PLM detection by actigraphy compared to polysomnography: a validation and comparison of two actigraphs

Fabry disease and sleep disorders: a systematic review

Background

Fabry disease (FD) is an X-chromosome-linked disorder characterized by a reduced or complete absence of the enzyme α-galactosidase, resulting in the accumulation of lysosomal globotriaosylceramide. Despite the presence of these deposits in multiple organs, the problem of sleep disorders within this population has very rarely been documented.

Objective

This study aimed to investigate the types and prevalence of sleep disorders among patients with FD.

Methods

Screening of the following medical databases using key terms was performed on 10 February 2023: PubMed, Scopus, and Embase. A total of 136 records were identified. The quality assessment of the studies was conducted by using tools from the National Institutes of Health (NIH) and critical appraisal tools from the Joanna Briggs Institute (JBI).

Results

The study included nine studies on sleep disorders in patients with FD. The overall quality of the majority of these studies was assessed as either poor or fair. Among 330 patients, there was a slightly higher representation of female patients (56%). Sleep problems manifested 4-5 years after the onset of FD and sometimes even after 10-11 years. Genotypes of disease associated with sleep problems were rarely described. Within the FD population, the most commonly reported conditions were excessive daytime sleepiness (EDS) as well as obstructive and central sleep apnea (OSA, CSA). However, EDS occurred more frequently in FD patients, while the prevalence of OSA and CSA was within the ranges observed in the general population. The studies included indicated a lack of association between organ impairment by primary disease and EDS and OSA. The effectiveness of enzyme replacement therapy (ERT) in treating sleep disorders was not demonstrated.

Conclusion

The findings of this report revealed the presence of many sleep-related disorders within the FD population. However, very few studies on this subject are available, and their limited results make it difficult to truly assess the real extent of the prevalence of sleep disturbances among these individuals. There is a need to conduct further studies on this topic, involving a larger group of patients. It is important to note that there are no guidelines available for the treatment of sleep disorders in patients with FD.

Noninvasive Vagus Nerve Stimulation: A New Therapeutic Approach for Pharmacoresistant Restless Legs Syndrome

AIMS

This work aimed to study the effect of noninvasive vagus nerve stimulation on severe restless legs syndrome (RLS) resistant to pharmacotherapy.

MATERIALS AND METHODS

Patients with severe pharmacoresistant RLS were recruited from a tertiary care sleep center. Intervention was one-hour weekly sessions of transauricular vagus nerve stimulation (tVNS) in the left cymba concha, for eight weeks. The primary outcome measure was the score on the International Restless Legs Rating Scale (IRLS); secondary outcome measures were quality of life (Restless Legs Syndrome Quality of Life scale [RLSQOL]), mood disorders using the Hospital Anxiety and Depression scale subscale for depression (HADD) and Hospital Anxiety and Depression scale subscale for anxiety (HADA), and objective sleep latency, sleep duration, efficiency, and leg movement time measured by actigraphy.

RESULTS

Fifteen patients, 53% male, aged mean 62.7 ± 12.3 years with severe RLS, reduced quality of life, and symptoms of anxiety and depression, were included. The IRLS improved from baseline to session eight: IRLS 31.9 ± 2.9 vs 24.6 ± 5.9 p = 0.0003. Of these participants, 27% (4/15) had a total response with a decrease below an IRLS score of 20; 40% (6/15) a partial response with an improvement in the IRLS > 5 but an IRLS above 20; and 33% (5/15) were nonresponders. After tVNS, quality of life improved (RLSQOL 49.3 ± 18.1 vs 80.0 ± 19.6 p = 0.0005), as did anxiety (HADA 8.9 ± 5.4 vs 6.2 ± 5.0 p = 0.001) and depression (HADD 5.2 ± 4.5 vs 4.0 ± 4.0 p = 0.01). No significant change was found in actigraphic outcome measures.

CONCLUSIONS

In this pilot study, tVNS improved the symptoms of RLS in 66% of participants (10/15) with severe pharmacoresistant RLS, with concomitant improvements in quality of life and mood. Randomized controlled trials evaluating therapeutic efficacy of tVNS in RLS are needed to confirm these promising findings.

