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

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

  • By

  • 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

  • November 13, 2025

  • 0 min

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Objective:

To evaluate the prognostic value of continuous biometric monitoring of heart rate variability (HRV) in chronic kidney disease (CKD) using wearable devices, emphasizing its potential role in improving patient outcomes.

Key Findings:
  • Diabetes was associated with a 7.4 ms lower SDNN compared to non-diabetic participants (p = 0.001), indicating a significant cardiovascular risk.
  • Higher proteinuria (uPCR ≥ 0.2) correlated with a 5.73 ms lower SDNN compared to lower proteinuria (p = 0.027), suggesting a link between kidney function and heart health.
  • 65.8% of participants in the low SDNN category had diabetes, indicating a significant disease burden and potential for targeted interventions.
Interpretation:

The study highlights the influence of specific clinical and demographic factors on HRV in CKD, suggesting that HRV metrics could serve as predictive biomarkers for cardiovascular risk, potentially guiding clinical decisions.

Limitations:
  • Cross-sectional design limits causal inferences, making it difficult to establish direct relationships.
  • Potential selection bias as participants were generally healthier than those in other CRIC phases, which may affect the generalizability of the findings.
Conclusion:

Findings provide a foundation for future research on HRV as a predictive tool for cardiovascular outcomes in CKD, emphasizing the need for longitudinal studies to validate these results.

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