Isolated REM sleep without atonia and isolated REM sleep behaviour disorder: a study of clinical and prognostic differences

Although periodic limb movements in sleep (PLMS) have been described in multiple pediatric publications, periodic limb movement disorder (PLMD) has not. The aims of this study were to describe the prevalence, sleep-related correlates, and polysomnographic correlates of PLMD in a large pediatric case series, and compare these to pediatric obstructive sleep apnea (OSA). All PLMD cases (defined by International Classification of Sleep Disorders, 2nd edition criteria + respiratory disturbance index [RDI] < 3) and OSA cases (defined by RDI ≥ 3 + PLMS < 5), from a single pediatric sleep practice, over a 2-year time span, were included. Chart, questionnaire, and polysomnographic data were compiled. Of 468 referred children, 66 PLMD cases were identified (14%). The PLMD cases, mean age 8.1 years (range 1-17), were clinically characterized by frequent sleep onset and maintenance problems, difficulty awakening, restless sleep, leg pain/discomfort at night, and parasomnias. Compared to 90 OSA children, those with PLMD had a history of significantly more sleep onset and maintenance problems, leg pain/discomfort at night, parasomnias, getting out of bed at night, and family history of restless legs syndrome. Polysomnographically, PLMD cases had more awakenings, stage 1 sleep, stage shifts, and spontaneous arousals. These data indicate that pediatric PLMD has important clinical and polysomnographic correlates. In addition, PLMD has many characteristics that are different from pediatric OSA, suggesting that PLMD is a distinct pediatric sleep disorder, of which clinicians should be aware.

Respiratory-related leg movements (RRLMs) may contribute to the cardiovascular risk associated with obstructive sleep apnea (OSA). Selective serotonin reuptake inhibitors (SSRIs), but not bupropion, increase periodic leg movements in sleep. This study examines whether patients with OSA using SSRIs have more RRLMs than those taking bupropion or no antidepressant. Patients with an apnea-hypopnea index (AHI) of at least 10 events/h during a full-night diagnostic study or split-night study, who were taking bupropion (n = 32), an SSRI (n = 31), or no antidepressant (n = 31), were selected from a database of prestudy questionnaires. RRLMs were scored according to World Association of Sleep Medicine 2016 standards. Patients using SSRIs had significantly greater overall RRLM% (defined as the percentage of respiratory events associated with a leg movement, including apneas, hypopneas, and respiratory effort-related arousals), RRLM index, and periodic limb movement index relative to patients using bupropion and control patients. The difference between the RRLM% in the SSRI and bupropion groups was limited to patients undergoing split-night studies, and that of the SSRI and control groups was limited to patients undergoing full-night diagnostic studies. The greater number of RRLMs and PLMs in the SSRI group may contribute to treatment-emergent insomnia often seen with SSRI use. Fragmented sleep and elevated autonomic nervous system activation associated with increased RRLMs in patients with OSA taking SSRIs might also limit the tolerability of antidepressant treatment, as well as increase the risk for cardiovascular disease.

Pharmacologically induced/exacerbated restless legs syndrome (RLS), periodic limb movements in sleep (PLMS), and REM behavior disorder/REM sleep without atonia (RSWA) are increasingly recognized in clinical sleep medicine. A scoring system to evaluate the literature was created and implemented. The aim was to identify the evidence with the least amount of confound, allowing for more reliable determinations of iatrogenic etiology. Points were provided for the following criteria: manuscript type (abstract, peer-reviewed paper); population size studied (large retrospective study, small case series, case report); explicitly stated dosage timing; identification of peak symptoms related to time of medication administration (i.e., medication was ingested in the evening or at bedtime); initiation of a treatment plan; symptoms subsided or ceased with decreased dosage or drug discontinuation (for RLS articles only); negative personal history for RLS prior to use of the medication; exclusion of tobacco/alcohol/excessive caffeine use; exclusion of sleep disordered breathing by polysomnography (PSG); and PSG documentation of presence or absence of PLMS. For RLS and PLMS articles were also given points for the following criteria: each 2003 National Institutes of Health (NIH) RLS criteria met; exclusion of low serum ferritin; and exclusion of peripheral neuropathy by neurological examination. Thirty-two articles on drug-induced RLS, 6 articles on drug-induced PLMS, and 15 articles on drug-induced RBD/ RSWA were analyzed. Based on scores < or = 10 and trials of medication reduction/cessation, the strongest evidence available for drug induced RLS are for the following drugs: escitalopram; fluoxetine; L-dopa/carbidopa and pergolide; L-thyroxine; mianserin; mirtazapine; olanzapine; and tramadol. Since none of the PLMS articles assessed PLMI in trials of medication reduction/cessation, the strongest evidence based on scores > or = 10 are for the following drugs: bupropion, citalopram, fluoxetine, paroxetine, sertraline, and venlafaxine. Based on scores > or = 10 and/or trials of medication cessation, the strongest evidence for drug induced RBD/ RSWA is for the following drugs: clomipramine, selegiline, and phenelzine.