Accelerometer-measured physical activity and its impact on sleep quality in patients suffering from restless legs syndrome

BACKGROUND

The primary symptoms of restless legs syndrome (RLS) are sleep onset insomnia and difficulty to maintain sleep. Previous studies have shown that regular physical activity can reduce the risk of developing RLS. However, the relationship between physical activity and sleep quality parameters in individuals suffering from RLS has not yet been investigated by applying accelerometry. Thus, the present study investigates the impact of physical activity (measuring both intensity levels and duration of physical activity) during the day (7-12 h, 12-18 h, 18-23 h) on sleep quality in patients suffering from idiopathic RLS by applying a real-time approach.

METHODS

In a sample of 47 participants suffering from idiopathic RLS, physical activity and sleep quality were measured over one week using accelerometers. For data analysis, physical activity levels and step counts during three periods of the day (morning, afternoon, evening) were correlated with sleep quality parameters of the subsequent night.

RESULTS

This observational study revealed that in most instances physical activity was not correlated with sleep parameters (two exceptions exist: steps taken in the morning were negatively correlated with periodic leg movements during sleep, and physical activity in the evening was negatively correlated with total sleep time). The physical activity levels of the participants in this study, however, were unexpectedly high compared to population-level data and variance in physical activity was low. The average activity was 13,817 (SD = 4086) steps and 347 (SD = 117) minutes of moderate physical activity per day in females, and 10,636 (SD = 3748) steps and 269 (SD = 69) minutes of moderate physical activity in males, respectively. Participants did not engage in any vigorous physical activity.

CONCLUSIONS

Further interventional studies are needed to investigate the daily effects of different intensities of physical activity on RLS symptoms.

[Restless legs syndrome in Parkinson's disease]

Disturbances in sleep and wakefulness are important symptoms of Parkinson's disease (PD) and are associated with negative effects on patients' quality of life. The analysis of literature on the relationship between RLS and PD revealed three main hypotheses explaining the relatively high incidence of RLS in PD: (1) RLS can be considered as an early (prodromal) manifestation or a predictor of PD that can outpace its main symptoms by several years (by analogy with conduct disorder during sleep with REM); (2) the high incidence of RLS in the advanced stage of PD may be associated with augmentation of previously latent RLS symptoms during prolonged dopaminergic therapy of PD; (3) a significant proportion of RLS cases in PD patients are not «classical» RLS, but represent, for example, manifestations of motor or non-motor fluctuations or a special form of stereotypy in the legs. Further research is needed to determine if any of these statements are true.

Actigraphic detection of periodic limb movements: development and validation of a potential device-independent algorithm. A proof of concept study

STUDY OBJECTIVES

We propose a unique device-independent approach to analyze long-term actigraphy signals that can accurately quantify the severity of periodic limb movements in sleep (PLMS).

METHODS

We analyzed 6-8 hr of bilateral ankle actigraphy data for 166 consecutively consenting patients who simultaneously underwent routine clinical polysomnography. Using the proposed algorithm, we extracted 14 time and frequency features to identify PLMS. These features were then used to train a Naïve-Bayes learning tool which permitted classification of mild vs. severe PLMS (i.e. periodic limb movements [PLM] index less than vs. greater than 15 per hr), as well as classification for four PLM severities (i.e. PLM index < 15, between 15 and 29.9, between 30 and 49.9, and ≥50 movements per hour).

RESULTS

Using the proposed signal analysis technique, coupled with a leave-one-out cross-validation method, we obtained a classification accuracy of 89.6%, a sensitivity of 87.9%, and a specificity of 94.1% when classifying a PLM index less than vs. greater than 15 per hr. For the multiclass classification for the four PLM severities, we obtained a classification accuracy of 85.8%, with a sensitivity of 97.6%, and a specificity of 84.8%.

CONCLUSIONS

Our approach to analyzing long-term actigraphy data provides a method that can be used as a screening tool to detect PLMS using actigraphy devices from various manufacturers and will facilitate detection of PLMS in an ambulatory setting.

Extracellular vesicles reveal abnormalities in neuronal iron metabolism in restless legs syndrome

STUDY OBJECTIVES

Determine abnormalities in levels of iron-management proteins in neuronal origin-enriched extracellular vesicles (nEVs) in restless legs syndrome (RLS).

