Physical Function Phenotypes in Chronic Kidney Disease: A Hierarchical Cluster Analysis

作者：Jinhee Jeong, K. Mammino, Xiangqin Cui, J. Sabino-Carvalho, M. Zanuzzi, Melissa J. McGranahan, Joe R Nocera, Jeanie Park · 发表于：Physiology · 年份：2026 · DOI：10.1152/physiol.2026.41.s1.2300103

Background: Poor physical function is common in chronic kidney disease (CKD) and is associated with adverse outcomes; however, patterns of impairment are heterogeneous, and underlying mechanisms remain poorly understood. Traditional single-variable classification approaches may not fully capture this heterogeneity, potentially missing distinct at-risk subgroups. Hypothesis: We hypothesized that pattern-based phenotyping would identify clinically meaningful subgroups with different physiological profiles. Methods: Patients with CKD stage 3-4 (n=72, 62± 9 yr, 78% male, eGFR: 45±13 ml/min/1.73m 2 ) completed a 4-domain physical function assessment (handgrip strength, gait speed, chair-stand time, and static balance), body composition and volume status (extracellular water/total body water (ECW/TBW)) by bioimpedance, and vascular stiffness (pulse pressure, augmentation index (AIx). Hierarchical clustering was applied to z-standardized 4-domain for physical function scores to identify multi-variable patterns. Construct validity was evaluated through Spearman correlations and principal components analysis (PCA). To further characterize phenotypes, the associations between individual physical functional measures and clinical risk factors were assessed. Results: Three phenotype clusters emerged; 1) High-functioning (n=38, 53%, 60± 9 yr, 18% female) demonstrated better performance across all functional domains compared to other clusters (p< 0.05); 2) Lower-limb Mobility Impairment (...