Lastra AC, Ingram D, Park J, etal. Moving toward standardization: physician reporting of sleep studies. J Clin Sleep Med. 2023;19(3):595-603.

IntroductionRestless legs syndrome is a sensorimotor neurological disorder characterized by an urge to move the legs in response to uncomfortable leg sensations. While asleep, 70 to 90 percent of patients with restless legs syndrome have periodic limb movements in sleep. Frequent periodic limb movements in sleep and related brain arousals as documented by polysomnography are associated with poorer quality of sleep and daytime fatigue. Restless legs syndrome in middle age is sometimes associated with neuropathic foot dysesthesias. The causes of restless legs syndrome and periodic limb movements in sleep are unknown, but the sensorimotor symptoms are hypothesized to originate in the central nervous system. We have previously determined that bilateral forefoot digital nerve impingement masses (neuromas) may be a cause of both neuropathic foot dysesthesias and the leg restlessness of restless legs syndrome. To the best of our knowledge, this case is the first report of bilateral foot neuromas as a cause of periodic limb movements in sleep.Case presentationA 42-year-old Caucasian woman with severe restless legs syndrome and periodic limb movements in sleep and bilateral neuropathic foot dysesthesias was diagnosed as having neuromas in the second, third, and fourth metatarsal head interspaces of both feet. The third interspace neuromas represented regrowth (or 'stump') neuromas that had developed since bilateral third interspace neuroma excision five years earlier. Because intensive conservative treatments including repeated neuroma injections and various restless legs syndrome medications had failed, radical surgery was recommended. All six neuromas were excised. Leg restlessness, foot dysesthesias and subjective sleep quality improved immediately. Assessment after 18 days showed an 84 to 100 percent reduction of visual analog scale scores for specific dysesthesias and marked reductions of pre-operative scores of the Pittsburgh sleep quality index, fatigue severity scale, and the international restless legs syndrome rating scale (36 to 4). Polysomnography six weeks post-operatively showed improved sleep efficiency, a marked increase in rapid eye movement sleep, and marked reductions in hourly rates of both periodic limb movements in sleep with arousal (135.3 to 3.3) and spontaneous arousals (17.3 to 0).ConclusionThe immediate and near complete remission of symptoms, the histopathology of the excised tissues, and the marked improvement in polysomnographic parameters documented six weeks after surgery together indicate that this patient's severe restless legs syndrome and periodic limb movements in sleep was of peripheral nerve (foot neuroma) origin. Further study of foot neuromas as a source of periodic limb movements in sleep and as a cause of sleep dysfunction in patients with or without concomitant restless legs syndrome, is warranted.