METHODS

We used immunoprecipitation for neuronal marker L1CAM to isolate nEVs from the serum of 20 participants with RLS from a study including magnetic resonance imaging (MRI) determinations of iron deposition in the substantia nigra and hematologic parameters and 28 age- and sex-matched Controls.

RESULTS

RLS compared with Control participants showed higher levels of nEV total ferritin but similar levels of transferrin receptor and ferroportin. Western blot analysis showed that heavy- but not light-chain ferritin was increased in nEVs of RLS compared with Control participants. In RLS but not Control participants, nEV total ferritin was positively correlated with systemic iron parameters; the two groups also differed in the relation of nEV total ferritin to MRI measures of iron deposition in substantia nigra.

CONCLUSIONS

Given the neuronal origin and diversity of EV cargo, nEVs provide an important platform for exploring the underlying pathophysiology and possible biomarkers of RLS.

Utility of the Sleep Disorders Inventory for Students in Clinically Referred Youth With Insomnia: Risk Identification and Relationship With Polysomnographic Measures

Objective/Background: This study evaluated the overall performance of the Sleep Disorders Inventory for Students (SDIS) in identifying sleep disorders risk and the sensitivity and specificity of specific SDIS subscales in a clinically referred sample of youth with insomnia. Participants: Youth (N = 1,329, M = 2.5-18.99 years) with insomnia, of whom 392 underwent clinically indicated diagnostic PSG within ± 6 months of SDIS screening. Methods: Risk identification for sleep disturbance warranting sleep specialist evaluation was determined based on elevation on any SDIS scale for the entire sample. Patients with obstructive sleep apnea (OSA) and periodic limb movement disorder (PMLD) based on PSG were evaluated in relation to SDIS-OSA and SDIS-PLMD subscales (T-scores ≥ 60), with sensitivity, specificity, and receiver operator characteristic curves computed. Results: Clinical elevation correctly identified 74.0% to 83.6% referred to a sleep specialist. Nearly 30% of the subsample undergoing PSG met criteria for OSA and 20.2% had PLMs. The SDIS-OSA subscale demonstrated low to fair sensitivity and specificity. The SDIS-PLMD subscale displayed low sensitivity and low (children) to fair (adolescents) specificity, with the area under the curve suggesting good classification accuracy for adolescents. Conclusions: The SDIS performed well in identifying overall sleep disturbance risk in a large pediatric insomnia sample, suggesting careful examination of all subscales and total score to increase confidence in referral to a sleep specialist. Sensitivity and specificity indices highlight challenges in identifying primary sleep disorder risk and raise potential research questions regarding measurement of parent perceptions in children with insomnia. Additional research in nationally representative samples is warranted.

Contactless detection of periodic leg movements during sleep: A 3D video pilot study

In clinical practice, the quality of polysomnographic recordings in children and patients with neurodegenerative diseases may be affected by sensor displacement and diminished total sleep time due to stress during the recording. In the present study, we investigated if contactless three‐dimensional (3D) detection of periodic leg movements during sleep was comparable to polysomnography. We prospectively studied a sleep laboratory cohort from two Austrian sleep laboratories. Periodic leg movements during sleep were classified according to the standards of the World Association of Sleep Medicine and served as ground truth. Leg movements including respiratory‐related events (A1) and excluding respiratory‐related events (A2 and A3) were presented as A1, A2 and A3. Three‐dimensional movement analysis was carried out using an algorithm developed by the Austrian Institute of Technology. Fifty‐two patients (22 female, mean age 52.2 ± 15.1 years) were included. Periodic leg movement during sleep indexes were significantly higher with 3D detection compared to polysomnography (33.3 [8.1–97.2] vs. 30.7 [2.9–91.9]: +9.1%, p = .0055/27.8 [4.5–86.2] vs. 24.2 [0.00–88.7]: +8.2%, p = .0154/31.8 [8.1–89.5] vs. 29.6 [2.4–91.1]: +8.9%, p = .0129). Contactless automatic 3D analysis has the potential to detect restlessness mirrored by periodic leg movements during sleep reliably and may especially be suited for children and the elderly.

