Time-Specific Associations of Wearable, Sensor-Based Cardiovascular and Behavioral Readouts with Disease Phenotypes in the Outpatient Setting of the Chronic Renal Insufficiency Cohort (CRIC)

Abstract

AbstractPatients with chronic kidney disease (CKD) are at risk of developing cardiovascular disease. To facilitate out-of-clinic evaluation, we piloted wearable device-based analysis of heart rate variability and behavioral readouts in patients with CKD participating in the Chronic Renal Insufficiency Cohort and (n=49) controls. Time-specific partitioning of HRV readouts indicate higher parasympathetic nervous activity during the night (mean RR at night 14.4±1.9 ms versus 12.8±2.1 ms during active hours; n=47, ANOVA q=0.001). The α2 long-term fluctuations in the detrended fluctuation analysis, a parameter predictive of cardiovascular mortality, significantly differentiated between diabetic and non-diabetic patients (prominent at night with 0.58±0.2 versus 0.45±0.12, respectively, adj. p=0.004). Both diabetic and nondiabetic CKD patients showed loss of rhythmic organization compared to controls, with diabetic CKD patients exhibiting deconsolidation of peak phases between their activity and SDNN (standard deviation of interbeat intervals) rhythms (mean phase difference CKD 8.3h, CKD/T2DM 4h, controls 6.8h). This work provides a roadmap toward deriving actionable clinical insights from the data collected by wearable devices outside of highly controlled clinical environments.