Evidence map›Paper›PMID 39980570›Full record

ReviewDigital health

Sleep as a window of cardiometabolic health: The potential of digital sleep and circadian biomarkers.

Willem J van den Brink, Johanneke E Oosterman, Dagmar J Smid, Herman J de Vries, Douwe E Atsma, Sebastiaan Overeem, Suzan Wopereis

Abstract readReview
In one paragraph

Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Willem J van den BrinkResearch Group Microbiology and Systems Biology, Netherlands Organization for Applied Scientific Research (TNO), Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-4493-2382
Johanneke E OostermanResearch Group Microbiology and Systems Biology, Netherlands Organization for Applied Scientific Research (TNO), Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-1473-5839
Dagmar J SmidResearch Group Microbiology and Systems Biology, Netherlands Organization for Applied Scientific Research (TNO), Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-8675-5302
Herman J de VriesResearch Group Learning & Workforce Development, Netherlands Organisation for Applied Scientific Research (TNO), Soesterberg, The Netherlands.
Douwe E AtsmaDepartment of Cardiology, Leiden University Medical Centre, Leiden, The Netherlands.
Sebastiaan OvereemSleep Medicine Center Kempenhaeghe, Heeze, The Netherlands.
Suzan WopereisResearch Group Microbiology and Systems Biology, Netherlands Organization for Applied Scientific Research (TNO), Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital biomarkers are quantifiable and objective indicators of a person's physiological function, behavioral state or treatment response, that can be captured using connected sensor technologies such as wearable devices and mobile apps. We envision that continuous and 24-h monitoring of the underlying physiological and behavioral processes through digital biomarkers can enhance early diagnostics, disease management, and self-care of cardiometabolic diseases. Cardiometabolic diseases, which include a combination of cardiovascular and metabolic disorders, represent an emerging global health threat. The prevention potential of cardiometabolic diseases is around 80%, indicating a promising role for interventions in the lifestyle and/or the environmental context. Disruption of sleep and circadian rhythms are increasingly recognized as risk factors for cardiometabolic disease. Digital biomarkers can be used to measure around the clock, that is, day and night, to quantify not only sleep patterns but also diurnal fluctuations of certain biomarkers and processes. In this way, digital biomarkers can support the delivery of optimal timed medical care. Night-time cardiometabolic patterns, such as blood pressure dipping, are predictive of cardiometabolic health outcomes. In addition, the sleep period provides an opportunity for digital cardiometabolic health monitoring with relatively low influence of artifacts, such as physical activity and eating. Digital biomarkers that utilize sleep as a window of health can be used during daily life to enable early diagnosis of cardiometabolic diseases, facilitate remote patient monitoring, and support self-management in people with cardiometabolic diseases. This review describes the influence of sleep and circadian rhythms on cardiometabolic disease and highlights the state-of-the-art sleep and circadian digital biomarkers which could be of benefit in the prevention of cardiometabolic disease.

Indexed as

cardiometabolic diseasecardiovascular diseasecircadian misalignmentcircadian rhythmdigital biomarkersdigital health technologiespersonalized medicineprevention diseaserisk factorsSleepwearables

Identifiers

PMID39980570
PMCPMC11840856

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.