Diurnal variation of wearable device-based heart rate variability in the Chronic Renal Insufficiency Cohort study

Carsten Skarke; Wei Yang; Daohang Sha; Nicholas F Lahens; Tamara Isakova; Mark Unruh; Rajat Deo; Eunice Carmona-Powell; John H Holmes; Elaine Ficarra; Jing Chen; Jiang He; Hernan Rincon-Choles; Vallabh Shah; Chi-Yuan Hsu; Amanda H Anderson; James P Lash; Mahboob Rahman; CRIC Study Investigators

doi:10.1038/s41746-025-02010-5

Diurnal variation of wearable device-based heart rate variability in the Chronic Renal Insufficiency Cohort study

NPJ Digit Med. 2025 Nov 13;8(1):653. doi: 10.1038/s41746-025-02010-5.

Authors

Carsten Skarke^{1

2}, Wei Yang³, Daohang Sha³, Nicholas F Lahens⁴, Tamara Isakova⁵, Mark Unruh⁶, Rajat Deo⁷, Eunice Carmona-Powell⁸, John H Holmes³, Elaine Ficarra⁷, Jing Chen⁹, Jiang He¹⁰, Hernan Rincon-Choles¹¹, Vallabh Shah¹¹, Chi-Yuan Hsu¹², Amanda H Anderson⁸, James P Lash¹³, Mahboob Rahman¹⁴; CRIC Study Investigators

Collaborators

CRIC Study Investigators:
Lawrence J Appel, Debbie L Cohen, Laura M Dember, Alan S Go, Panduranga S Rao

Affiliations

¹ Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. cskarke@pennmedicine.upenn.edu.
² Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. cskarke@pennmedicine.upenn.edu.
³ Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
⁴ Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
⁵ Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
⁶ Department of Kidney Medicine, Medical Specialty Institute, Cleveland Clinic Foundation, OH, USA.
⁷ Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
⁸ Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
⁹ Division of Nephrology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
¹⁰ Department of Epidemiology, University of Texas Southwestern Medical Center O'Donnell School of Public Health, Dallas, TX, USA.
¹¹ Department of Internal Medicine, University of New Mexico HSC, Albuquerque, NM, USA.
¹² Division of Nephrology, University of California-San Francisco, San Francisco, CA, USA.
¹³ Division of Nephrology, Department of Medicine, University of Illinois Chicago, Chicago, IL, USA.
¹⁴ University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, USA. Mahboob.Rahman@UHhospitals.org.

Abstract

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.

Abstract

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