weight (n = 97) and MUHNW (n = 85). Over a median follow-up of 0.8 years, multivariable logistic regression analysis revealed significant associations of the skeletal muscle index (SMind) (HR: 0.50, 95% CI: 0.29 - 0.84, p = 0.01), subcutaneous adipose tissue index (SATind) (HR: 0.63, 95% CI: 0.45 - 0.88, p = 0.01), and visceral adipose tissue index (VATind) (HR: 1.34, 95% CI: 1.10 - 1.63, p < 0.01) with the risk of experiencing MACEs, whereas epicardial adipose tissue (EAT) was not significantly associated with the risk of experiencing MACEs in the multivariable model (HR: 1.10, 95% CI: 0.97 - 1.24, p = 0.14). For the primary outcome, adjusted for significant covariates, the model had an IDI of 0.25 and a C-index of 0.8, with significant associations of SMind (HR: 0.73, 95% CI: 0.62 - 0.87, p < 0.01), SATind (HR: 0.87, 95% CI: 0.78 - 0.97, p = 0.01), and VATind (HR: 1.25, 95% CI: 1.12-1.40, p < 0.01) with the risk of experiencing MACEs. For the secondary outcome, the model had an IDI of 0.36 and a C-index of 0.93, with EAT showing a significant protective effect against all-cause mortality and prolonged hospital stay (HR: 0.97, 95% CI: 0.93 - 0.99; p = 0.04).

Conclusions: Body composition parameters, including, VATind, SMind, and SATind, are significant predictors of MACEs in patients undergoing TAVR. Additionally, EAT shows a significant protective effect against all-cause mortality and prolonged hospital stay. These findings highlight the potential importance of comprehensive body composition assessments in the risk stratification and management of AS patients.

Keywords: Aortic stenosis; Body composition; Computed tomography; Metabolically unhealthy.

MeSH terms

  • Adiposity
  • Aged
  • Aged, 80 and over
  • Aortic Valve / diagnostic imaging
  • Aortic Valve / physiopathology
  • Aortic Valve / surgery
  • Aortic Valve Stenosis* / diagnostic imaging
  • Aortic Valve Stenosis* / mortality
  • Aortic Valve Stenosis* / physiopathology
  • Aortic Valve Stenosis* / surgery
  • Body Composition
  • Female
  • Humans
  • Length of Stay
  • Male
  • Predictive Value of Tests
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Time Factors
  • Transcatheter Aortic Valve Replacement* / adverse effects
  • Transcatheter Aortic Valve Replacement* / mortality
  • Treatment Outcome