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Periodic limb movements of sleep: empirical and theoretical evidence supporting objective at-home monitoring

Overview of attention for article published in Nature and science of sleep, August 2016
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Title
Periodic limb movements of sleep: empirical and theoretical evidence supporting objective at-home monitoring
Published in
Nature and science of sleep, August 2016
DOI 10.2147/nss.s101753
Pubmed ID
Authors

Marilyn Moro, Balaji Goparaju, Jelina Castillo, Yvonne Alameddine, Matt T Bianchi

Abstract

Periodic limb movements of sleep (PLMS) may increase cardiovascular and cerebrovascular morbidity. However, most people with PLMS are either asymptomatic or have nonspecific symptoms. Therefore, predicting elevated PLMS in the absence of restless legs syndrome remains an important clinical challenge. We undertook a retrospective analysis of demographic data, subjective symptoms, and objective polysomnography (PSG) findings in a clinical cohort with or without obstructive sleep apnea (OSA) from our laboratory (n=443 with OSA, n=209 without OSA). Correlation analysis and regression modeling were performed to determine predictors of periodic limb movement index (PLMI). Markov decision analysis with TreeAge software compared strategies to detect PLMS: in-laboratory PSG, at-home testing, and a clinical prediction tool based on the regression analysis. Elevated PLMI values (>15 per hour) were observed in >25% of patients. PLMI values in No-OSA patients correlated with age, sex, self-reported nocturnal leg jerks, restless legs syndrome symptoms, and hypertension. In OSA patients, PLMI correlated only with age and self-reported psychiatric medications. Regression models indicated only a modest predictive value of demographics, symptoms, and clinical history. Decision modeling suggests that at-home testing is favored as the pretest probability of PLMS increases, given plausible assumptions regarding PLMS morbidity, costs, and assumed benefits of pharmacological therapy. Although elevated PLMI values were commonly observed, routinely acquired clinical information had only weak predictive utility. As the clinical importance of elevated PLMI continues to evolve, it is likely that objective measures such as PSG or at-home PLMS monitors will prove increasingly important for clinical and research endeavors.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Master 4 15%
Other 2 7%
Student > Postgraduate 2 7%
Student > Doctoral Student 1 4%
Other 4 15%
Unknown 9 33%
Readers by discipline Count As %
Medicine and Dentistry 7 26%
Neuroscience 3 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Mathematics 1 4%
Agricultural and Biological Sciences 1 4%
Other 5 19%
Unknown 9 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 August 2016.
All research outputs
#17,285,036
of 25,373,627 outputs
Outputs from Nature and science of sleep
#443
of 629 outputs
Outputs of similar age
#252,519
of 381,036 outputs
Outputs of similar age from Nature and science of sleep
#8
of 8 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 629 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.5. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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