Background and Objectives: This study aimed to investigate the association between circulating monocyte subset profiles and carotid artery stenosis (CAS) severity and to examine their relationships with inflammatory and atherosclerosis-related parameters. Materials and Methods: This cross-sectional study included 73 adult patients who underwent carotid Doppler ultrasonography. Participants were classified according to internal CAS severity as <50% (n = 44) or ≥50% (n = 29). Monocyte subsets were analyzed using flow cytometry and categorized as classical (CD14++CD16−), intermediate (CD14++CD16+), and non-classical (CD14+CD16++) monocytes. Serum MCP-1 concentrations were measured using an enzyme-linked immunosorbent assay. Clinical characteristics, biochemical parameters, inflammatory indices, and carotid intima–media thickness (cIMT) were compared between the groups. Multivariate logistic regression analyses were performed to identify independent associations with significant stenosis. Results: Patients with CAS ≥50% exhibited significantly higher classical monocyte percentages and lower non-classical monocyte percentages than those with CAS < 50% (p = 0.044 and p = 0.027, respectively). Intermediate monocyte percentages did not differ significantly between the groups. Significant stenosis was also associated with a higher white blood cell count, neutrophil count, systemic inflammatory response index, fibrinogen, and HbA1c levels. Non-classical monocyte percentages showed a significant inverse correlation with cIMT (r = −0.320, p = 0.006). In a multivariable model adjusted for age, sex, and systolic blood pressure, lower non-classical monocyte percentage was associated with significant CAS (OR 0.872, 95% CI 0.765–0.994; p = 0.040). However, this association was no longer statistically significant after further adjustment for fibrinogen, neutrophil count, and HbA1c, whereas fibrinogen remained independently associated with significant CAS. Conclusions: Lower circulating non-classical monocyte percentages were associated with significant CAS and inversely correlated with cIMT and inflammatory markers. However, the attenuation of this association after adjusting for inflammatory parameters suggests that monocyte subset distribution should be interpreted within the broader inflammatory context that accompanies advanced carotid atherosclerosis.

Background: Sarcopenia is an increasingly recognized complication of chronic kidney disease (CKD), contributing to impaired physical function and higher mortality. While most evidence derives from elderly populations, its frequency and inflammatory correlates in younger adults remain underexplored. This study aimed to investigate the prevalence of sarcopenia and its association with inflammatory markers in a non-geriatric CKD cohort, including both hemodialysis and non-dialysis patients. Methods: This cross-sectional observational study included 128 non-geriatric CKD patients (18–65 years), 60 of whom were on maintenance hemodialysis. Sarcopenia was diagnosed according to EWGSOP2 criteria using handgrip strength, bioelectrical impedance analysis, and 4-meter gait-speed testing. Serum interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) were measured by ELISA, while C-reactive protein (CRP) served as another inflammatory marker. SPSS v27.0 was used for statistical analysis. Results: Sarcopenia was confirmed in 21.9% of the cohort, with a significantly higher prevalence among hemodialysis patients (31.7% vs 13.2%, P < .05). The prevalence of sarcopenia increased progressively with advancing CKD stage in the overall cohort (P < .05). Dialysis status was the most consistent independent predictor of sarcopenia (fully adjusted OR = 8.28, P = .004). IL-6 ≥ 110 ng/L and TNF-α > 150 ng/L were associated with higher sarcopenia prevalence and lower appendicular skeletal muscle mass, respectively (P < .05). Conclusion: Sarcopenia is highly prevalent among non-geriatric CKD patients and increases with disease progression. Dialysis remains the strongest independent predictor, while elevated IL-6 and TNF-α levels reflect inflammation-related muscle loss.