Unsupervised Clustering of Intradialytic Blood Pressure Patterns and Their Associations With Body Composition in Patients Undergoing Chronic Hemodialysis.

Abstract

Background: Intradialytic blood pressure (BP) abnormalities are common in patients undergoing chronic hemodialysis (HD), however, their relationship with body composition remains unclear. We investigated the association between intradialytic BP patterns and body composition using an unsupervised clustering approach.

Methods: Adult outpatients receiving chronic HD who underwent segmental multifrequency bioelectrical impedance analysis were included. Systolic blood pressure (SBP) trajectories during HD were mapped to prespecified 30-minute time points from 0 to 240 minutes, and changes relative to predialysis SBP were clustered using k-means clustering. Body composition parameters were compared across BP clusters. Linear mixed-effects models with a random intercept for patient identifier were used to account for repeated HD sessions.

Results: Among 928 HD sessions from 179 patients, three SBP patterns were identified: marked decreasing (16.8%), mild decreasing (46.2%), and rising (37.0%) patterns. Body mass index did not differ across clusters. However, fat-free mass index and skeletal muscle mass index increased from the marked decreasing to the mild decreasing and rising clusters, whereas percent body fat decreased. The extracellular water-to-total body water ratio was highest in the rising cluster, and visceral fat area showed a decreasing trend from the marked decreasing cluster to the rising cluster. These associations remained significant after adjustment. Similar findings were observed in sensitivity analyses.

Conclusion: Unsupervised clustering identified reproducible intradialytic BP phenotypes that closely associated with volume status and body composition in patients undergoing chronic HD.