The current study aimed to investigate the clinical characteristics of Parkinson's disease (PD) patients with concomitant periodic limb movements in sleep (PLMS). The clinical data of 36 PD patients who underwent polysomnography (PSG) in Beijing Tiantan Hospital from October 2018 to July 2022 were collected. Unified Parkinson's Disease Rating Scale 3.0 and Hoehn & Yahr (H-Y) stage were used to evaluate the disease severity. Patients were divided into two groups: the PLMS+group periodic limb movements in sleep index [(PLMSI)≥15 times/h] and the PLMS-group (PLMSI<15 times/h), using the PLMSI 15 times/h as the cut-off value. The clinical characteristics between the two groups were compared. There were 15 patients (42%) in the PLMS+group and 21 patients (58%) in the PLMS-group, among which 12 patients (12/15) in the PLMS+group and 9 patients (42.9%) in the PLMS-group had rapid eye movement sleep behavior disorder (RBD). The rate of RBD in PLMS+group was higher than that in PLMS-group (P<0.05). There was statistically significant difference in the blood folate level between the PLMS-group and PLMS+group [6.20 (5.14, 11.70) ng/ml vs 4.41 (3.07, 5.64) ng/ml] (P<0.01). Folate deficiency was more common in the PLMS+group, while no statistically significant differences were found in homocysteine and ferritin levels (both P>0.05). Four patients in the PLMS+group had falling experience, while 14.3% (3/21) patients in the PLMS-group had falling experience. Patients in the PLMS+group were more likely to fall. The PLMS+group had higher arousal index according to PSG [PLMS-group: 11.90 (9.10, 15.80) times/h; PLMS+group: 21.50 (19.35, 29.90) times/h] (P<0.05). No statistically significant differences in other sleep parameters were detected between the two groups (all P>0.05). Meanwhile, the apnea-hypopnea index (AHI) in both groups was higher than normal (<5 times/h), of which the PLMS-group was 9.80 (4.70, 22.20) times/h and the PLMS+group was 8.20 (1.70, 11.15) times/h, indicating that PD patients were more likely to experience sleep apnea and hypopnea. PD patients with PLMS had lower folate level, higher risk for falls, higher sleep arousal index, more sleep fragmentation, and higher prevalence of RBD.

Rise of blood pressure with periodic limb movements in sleep and wakefulness

The restless legs syndrome (RLS) is a common neurologic disorder characterized by an irresistible urge to move the legs. It is a major cause of sleep disruption. Periodic limb movements in sleep are detectable in most patients with RLS and represent an objective physiological metric. To search for sequence variants contributing to RLS, we performed a genomewide association study and two replication studies. To minimize phenotypic heterogeneity, we focused on patients with RLS who had objectively documented periodic limb movements in sleep. We measured serum ferritin levels, since iron depletion has been associated with the pathogenesis of RLS. In an Icelandic discovery sample of patients with RLS and periodic limb movements in sleep, we observed a genomewide significant association with a common variant in an intron of BTBD9 on chromosome 6p21.2 (odds ratio, 1.8; P=2x10(-9)). This association was replicated in a second Icelandic sample (odds ratio, 1.8; P=4x10(-4)) and a U.S. sample (odds ratio, 1.5; P=4x10(-3)). With this variant, the population attributable risk of RLS with periodic limb movements was approximately 50%. An association between the variant and periodic limb movements in sleep without RLS (and the absence of such an association for RLS without periodic limb movements) suggests that we have identified a genetic determinant of periodic limb movements in sleep (odds ratio, 1.9; P=1x10(-17)). Serum ferritin levels were decreased by 13% per allele of the at-risk variant (95% confidence interval, 5 to 20; P=0.002). We have discovered a variant associated with susceptibility to periodic limb movements in sleep. The inverse correlation of the variant with iron stores is consistent with the suspected involvement of iron depletion in the pathogenesis of the disease.

&lt;p&gt;Periodic Limb Movement in Sleep (PLMS) are a sleep-related disorder of the limbs that increasingly more research has begun to associate with severe Cardiovascular Diseases (CVD). With that said, Polysomnography (PSG), followed by manual scoring, is the conventional approach being used to monitor the disorder. However, patient inconvenience, and the high costs associated with PSG, has probed the need for alternative screening tools to be developed. Moreover, due to the cumbersome and time-consuming nature of manually scoring for PLMS, more studies have begun to look into automated means of detecting PLMS. Hence, while one of the goals of the current thesis was to use the latest clinical specifications to develop an automated Periodic Limb Movement (PLM) detector, the other goal was to look into alternative signals to monitor PLMS. With that said, in the current thesis, an automated PLM detector was developed and tested on two datasets. In fact, the results were promising in that, correlation coefficients of 0.78 and 0.8, and absolute differences not greater than 9 and 6 (not including the extreme outliers) respectively, were found when comparing the clinical PLM scores with that of the automated algorithm’s PLM scores. Moreover, not only did the automated PLM detector compute PLM scores, it also provided us with PLM segmentation information, i.e., localization of PLM with respect to time. On the other hand, with regards to finding alternative signals to monitor PLMS, the etiology of PLMS was used in order to validate the use of relatively easily acquirable signals, such as Heart Rate (HR) signals, to monitor the condition. Moreover, core features were extracted from the HR signals and the PLM segmentation information from the developed PLM detector was used in order to perform individuaized classification between PLM and non-PLM segments (per subject). Although the results were promising in that, the percent of correctly identifying a given segment as PLM or non-PLM, using the HR features, across most of the subjects, i.e., especially those with PLM Index ≥ 15, were around and well above the 70% range, due to the possibility of other factors interfering with HR during sleep, a more immediate application of the observed PLMS vs HR distinction was, to be able to monitor the autonomic health of an individual, given their PLM information. Specifically, the latter was anticipated to be useful for studies looking into the relationship between PLMS and HR, and thus CVD, or more significantly, those looking into preventing CVD by treating PLM.&lt;/p&gt;