Impact of transcutaneous electrical nerve stimulation on sleep in chronic low back pain: a real-world retrospective cohort study

Objective

The purpose of this study was to determine if transcutaneous electrical nerve stimulation (TENS) improves sleep in chronic low back pain (CLBP).

Background

There is uncertainty over the effectiveness of TENS in CLBP. In most studies, pain intensity has been the primary outcome measure. Although sleep abnormalities are common in CLBP, sleep outcomes have not been evaluated in most studies of TENS effectiveness. Subjective and objective sleep measures are often inconsistent in CLBP, suggesting that perception of sleep and actual sleep may differ.

Methods

This retrospective cohort study evaluated TENS for CLBP over 10 weeks. The source database included demographics, pain characteristics, pain intensity and interference on an 11-point numerical rating scale, adherence and actigraphic sleep data from real-world TENS users. Key inclusion criteria were CLBP with self-reported history of back injury and baseline pain interference with sleep ≥4. Study participants were stratified into improved and unimproved groups based on changes in pain interference with sleep (improved ≥1-point decrease). Actigraphic sleep metrics were compared between the two groups for weeks 1–2 and weeks 9–10.

Results

The inclusion criteria were met by 554 TENS users. There were 282 (50.9%) participants in the improved group and 272 (49.1%) in the unimproved group. The two groups had similar baseline characteristics and high TENS adherence. At the weeks 1–2 assessment, there were no differences among actigraphic sleep. At the weeks 9–10 assessment, there was a difference in total sleep time, with the improved group sleeping 29 minutes longer. In addition, the periodic leg movement (PLM) index was lower in the improved group.

Conclusion

Regular TENS improved self-reported and objective sleep measures in individuals with CLBP. When compared to the unimproved group, the improved group had longer total sleep time and fewer PLMs. Sleep may be an important outcome for TENS effectiveness in CLBP.

A Device-Independent Efficient Actigraphy Signal-Encoding System for Applications in Monitoring Daily Human Activities and Health

Actigraphs for personalized health and fitness monitoring is a trending niche market and fit aptly in the Internet of Medical Things (IoMT) paradigm. Conventionally, actigraphy is acquired and digitized using standard low pass filtering and quantization techniques. High sampling frequencies and quantization resolution of various actigraphs can lead to memory leakage and unwanted battery usage. Our systematic investigation on different types of actigraphy signals yields that lower levels of quantization are sufficient for acquiring and storing vital movement information while ensuring an increase in SNR, higher space savings, and in faster time. The objective of this study is to propose a low-level signal encoding method which could improve data acquisition and storage in actigraphs, as well as enhance signal clarity for pattern classification. To further verify this study, we have used a machine learning approach which suggests that signal encoding also improves pattern recognition accuracy. Our experiments indicate that signal encoding at the source results in an increase in SNR (signal-to-noise ratio) by at least 50⁻90%, coupled with a bit rate reduction by 50⁻80%, and an overall space savings in the range of 68⁻92%, depending on the type of actigraph and application used in our study. Consistent improvements by lowering the quantization factor also indicates that a 3-bit encoding of actigraphy data retains most prominent movement information, and also results in an increase of the pattern recognition accuracy by at least 10%.

Use of Actigraphy for the Evaluation of Sleep Disorders and Circadian Rhythm Sleep-Wake Disorders: An American Academy of Sleep Medicine Systematic Review, Meta-Analysis, and GRADE Assessment

INTRODUCTION

The purpose of this systematic review is to provide supporting evidence for a clinical practice guideline on the use of actigraphy.

METHODS

The American Academy of Sleep Medicine commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies that compared the use of actigraphy, sleep logs, and/or polysomnography. Statistical analyses were performed to determine the clinical significance of using actigraphy as an objective measure of sleep and circadian parameters. Finally, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence for making recommendations.

RESULTS

The literature search resulted in 81 studies that met inclusion criteria; all 81 studies provided data suitable for statistical analyses. These data demonstrate that actigraphy provides consistent objective data that is often unique from patient-reported sleep logs for some sleep parameters in adult and pediatric patients with suspected or diagnosed insomnia, circadian rhythm sleep-wake disorders, sleep-disordered breathing, central disorders of hypersomnolence, and adults with insufficient sleep syndrome. These data also demonstrate that actigraphy is not a reliable measure of periodic limb movements in adult and pediatric patients. The task force provided a detailed summary of the evidence along with the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use considerations.

