Objectives Fatty acid-binding protein (FABP3) expression is upregulated in aged muscles. We aimed to investigate the role of circulating FABP3 in muscle quantity and quality evaluated by ultrasound with an artificial intelligence-based (AI) system at the rectus femoris (RF) in patients with disease related malnutrition (DRM). Design and methods A total of 159 patients with DRM were enrolled. Muscle mass (quality and quantity) was evaluated using ultrasound of RF, supported by AI-based system. Additional assessments included bioimpedance measurements of skeletal muscle mass (SMM), appendicular SMM (aSMM), and the appendicular SMM index (aSMMI) and levels of FABP3. Results The cohort included 87 females and 72 males. The mean age was 64.1 ± 5.6 years. Sarcopenia was diagnosed in 55 patients (34.6%). Compared to non-sarcopenic individuals, patients with sarcopenia exhibited significantly lower values: phase angle (-0.9 ± 0.2° p = 0.01), reactance (-4.8 ± 1.8 ohms; p = 0.04), skeletal muscle mass (SMM) (-2.2 ± 0.4 kg; p = 0.02), appendicular skeletal muscle mass (aSMM) (-2.1 ± 0.1 kg; p = 0.03), appendicular skeletal muscle mass index (aSMMI) (-1.7 ± 0.3 kg/m² p = 0.02), RF muscle area (-0.5 ± 0.2 cm² p = 0.04), RF Y-axis diameter (-0.11 ± 0.1 cm; p = 0.03), pennation angle (-0.6 ± 0.2º p = 0.02), muscle strength (-8.2 ± 1.9 kg; p = 0.001), and calf circumference (-3.2 ± 0.1 cm; p = 0.02), albumin and prealbumin levels. MiT, FATiT and NMNFiT did not reach significant differences. Circulating concentrations of FABP3 were significantly higher in sarcopenic patients. Multivariate logistic regression analysis revealed a significant association between higher FABP3 levels and sarcopenia risk (OR = 2.1,95%CI:0.1.3–4.1; p = 0.03) and dynapenia risk (OR = 2.4,95%CI: 1.3–4.7; p = 0.02). FABP3 serum levels exhibited modest diagnostic accuracy for both sarcopenia and dynapenia (AUCs of 0.60 and 0.64, respectively). Conclusions Elevated FABP3 levels were associated with sarcopenia, reduced muscle strength, and impaired muscle quality in malnourished patients, using AI-assisted ultrasound evaluation of RF.
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Luis et al. (2026) studied this question.
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