No abstract available.
Restless Legs Syndrome

No abstract available.
Restless Legs Syndrome

Restless legs syndrome(RLS) is a common but frequently undiagnosed sensorimotor disorder. It has distinct clinical manifestations and also it is fairly common in late adulthood. However, it is rarely recognized in children because of the difficulties in expressing the signs and symptoms and the lacks of experience of pediatricians about the disease. Although its underlying pathophysiology is not fully understood, the diagnostic criteria of RLS in children were established in the year of 2003. We experienced a case of idiopathic restless legs syndrome in a 10-year-old boy and we present the case with a brief review of related literature.
Child* ; Humans ; Male ; Restless Legs Syndrome*

Mirtazapine is a novel antidepressant and has a unique dual action profile, combining the enhancement of the noradrenergic neurotransmitter system with specific actions on particular serotonergic receptor subtypes. The authors report a case of restless leg syndrome induced by mirtazapine. The patient (46 years old male) with major depressive disorder developed typical restless leg syndrome from the initial period of administration of mirtazapine. Restless leg syndrome was not relieved by reduction of mirtazapine and disappeared rapidly after discontinuation of mirtazapine. The major difference of the case from previously reported cases is the onset time of symptoms. We may consider that mirtazapine can induce dopaminergic side effect like a restless leg syndrome promptly as its fast-acting antidepressant effect.
Depressive Disorder, Major* ; Humans ; Neurotransmitter Agents ; Restless Legs Syndrome*

OBJECTIVES: To compare the sleep quality in the view of polysomnography (PSG) and cardiopulmonary coupling (CPC) analysis in subjects with restless legs syndrome (RLS) versus with psychophysiological insomnia (PPI). METHODS: The PSG data of 109 subjects with RLS and 86 with PPI (apnea-hypopnea index <5 /h) were collected. All subjects reported sleep onset and maintenance insomnia. CPC parameters were obtained using CPC analyzer in RemLogic. Sleep spectrogram by CPC analyses categorized sleep as "stable" [high-frequency coupling (HFC), 0.1-0.4 Hz] and "unstable" [low-frequency coupling (LFC), 0.1-0.01 Hz], independent of sleep stages. We compared PSG and CPC parameters between two groups and performed correlation analyses to find the PSG parameters to affect CPC parameters. RESULTS: In PSG parameters, subjects with PPI showed significantly longer sleep latency (14.2+/-20.06 vs. 27.5+/-34.96, p<0.001), and decreased sleep efficiency (SE, 80.5+/-14.96 vs. 76.5+/-14.45, p=0.009) than RLS. CPC parameters were not significantly different between groups. In both groups HFC was positively correlated with total sleep time and SE and was negatively associated with time of wake after sleep onset in both groups. Meanwhile, very LFC showed the opposite results to HFC with the same PSG parameters. CONCLUSIONS: Although subjects with RLS or PPI present sleep onset and maintenance insomnia, objective sleep quality was worse in PPI than RLS. It suggests that CPC as a factor to differentiate sleep quality between the RLS and the PPI has a limited role.
Polysomnography* ; Restless Legs Syndrome* ; Sleep Initiation and Maintenance Disorders* ; Sleep Stages

OBJECTIVETo compare therapeutic effects of different acupoints selected on restless legs syndrome.

METHODSEighty-one cases were randomly divided into a treatment group (n=41) treated by acupoint selection method according to nerve anatomy and combination of positive findings with neurobiological theory, and a control group (n=40) treated by traditional acupoint selection method.

RESULTSThe effective rate and the markedly effective rate were 97.6% and 90.3% in the treatment group, and 75.0% and 60.0% in the control group with significant differences between the two groups (P < 0.01), and there was a significant difference between the two groups in the needed treatment times for the cured cases (P < 0.01).

CONCLUSIONThe acupoint selection method according to nerve anatomy, positive findings and neurobiological theory has a better therapeutic effect on restless legs syndrome as compared with the traditional method.

