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Developing Biomarker Arrays Predicting Sleep and Circadian-Coupled Risks to Health

Overview of attention for article published in Sleep, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
3 X users
reddit
1 Redditor

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mendeley
164 Mendeley
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Article details
Title
Developing Biomarker Arrays Predicting Sleep and Circadian-Coupled Risks to Health
Published in
Sleep, April 2016
DOI 10.5665/sleep.5616
Pubmed ID
Authors
Abstract

The impact of advances in sleep and circadian sciences over the last 20 years on medicine, health, and public safety has been limited in part by the lack of availability of objective tools capable of quantifying sleep and circadian function in point-of-care settings. This whitepaper is a product of a workshop that was designed to bring together thought-leaders in biomarker development, experts in sleep circadian biology and sleep disorders to identify barriers and opportunities informing the future development of point-of-care diagnostic tools. The workshop entitled, "Developing Biomarker Arrays Predicting Sleep and Circadian-Coupled Risks to Health," was held in Bethesda April 27-28 2015, and was jointly sponsored by the National Heart Lung and Blood Institute, National Institute on Aging and the Sleep Research Society (hereafter referred to as the biomarker workshop, http://www.nhlbi.nih.gov/research/reports). The Sleep Research Society supported a number of early career investigators to attend the workshop. They contributed to the writing of this whitepaper. A biomarker is a "biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, condition or disease."1,2 For the purpose of this whitepaper, "biomarkers" include quantifiable molecules and chemical properties of easily accessible biological samples (e.g., blood, urine, saliva). An ultimate goal is the development of robust and practical approaches for point-of-contact/care (p-o-c) implementation in population-based research and most importantly, for clinical applications to enhance sleep and circadian health. Biomarkers to assess current alertness status, sleep health and circadian function are lacking for: research, p-o-c diagnosis of sleep and circadian disorders, for prognosis and to evaluate the risk of associated heart, lung, blood, and aging diseases and disorders, and to assess the adequacy of therapy. The ideal biomarker would show high specificity (correctly identify the absence of a sleep deficiency) and sensitivity (correctly identify the state and degree of sleep loss, and possibly even duration that such a status has been ongoing). However, currently the field is without any viable biomarkers based in easily accessible bio-specimens. The availability of objective platforms capable of quantifying sleep and circadian function will ultimately determine whether advances in understanding sleep and circadian biology can be applied to improve health and disease management and reduce risks to health and public safety. In parallel with the development of p-o-c biomarkers, there is urgent need to enhance and validate mobile and wearable technologies that can be used in population phenotyping to accurately track sleep and circadian physiology and behavior. Together these efforts will position the field for participation in the Million Vet Program (http://www.research.va.gov/MVP/) and the Precision Medicine Initiatives (http://www.nih.gov/precision-medicine-initiative-cohort-program). With diagnostic tools for p-o-c measurement of sleep and circadian function, medical care and physician practices addressing sleep and circadian disorders and risk for metabolic and other diseases, will be vastly improved, translating into lower health care costs and a healthier population.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 <1%
United Kingdom 1 <1%
Unknown 162 99%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 27 16%
Student > Bachelor 20 12%
Student > Master 19 12%
Researcher 18 11%
Professor > Associate Professor 9 5%
Other 24 15%
Unknown 47 29%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 29 18%
Biochemistry, Genetics and Molecular Biology 18 11%
Neuroscience 13 8%
Nursing and Health Professions 7 4%
Agricultural and Biological Sciences 7 4%
Other 30 18%
Unknown 60 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 May 2023.
All research outputs
#3,637,038
of 33,779,198 outputs
Outputs from Sleep
#1,793
of 5,963 outputs
Outputs of similar age
#44,792
of 336,553 outputs
Outputs of similar age from Sleep
#23
of 63 outputs
Altmetric has tracked 33,779,198 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,963 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 33.6. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 336,553 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.