&lt;p&gt;Periodic Limb Movement in Sleep (PLMS) are a sleep-related disorder of the limbs that increasingly more research has begun to associate with severe Cardiovascular Diseases (CVD). With that said, Polysomnography (PSG), followed by manual scoring, is the conventional approach being used to monitor the disorder. However, patient inconvenience, and the high costs associated with PSG, has probed the need for alternative screening tools to be developed. Moreover, due to the cumbersome and time-consuming nature of manually scoring for PLMS, more studies have begun to look into automated means of detecting PLMS. Hence, while one of the goals of the current thesis was to use the latest clinical specifications to develop an automated Periodic Limb Movement (PLM) detector, the other goal was to look into alternative signals to monitor PLMS. With that said, in the current thesis, an automated PLM detector was developed and tested on two datasets. In fact, the results were promising in that, correlation coefficients of 0.78 and 0.8, and absolute differences not greater than 9 and 6 (not including the extreme outliers) respectively, were found when comparing the clinical PLM scores with that of the automated algorithm’s PLM scores. Moreover, not only did the automated PLM detector compute PLM scores, it also provided us with PLM segmentation information, i.e., localization of PLM with respect to time. On the other hand, with regards to finding alternative signals to monitor PLMS, the etiology of PLMS was used in order to validate the use of relatively easily acquirable signals, such as Heart Rate (HR) signals, to monitor the condition. Moreover, core features were extracted from the HR signals and the PLM segmentation information from the developed PLM detector was used in order to perform individuaized classification between PLM and non-PLM segments (per subject). Although the results were promising in that, the percent of correctly identifying a given segment as PLM or non-PLM, using the HR features, across most of the subjects, i.e., especially those with PLM Index ≥ 15, were around and well above the 70% range, due to the possibility of other factors interfering with HR during sleep, a more immediate application of the observed PLMS vs HR distinction was, to be able to monitor the autonomic health of an individual, given their PLM information. Specifically, the latter was anticipated to be useful for studies looking into the relationship between PLMS and HR, and thus CVD, or more significantly, those looking into preventing CVD by treating PLM.&lt;/p&gt;

Monitoring periodic limb movements in sleep (PLMS) is important since it is correlated with people's quality of sleep and several other sleep disorders. The clinically approved method of examining PLMS is polysomnography (PSG) where the sleep of patients are examined in a laboratory with various sensors attached to their body. However, PSG is time-consuming and expensive for patients and the need for cost-effective and comfortable PLMS detection method has not been fulfilled. Accordingly, we propose a PLMS detection framework which utilizes a wearable motion-sensor-embedded band. In this work, we study the location to comfortably wear the device and accurately collect data on a foot. Further, to increase the accuracy of classifying PLMS, we propose the Motion Synchronized Windowing technique which segments the intervals where movements occur. Finally, we classify PLMS by using various machine learning algorithms typically used in the human activity recognition. Our proposed system achieves the accuracy of up to 96.92% in detecting PLMS. Therefore, our system is a cost-effective and convenient method of monitoring PLMS.