Restless legs syndrome,as a common sleep disorder,has nowadays long been diagnosed by self-rating scale and polysomnography.In this paper,a domestic diagnosis system for early restless legs syndrome based on deep learning is proposed,which is suitable for early patients with unstable symptoms in routine diagnosis.The hardware system is installed in the bed.And the non-contact sleeping dynamic signal acquisition is realized based on the acceleration sensors.The software system uses deep learning to classify and recognize the signals.A Fully Connected Feedforward Network based on Keras framework is constructed to recognize seven kinds of activities during sleeping.The accuracy of comprehensive classification is 97.83%.Based on former results,the periodic limb movement index and awakening index were evaluated to make the diagnosis of restless legs syndrome.
Deep Learning ; Humans ; Movement ; Polysomnography ; Restless Legs Syndrome ; diagnosis ; Sleep

We report a young man who had received tramadol for pain control and experienced an uncomfortable sensation in both legs immediately after tramadol withdrawal that worsened at rest and at night, and which could be relieved only by moving the legs. He suffered from insomnia and paced up and down in his house every night. Readministration of tramadol dramatically resolved his symptoms of restless legs syndrome (RLS), but they reappeared after tramadol withdrawal. Tramadol was therefore replaced with ropinirole, which was discontinued after several weeks, and there was no recurrence of his RLS symptoms. This patient appeared to have developed tramadol-withdrawal-induced RLS, and this case report emphasizes the importance of monitoring for withdrawal-type symptoms like RLS when tramadol intake is being stopped.
Humans ; Leg ; Recurrence ; Restless Legs Syndrome* ; Sensation ; Sleep Initiation and Maintenance Disorders ; Substance Withdrawal Syndrome ; Tramadol*

BACKGROUND AND PURPOSE: The purpose of this study was to characterize abnormal cortical activity during sleep in restless legs syndrome (RLS) patients and to determine the effects of treatment with a dopamine agonist. Based on whole-brain electroencephalograms, we attempted to verify alterations in the functional network as well as the spectral power of neural activities during sleep in RLS patients and to determine whether the changes are reversed by treatment with pramipexole. METHODS: Twelve drug-naïve RLS patients participated in the study. Overnight polysomnography was performed before and after treatment: the first recording was made immediately prior to administering the first dose of pramipexole, and the second recording was made 12–16 weeks after commencing pramipexole administration. Sixteen age-matched healthy participants served as a control group. The spectral power and interregional phase synchrony were analyzed in 30-s epochs. The functional characteristics of the cortical network were quantified using graph-theory measures. RESULTS: The delta-band power was significantly increased and the small-world network characteristics in the delta band were disrupted in RLS patients compared to the healthy controls. These abnormalities were successfully treated by dopaminergic medication. The delta-band power was significantly correlated with the RLS severity score in the RLS patients prior to treatment. CONCLUSIONS: Our findings suggest that the spectral and functional network characteristics of neural activities during sleep become abnormal in RLS patients, and these abnormalities can be successfully treated by a dopamine agonist.
Delta Rhythm* ; Dopamine Agonists* ; Dopamine* ; Electroencephalography ; Healthy Volunteers ; Humans ; Polysomnography ; Restless Legs Syndrome*

BACKGROUND AND PURPOSE: Previous T2 relaxometry studies have provided evidence for regional brain iron deficiency in patients with restless legs syndrome (RLS). Measurement of the iron content in several brain regions, and in particular the substantia nigra (SN), in early- and late-onset RLS patients using T2 relaxometry have yielded inconsistent results. In this study the regional iron content was assessed in patients with early- and late-onset RLS using magnetic resonance imaging (MRI), and compared the results with those in controls. METHODS: Thirty-seven patients with idiopathic RLS (20 with early onset and 17 with late onset) and 40 control subjects were studied using a 3.0-tesla MRI with a gradient-echo sampling of free induction decay and echo pulse sequence. The regions of interest in the brain were measured independently by two trained analysts using software known as medical image processing, analysis, and visualization. The results were compared and a correlation analysis was conducted to investigate which brain areas were related to RLS clinical variables. RESULTS: The iron index in the SN was significantly lower in patients with late-onset RLS than in controls (p=0.034), while in patients with early-onset RLS there was no significant difference. There was no significant correlation between the SN iron index of the late-onset RLS group and clinical variables such as disease severity. CONCLUSIONS: Late-onset RLS is associated with decreased iron content in the SN. This finding supports the hypothesis that regional brain iron deficiency plays a role in the pathophysiology of late-onset RLS.
Brain* ; Humans ; Iron ; Magnetic Resonance Imaging* ; Red Nucleus ; Restless Legs Syndrome* ; Substantia Nigra