Agreement between sleep diary and actigraphy in a highly educated Brazilian population

OBJECTIVE

This study evaluated the agreement between a sleep diary and actigraphy on the assessment of sleep parameters among school teachers from Brazil.

METHODS

A total of 163 teachers (66.3% women; aged 45 ± 9 years) filled out a sleep diary and wore a wrist actigraph device for seven consecutive days. Data were collected from August 2014 to March 2015 in Londrina, a large city in southern Brazil. Intraclass correlation coefficients (ICC) and Pearson correlation coefficients (r) were used to compare self-reported and actigraphic data.

RESULTS

Self-reported total sleep time (TST), sleep onset latency (SOL), and sleep efficiency were higher than measured by actigraphy (mean difference: 22.6 ± 46.9 min, 2.6 ± 13.3 min, and 7.3± 5.7%, respectively). Subjective total time in bed (TIB) and wake-up time were lower than measured by actigraphy (mean difference: -10.7 ± 37.6 and -19.7 ± 29.6, respectively). Moderate or good agreement and correlation were found between the sleep diary and the actigraphic data for TST (ICC = 0.70; r = 0.60), TIB (ICC = 0.83; r = 0.73), bedtime (ICC = 0.95; r = 0.91), sleep start time (ICC = 0.94; r = 0.88), and wake-up time (ICC = 0.87; r = 0.78). However, SOL (ICC = 0.49; r = 0.38) and sleep efficiency (ICC = 0.16; r = 0.22) showed only fair or poor agreement and correlation.

CONCLUSION

In this highly educated population, the sleep diary and the actigraphy showed moderate or good agreement to assess several sleep parameters. However, these methods seemed to measure different dimensions of sleep regarding sleep onset latency and efficiency. These findings moderately varied according to the individual's subjective sleep quality.

Validation of a leg movements count and periodic leg movements analysis in a custom polysomnography system

BACKGROUND

Periodic leg movements (PLM) during sleep (PLMS) are considered strongly related to restless legs syndrome (RLS), and are associated with polymorphisms in RLS risk genes. Various software for automatic analysis of PLMS are available, but only few of them have been validated. Aim of this study was to validate a leg movements count and analysis integrated in a commercially available polysomnography (PSG) system against manual scoring.

METHODS

Twenty RLS patients with a PLMS index > 20/h and 20 controls with a PLMS index < 5/h were included. Manual and computerized scoring of leg movements (LM) and PLM was performed according to the standard American Academy of Sleep Medicine (AASM) criteria. LM and PLM indices during sleep and wakefulness, the rate of PLMS associated with respiratory events, intermovement interval and periodicity indices were manually and automatically scored.

RESULTS

The correlation between manual and computerized scoring was high for all investigated parameters (Spearman correlation coefficients 0.751-0.996, p < 0.001; intraclass correlation coefficients 0.775-0.999, p < 0.001). Bland-Altman plots showed high agreement between manual and automatic analysis.

CONCLUSIONS

This study validated an automatic LM count and PLM analysis against the gold standard manual scoring according to AASM criteria. The data demonstrate that the software used in this study has an outstanding performance for computerized LM and PLM scoring, and LM and PLM indices generated with this software can be reliably integrated in the routine PSG report. This automatic analysis is also an excellent tool for research purposes.

Advanced signal analysis for the detection of periodic limb movements from bilateral ankle actigraphy

