1.Restless Legs Syndrome: An Update in Diagnosis and Management.
Journal of the Korean Academy of Family Medicine 2008;29(4):241-250
No abstract available.
Restless Legs Syndrome
2.Unilateral Restless Legs Syndrome.
Sang Wook LEE ; Changwoon CHOI ; Yong Seo KOO ; Ki Young JUNG
Journal of the Korean Neurological Association 2012;30(4):379-380
No abstract available.
Restless Legs Syndrome
3.A Case of Idiopathic Restless Legs Syndrome in a Child.
Do Young KIM ; In Kyu LEE ; Sun Young KIM ; Myung Ho OH ; Young Chang KIM
Journal of the Korean Child Neurology Society 2004;12(2):247-251
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*
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Humans
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Male
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Restless Legs Syndrome*
4.Comparison of therapeutic effects of acupoints selected along different meridians on restless legs syndrome.
Wen ZHOU ; Di-hua WANG ; Rong-kun YANG ; Hong ZHOU
Chinese Acupuncture & Moxibustion 2005;25(9):616-618
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.
Acupuncture Points ; Acupuncture Therapy ; Humans ; Meridians ; Restless Legs Syndrome
5.A Case of Restless Leg Syndrome Induced by Mirtazapine in a Patient with Major Depressive Disorder.
Han Yong JUNG ; Soyoung Irene LEE ; Dong Hyeon KIM ; Eui Jung CHOI
Korean Journal of Psychopharmacology 2004;15(4):488-491
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*
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Humans
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Neurotransmitter Agents
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Restless Legs Syndrome*
6.Objective Sleep Quality in Subjects with Restless Legs Syndrome versus with Psychophysiological Insomnia: Polysomnography and Cardiopulmonary Coupling Analysis.
Geon Youb NA ; Su Jung CHOI ; Eun Yeon JOO ; Seung Bong HONG
Journal of Sleep Medicine 2015;12(1):13-17
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*
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Restless Legs Syndrome*
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Sleep Initiation and Maintenance Disorders*
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Sleep Stages
7.A Domestic Diagnosis System for Early Restless Legs Syndrome Based on Deep Learning.
Ping ZHOU ; Luojie HUANG ; Qingxian ZHAO ; Wenjin XIAO ; Siyu LI
Chinese Journal of Medical Instrumentation 2019;43(2):79-82
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
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Humans
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Movement
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Polysomnography
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Restless Legs Syndrome
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diagnosis
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Sleep
8.Acute-Withdrawal Restless Legs Syndrome Following Abrupt Cessation of Short-Term Tramadol.
Young Min PARK ; Hye Kyeong PARK ; Leen KIM ; Heon Jeong LEE ; Seung Gul KANG
Psychiatry Investigation 2014;11(2):204-206
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
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Leg
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Recurrence
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Restless Legs Syndrome*
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Sensation
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Sleep Initiation and Maintenance Disorders
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Substance Withdrawal Syndrome
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Tramadol*
9.Restless Legs Syndrome in Children and Adolescents with Type 1 Diabetes.
Woo Seok YANG ; Jae Ho YOO ; Sang Myung CHEON ; Seong Hwan KIM ; Byeong Moo CHOE ; Woo Jin KIM ; Young Rong BANG ; Jae Hong PARK
Sleep Medicine and Psychophysiology 2015;22(1):20-24
OBJECTIVES: Restless legs syndrome (RLS) is a common sleep disorder in adults with diabetes. This study investigated the frequency of RLS and clinical correlations in children and adolescents with type 1 diabetes. METHODS: This study included 55 consecutive patients (21 males, age 12.6 +/- 3.4 years) with type I diabetes that were regularly treated at the Department of Pediatric Endocrinology. RLS was diagnosed by intensive interviews which also included the Epworth Sleepiness Scale (ESS) and International RLS Rating Scale (IRLSRS). Patients also received neurological examinations and laboratory tests for diabetes, iron metabolism and renal function. RESULTS: Thirteen patients (23.6%, 6 males) were compatible for the diagnostic criteria of RLS. None of the RLS patients showed abnormal findings in neurological evaluations and 7 patients had familial history of RLS. Demographic and laboratory findings were not different between the patients with or without RLS. The RLS group showed significantly increased ESS and IRLSRS scores. CONCLUSION: RLS was prevalent in children and adolescents with type I diabetes. The association between RLS and diabetes-related laboratory findings requires further investigation.
Adolescent*
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Adult
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Child*
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Endocrinology
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Humans
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Iron
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Male
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Metabolism
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Neurologic Examination
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Restless Legs Syndrome*
10.Sleep Related Periodic Leg Movements.
Yong Duk KIM ; Sang Bock LEE ; Myung Sik LEE
Journal of the Korean Neurological Association 1995;13(4):913-923
We describe 7 patients with sleep related periodic leg movements(SRPLM) associated with variable neurological diseases, including focal thoracic cord lesions(4 cases), idiopathic Parkinson's diseased case), recurrent aseptic meningitis(1 case), and subacute sensory polyneuropathy(l case). Four patients with SRPLM associated with thoracic cord lesions also had paraparesis, suggesting involvement of pyramidal tract in the genesis of SRPLM. All the other three patients had dysesthesia, and at least two of them had restless legs syndrome. SRPLM of a patient with a thoracic schwannoma disappeared completely after surgical removal of tumor. One patient with intramedullary thoracic cord lesion and one asociated with Parkinson's disease showed marked improvement of SRPLM after levodopa treatment. Damage to the pyramidal tract or abnormal sensory inputs seem to activate lumbosacral generator selectively. Such neuronal systems are suspected to be modulated by. The dopaminergic neuronal system and the neuronal structures related to sleep.
Dopaminergic Neurons
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Humans
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Leg*
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Levodopa
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Neurilemmoma
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Neurons
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Paraparesis
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Paresthesia
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Parkinson Disease
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Pyramidal Tracts
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Restless Legs Syndrome