ArticleDigital health
Time-specific associations of wearable sensor-based cardiovascular and behavioral readouts with disease phenotypes in the outpatient setting of the Chronic Renal Insufficiency Cohort.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Quantifying sleep wake rhythms in the hospital environment with digital technologies.NPJ digital medicine · 2026Article
- TracMyAir: Smartphone-enabled spatiotemporal estimates for inhaled doses of particulate matter and ozone to personalize health outcomes.medRxiv : the preprint server for health sciences · 2026Article
- Quantifying Sleep-Wake Rhythms in the Hospital Environment with Digital Technologies.medRxiv : the preprint server for health sciences · 2025Article
- Diurnal variation of wearable device-based heart rate variability in the Chronic Renal Insufficiency Cohort study.NPJ digital medicine · 2025Article
- Article
- Evidence for a role of human blood-borne factors in mediating age-associated changes in molecular circadian rhythms.bioRxiv : the preprint server for biology · 2024Article
- Prognostic utility of rhythmic components in 24-h ambulatory blood pressure monitoring for the risk stratification of chronic kidney disease patients with cardiovascular co-morbidity.Journal of human hypertension · 2024Article
- Integrative Analysis of Rhythmicity: From Biology to Urban Environments and Sustainability.International journal of environmental research and public health · 2022Review
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Authors and funding
11 authors.
Funding
Abstract
Patients with chronic kidney disease 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 chronic kidney disease from the Chronic Renal Insufficiency Cohort and controls (n = 49). Time-specific partitioning of heart rate variability readouts confirm higher parasympathetic nervous activity during the night (mean RR at night 14.4 ± 1.9 ms vs. 12.8 ± 2.1 ms during active hours; n = 47, analysis of variance (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 nondiabetic patients (prominent at night with 0.58 ± 0.2 vs. 0.45 ± 0.12, respectively, adj.
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