Background: Some patients with periodic limb movement in sleep (PLMS) have disrupted sleep and excessive daytime sleepiness (EDS). The clinical characteristics of patients with PLMS and EDS remain to be elucidated. Objective: To address the clinical characteristics of patients with PLMS affected by EDS, we assessed the clinical variables in patients with and without EDS and determined the influencing factors using polysomnography (PSG). Methods: This retrospective study included 306 patients with PLMS who did not take drugs. They visited our clinic between March 2015 and February 2021. Their sleep was recorded using PSG. PLMS was defined as having brief (0.5-5 seconds) repetitive limb movements, with a frequency of 15 or more times per hour. The Epworth Sleepiness Scale (ESS) was used as a subjective sleepiness indicator. Using the ESS, EDS was defined as a score ≧11. Multivariable logistic regression analysis was performed to determine the factors influencing EDS in patients with PLMS. Results: Of the 306 patients, 43 had PLMS. EDS was detected in 23 patients with PLMS. Logistic regression analyses revealed lower odds of EDS in men (odds ratio［OR］0.187, 95% confidence interval ［CI］ 0.041-0.856, P = 0.0307) and older individuals (OR 0.92, 95% CI 0.862-0.982, P = 0.0119) among patients with PLMS. Conclusions: Older male patients with PLMS were less likely to have EDS. To our knowledge, this is the first study to demonstrate that men and older individuals had a lower likelihood of experiencing EDS among patients with PLMS.

Introduction Patients with periodic limb movements in sleep (PLMS) often present unique challenges in the management of obstructive sleep apnea (OSA). Anecdotal observations suggest that elevated download data and apnea-hypopnea indices (AHI) in patients using continuous positive airway pressure (CPAP) therapy may correlate with the presence of PLMS. This study aims to investigate the relationship between elevated download metrics on CPAP and confirmed PLMS diagnoses. Methods We conducted a retrospective analysis of 20 patients diagnosed with OSA and Statistical analyses were performed using chi-square. Inclusion criteria included the availability of detailed CPAP download data and polysomnography (PSG) ruling out PLMS. CPAP data were analyzed for average nightly usage, residual AHI, and percentage of flow limitations. Comparisons were made between patients with confirmed PLMS (PLMS+) and those without (PLMS-). Results Of the 50 patients analyzed, 14 patients were PLMS+. Statistical analyses were performed using chi-square, with a p-value of 0.002, indicating that the association between PLMS+ and PLMS- is statistically significant. Elevated download metrics were strongly predictive of PLMS diagnosis. Additionally, PLMS+ patients demonstrated greater CPAP pressure variability and lower subjective sleep quality scores compared to their PLMS- counterparts. Conclusion Elevated residual AHI and associated download metrics in patients undergoing CPAP therapy may serve as indirect markers for the presence of PLMS. These findings underscore the importance of comprehensive follow-up and PSG evaluations for patients presenting with suboptimal CPAP efficacy. Early identification of PLMS in this population could inform tailored therapeutic interventions, potentially improving sleep quality and overall treatment outcomes. Support (if any)

Cyclic alternating pattern (CAP) is known to increase in many conditions of sleep disruption and sleep disorders, including obstructive sleep apnea syndrome and periodic limb movements in sleep (PLMS). Periodic limb movements in sleep associated with obstructive sleep apnea syndrome may vanish after positive airway pressure treatment, may persist, or emerge at treatment night. Here, the authors aimed to investigate the underlying pathophysiology of nonvanishing, vanishing, or newly emergent PLMS. The authors designed a prospective study and included 10 patients with nonvanishing PLMS during positive airway pressure therapy, 10 patients with vanishing PLMS, 10 patients with newly emergent PLMS, and 10 patients without PLMS at both nights. The CAP analysis was performed in detail at diagnostic polysomnography recording and at positive airway pressure titration. The changes in CAP parameters were evaluated in regard to nonvanishing, vanishing, or newly emergent PLMS. Periodic limb movements in sleep related to A1 subtype of CAP were observed to decrease under positive airway pressure titration more than PLMS related to A3 subtype of CAP. The A3 subtype of CAP was higher in patients with vanishing PLMS than those with newly emergent PLMS. The newly emergent PLMS were mostly related to A1 subtype of CAP compared with A3 subtype of CAP. This study showed that vanishing, nonvanishing, or newly emerging PLMS may indeed represent different underlying pathophysiology. The authors suggest that organization of sleep and preservation of ultradian rhythms during titration may determine whether PLMS will be vanished or persist. Newly emergent PLMS may probably arise from a separate central generator by the activation of higher cortical areas.

Pediatric restless legs syndrome and periodic limb movement disorder: Parent–child pairs