Actigraphy can assist in the detection of periodic limb movements in sleep. Although several actigraphs have been previously reported to accurately detect periodic limb movements, many are no longer available; of the existing actigraphs, most sample too infrequently to accurately detect periodic limb movements. The purpose of this study was to use advanced signal analysis to validate a readily available actigraph that has the capability of sampling at relatively high frequencies. We simultaneously recorded polysomnography and bilateral ankle actigraphy in 96 consecutive patients presenting to our sleep laboratory. After pre-processing and conditioning, the bilateral ankle actigraphy signals were then analysed for 14 simple time, frequency and morphology-based features. These features reduced the signal dimensionality and aided in better representation of the periodic limb movement activity in the actigraph signals. These features were then processed by a Naïve-Bayes binary classifier for distinguishing between normal and abnormal periodic limb movement indices. We trained the Naïve-Bayes classifier using a training set, and subsequently tested its classification accuracy using a testing set. From our experiments, using a periodic limb movement index cut-off of 5, we found that the Naïve-Bayes classifier had a correct classification rate of 78.9%, with a sensitivity of 80.3% and a specificity of 73.7%. The algorithm developed in this study has the potential of facilitating identification of periodic limb movements across a wide spectrum of patient populations via the use of bilateral ankle actigraphy.

MATPLM1, A MATLAB script for scoring of periodic limb movements: preliminary validation with visual scoring

BACKGROUND AND PURPOSE

A Matrix Laboratory (MATLAB) script (MATPLM1) was developed to rigorously apply World Associations of Sleep Medicine (WASM) scoring criteria for periodic limb movements in sleep (PLMS) from bilateral electromyographic (EMG) leg recordings. This study compares MATPLM1 with both standard technician and expert detailed visual PLMS scoring.

METHODS AND SUBJECTS

Validation was based on a 'macro' level by agreement for PLMS/h during a night recording and on a 'micro' level by agreement for the detection of each PLMS from a stratified random sample for each subject. Data available for these analyses were from 15 restless leg syndrome (RLS) (age: 61.5 ± 8.5, 60% female) and nine control subjects (age: 61.4 ± 7.1, 67% female) participating in another study.

RESULTS

In the 'micro' analysis, MATPLM1 and the visual detection of PLMS events agreed 87.7% for technician scoring and 94.4% for expert scoring. The technician and MATPLM1 scoring disagreements were checked for 36 randomly selected events, 97% involved clear technician-scoring error. In the 'macro' analysis, MATPLM1 rates of PMLS/h correlated highly with visual scoring by the technician (r(2) = 0.97) and the expert scorer (r(2) = 0.99), but the technician scoring was consistently less than MATPLM1: median (quartiles) difference: 10 (5, 23). There was little disagreement with expert scorer [median (quartile) difference: -0.3 (-2.4, 0.3)].

CONCLUSIONS

The MATPLM1 produces reliable scoring of PLMS that matches expert scoring. The standard visual scoring without careful measuring of events tends to significantly underscore PLMS. These preliminary results support the use of MATPLM1 as a preferred method of scoring PLMS for EMG recordings that are of a good quality and without significant sleep-disordered breathing events.

Treatment of Insomnia, Insomnia Symptoms, and Obstructive Sleep Apnea During and After Menopause: Therapeutic Approaches

Understanding sleep complaints among menopausal women is an emerging area of clinical and research interest. Several recent reviews have focused on mechanisms of menopausal insomnia and symptoms. In this review, we present a discussion on the most relevant and recent publications on the treatment of sleep disorders for menopausal women, with a focus on menopause-related insomnia, insomnia symptoms, and obstructive sleep apnea. We discuss both nonpharmacological and pharmacological treatments, including cognitive-behavioral therapy for insomnia (CBT-I), complementary and alternative medicine, hormone replacement therapy, sedative hypnotics, antidepressants, and continuous positive airway pressure. In addition, we briefly discuss methods and considerations of assessment of sleep disorders in menopausal women.

Increased nocturnal periodic limb movements in rheumatoid arthritis patients meeting questionnaire diagnostic criteria for restless legs syndrome

BACKGROUND

Based on questionnaire criteria, the sensorimotor disorder restless legs syndrome (RLS) has been reported to have a higher prevalence in rheumatoid arthritis (RA) patients than in the general population. There has been some speculation that peripheral arthritic symptoms may allow false positive responses to questionnaire criteria. This study evaluates whether RA patients meeting RLS questionnaire criteria also have objective evidence of increased periodic limb movements (PLMs) characteristic of RLS.

METHODS

Participants were recruited from RA clinic. Questionnaire data collected at study entry included: pain scores, rheumatoid arthritis disease activity index, Epworth sleepiness scale, Pittsburgh sleep quality index and RLS diagnostic criteria. Each participant was provided a PAM-RL actigraphic monitor, which attached to the ankle. This device was worn for two consecutive nights then returned for data download. Laboratory data including hemoglobin, iron studies, renal function and C-reactive protein levels were collected.

