Leg movements during wakefulness in restless legs syndrome: Time structure and relationships with periodic leg movements during sleep
Sleep Research Centre, Department of Neurology I.C., Oasi Institute for Research on Mental Retardation and Brain Aging (IRCCS), Troina, Italy. Sleep Medicine
(Impact Factor: 3.15).
02/2012; 13(5):529-35. DOI: 10.1016/j.sleep.2011.08.007
Approximately one third of patients with restless legs syndrome (RLS) also show periodic leg movements (PLM) during relaxed wake fulness (PLMW). In contrast with the large amount of data published on periodic leg movements during sleep (PLMS), PLMW have received less attention from the scientific community. The objective of this study was to evaluate the correlations/differences of time-structure and response to a dopamine-agonist between PLMW and PLMS in patients with RLS.
Ninety idiopathic RLS patients and 28 controls were recruited. Subjects underwent clinical and neurophysiological evaluation, hematological screening, and one or two consecutive full-night polysomnographic studies. A subset of patients received 0.25mg of pramipexole or placebo before the second recording. Polysomnographic recordings were scored and LM activity was analyzed during sleep and during the epochs of wakefulness occurring during the first recording hour.
RLS patients had higher LM activity during wakefulness than controls, but with a similar periodicity. Even if correlated, the ability of the PLMW index to predict the PLMS index decreased with increasing LM activity. Intermovement intervals during wakefulness showed one peak only at approximately 4s, gradually decreasing with increasing interval in both patients and controls. The effect of pramipexole was very limited and involved the small periodic portion of LM activity during wakefulness.
PLMW index and PLMS index were correlated; however, the magnitude of this correlation was not sufficient to suggest that PLMW can be good predictors of PLMS. Short-interval LM activity during wakefulness and sleep might be linked to the severity of sleep disruption in RLS patients and the differences between their features obtained during wakefulness or sleep might be relevant for the diagnosis of sleep disturbances in RLS.
Available from: Oliviero Bruni
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ABSTRACT: This paper evaluates, in both the theoretical and practical frameworks, the value of the application of the current criteria for the scoring of leg movement activity during sleep, recorded in clinical and research settings, for the study of restless legs syndrome (RLS) and other conditions. Recently, new parameters have been introduced to better describe the time structure of leg movement activity during sleep. The periodicity index, the distribution of inter-movement intervals, and the hourly distribution of periodic leg movements during sleep have emerged as valuable descriptors. Therefore, the additional value provided by the new methods is discussed with a glance at the rationale behind these new approaches. It is concluded that these new methods have proven to be able to provide new insights into the phenomenon of leg movement activity during sleep. In particular, the classical periodic leg movements during sleep (PLMS) index does not seem to be sufficiently specific for the diagnosis and clinical significance of RLS. The specificity of PLMS for the diagnosis of RLS can be significantly increased by considering these additional parameters. The same parameters also allow a more detailed analysis of several aspects of RLS and PLMS that were impossible to perform before on the basis of the simple PLMS index alone.
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ABSTRACT: The current clinical standard for quantifying sleep physiology is the laboratory polysomnogram, from which basic sleep-wake stages are determined. However, the complexity of sleep physiology has inspired alternative metrics that are providing additional insights into the rich dynamics of sleep. Electro-encephalography, magneto-encephalography, and functional magnetic resonance imaging represent advanced imaging modalities for understanding brain dynamics. These methods are complemented by autonomic measurements that provide additional important insights. We review here the spectrum of approaches that have been leveraged towards improved understanding of the complexity of sleep.
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