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

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

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Title: Periodic limb movements of sleep: empirical and theoretical evidence supporting objective at-home monitoring
Author: Moro, Marilyn; Goparaju, Balaji; Castillo, Jelina; Alameddine, Yvonne; Bianchi, Matt T

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Citation: Moro, Marilyn, Balaji Goparaju, Jelina Castillo, Yvonne Alameddine, and Matt T Bianchi. 2016. “Periodic limb movements of sleep: empirical and theoretical evidence supporting objective at-home monitoring.” Nature and Science of Sleep 8 (1): 277-289. doi:10.2147/NSS.S101753. http://dx.doi.org/10.2147/NSS.S101753.
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Abstract: Introduction: 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. Methods: 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. Results: 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. Conclusion: 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.
Published Version: doi:10.2147/NSS.S101753
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4982487/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:29002585
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