RESULTS

Of the 57 participants, 23 met RLS diagnostic criteria. Those who met RLS criteria demonstrated higher mean frequency of nocturnal PLMs (19.63/hour; SD:21.13) than those who did not meet RLS criteria (11.13/hour; SD:12.10; p=0.033). There were no significant differences between groups in terms of patient characteristics, disease activity or duration measures. Patients meeting RLS criteria did have poorer sleep quality measures (p <0.001).

CONCLUSIONS

RA patients who met RLS diagnostic criteria demonstrated higher frequencies of nocturnal PLMs than RA patients who did not meet criteria for RLS. This finding supports use of the RLS diagnostic criteria in helping to differentiate between RA arthritic symptoms and RLS.

Leg actigraphy to quantify periodic limb movements of sleep: a systematic review and meta-analysis

Periodic limb movements of sleep (PLMS) are repetitive, stereotyped movements that can disrupt sleep and result in insomnia, non-restorative sleep, and/or daytime sleepiness. Currently, polysomnography is the gold standard and only clinically acceptable means of quantifying PLMS. Leg-worn actigraphy is an alternative method of measuring PLMS, which may circumvent many of the economic and technical limitations of polysomnography to quantify nocturnal leg movements. However, the use of leg actigraphy as a diagnostic means of assessing PLMS has not been systematically evaluated. In this review, the use of leg-worn actigraphy to measure PLMS is systematically evaluated, using both qualitative and quantitative assessment. Findings demonstrate significant heterogeneity among a limited number of studies in terms of type of actigraph utilized, position of the device on the lower extremity, and methods employed to count PLMS. In general, common accelerometers vary in their sensitivity and specificity to detect PLMS, which is likely related to the technical specifications of a given device. A current limitation in the ability to combine data from actigraphs placed on both legs is also a significant barrier to their use in clinical settings. Further research is required to determine the optimal methods to quantify PLMS using leg actigraphy, as well as specific clinical situations in which these devices may prove most useful.

Valid measures of periodic leg movements (PLMs) during a suggested immobilization test using the PAM-RL leg activity monitors require adjusting detection parameters for noise and signal in each recording

OBJECTIVE AND BACKGROUND

Individuals with restless legs syndrome (RLS) (Willis-Ekbom disease [WED]) usually have periodic leg movements (PLMs). The suggested immobilization test (SIT) measures sensory and motor features of WED during wakefulness. Surface electromyogram (EMG) recordings of the anterior tibialis (AT) are used as the standard for counting PLMs. However, due to several limitations, leg activity meters such as the PAM-RL were advanced as a potential substitute. In our study, we assessed the validity of the measurements of PLM during wakefulness (PLMW) in the SIT for PAM-RL using both default and custom detection threshold parameters compared to AT EMG.

METHODS

Data were obtained from 39 participants who were diagnosed with primary WED and who were on stable medication as part of another study using the SIT to repeatedly evaluate WED symptoms over 6-12 months. EMG recordings and PAM-RL, when available, were used to detect PLMW for each SIT. Complete PAM-RL and polysomnography (PSG) EMG data were available for 253 SITs from that study. The default PAM-RL (dPAM-RL) detected leg movements based on manufacturer's noise (resting) and signal (movement) amplitude criteria developed to accurately detect PLM during sleep (PLMS). The custom PAM-RL (cPAM-RL) similarly detected leg movements except the noise and movement detection parameters were adjusted to match the PAM-RL data for each SIT.

RESULTS

The distributions of the differences between either dPAM-RL or cPAM-RL and EMG PLMW were strongly leptokurtic (Kurtosis >2) with many small differences and a few unusually large differences. These distributions are better described by median and quartile ranges than mean and standard deviation. Despite an adequate correlation (r=0.66) between the dPAM-RL and EMG recordings, the dPAM-RL on average significantly underscored the number of PLMW (median: quartiles=-13: -51.2, 0.0) and on Bland-Altman plots had a significant magnitude bias with greater underscoring for larger average PLMW/h. There also was an adequate correlation (r=0.70) between cPAM-RL and EMG but with minimal underscoring of PLMW (median quartiles=0.0; -20, 10) and no significant magnitude bias. Two scorers independently scoring 13% of the SITs showed an adequate interscorer reliability of 0.96-0.98.

