Why the study?
Little is known about the prognostic value of continuous, out-of-clinic biometric monitoring of cardiovascular function in chronic kidney disease.
Do clinical factors like diabetes and proteinuria influence heart rate variability measured by wearable EKG devices in patients with chronic kidney disease?
Do clinical factors like diabetes and proteinuria influence heart rate variability measured by wearable EKG devices in patients with chronic kidney disease?
Wearable EKG monitoring in CKD patients reveals that diabetes and higher proteinuria are associated with significantly lower heart rate variability.
Should not yet change wearable HRV interpretation in CKD; hypothesis-generating for diabetes and proteinuria effects.
Little is known about the prognostic value of continuous, out-of-clinic biometric monitoring of cardiovascular function in chronic kidney disease (CKD). In this study, a mean (±SD) of 50.3 ± 9.3 h of EKG recordings from wearable BioPatch devices was collected from 458 participants across seven Chronic Renal Insufficiency Cohort centers. Multivariable linear regression showed that diabetes was associated with 7.4 ms lower Standard Deviation of NN Intervals (SDNN) compared to non-diabetic participants (p = 0.001). Higher proteinuria (uPCR ≥ 0.2) was associated with 5.73 ms lower SDNN compared to lower proteinuria (p = 0.027). This study represents the largest dataset to date evaluating SDNN, a key heart rate variability metric using wearable EKG technology in CKD. Our findings highlight that specific clinical and demographic factors significantly influence HRV in this population. These results provide a critical foundation for future work to determine whether time-specific HRV metrics can serve as predictive biomarkers for cardiovascular risk and clinical outcomes in CKD.
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Skarke et al. (2025) studied this question.
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