CONCLUSIONS

Our study confirms our expectation that measuring PLMW in a SIT using dPAM-RL is not valid and that adjustments to the detection threshold criteria are required. The PAM-RL, using parameters customized for each SIT provided a valid and reliable measure of PLMW with minimal magnitude bias compared to the AT EMG recordings.

Measuring leg movements during sleep using accelerometry: comparison with EMG and piezo-electric scored events

Periodic Limb Movements during Sleep (PLMS) can cause significant disturbance to sleep, resulting in daytime sleepiness and reduced quality of life. In conventional clinical practice, PLMS are measured using overnight electromyogram (EMG) of the tibialis anterior muscle, although historically they have also been measured using piezo-electric gauges placed over the muscle. However, PLMS counts (PLM index) do not correlate well with clinical symptomology. In this study, we propose that because EMG and piezo derived signals measure muscle activation rather than actual movement, they may count events with no appreciable movement of the limb and therefore no contribution to sleep disturbance. The aim of this study is thus to determine the percentage of clinically scored limb movements which are not associated with movement of the great toe measured using accelerometry. 9 participants were studied simultaneously with an overnight diagnostic polysomnogram (including EMG and piezo instrumentation of the right leg) and high temporal resolution accelerometry of the right great toe. Limb movements were scored, and peak acceleration during each scored movement was quantified. Across the participant population, 54.9% (range: 26.7-76.3) and 39.0% (range: 4.8-69.6) of limb movements scored using piezo and EMG instrumentation respectively, were not associated with toe movement measured with accelerometry. If sleep disturbance is the consequence of the limb movements, these results may explain why conventional piezo or EMG derived PLMI is poorly correlated with clinical symptomology.

Validation of the Multiple Suggested Immobilization Test: A Test for the Assessment of Severity of Restless Legs Syndrome (Willis-Ekbom Disease)

STUDY OBJECTIVES

To validate the Multiple Suggested Immobilization Test (m-SIT), a symptom-provocation test measuring restless legs syndrome (RLS) severity multiple times a day while the patient is awake and resting under controlled conditions. The m-SIT was designed to overcome some limitations in measuring RLS severity with rating scales.

DESIGN

Patients completed two m-SITs on 2 consecutive days while on 24-h dopaminergic medication. After treatment discontinuation, they completed one more m-SIT 3 days later. Controls performed only one m-SIT.

SETTING

Sleep laboratory.

PARTICIPANTS

Nineteen patients with RLS and 10 healthy controls.

INTERVENTIONS

The original m-SIT consisted of seven modified 60-min SITs performed every 2 h between noon and midnight. During each SIT, the subject reclined quietly but could move his or her legs without restriction to alleviate symptoms. Every 10 min, periodic leg movements during wakefulness (PLMW) were evaluated and the m-SIT Disturbance Scale (m-SIT-DS; range 0-10) was completed.

MEASUREMENTS AND RESULTS

The m-SIT, composed of 6:00pm, 8:00pm, 10:00pm, and 12:00pm SITs, discriminated patients from controls (mean m-SIT-DS: 2.68 ± 2.35 versus 0.08 ± 0.26; mean PLMW/h, P = 0.0001) and between treatment groups (on medication versus taken off medication; mean m-SIT-DS, P = 0.0001; mean PLMW/h, P < 0.01). It proved reliable on retest and covariated well with the International Restless Legs Scale (IRLS) and scales measuring daytime symptoms (Spearman ρ > 0.4).

CONCLUSIONS

The m-SIT is a valid and reliable test to evaluate RLS severity and treatment response, and could be useful in the future to confirm diagnosis and identify daytime symptoms. Although it was primarily designed for clinical trials, it might be useful in clinical settings because it provides a standardized testing condition to measure RLS symptoms.

CITATION

Garcia-Borreguero D; Kohnen R; Boothby L; Tzonova D; Larrosa O; Dunkl E. Validation of the Multiple Suggested Immobilization Test: a test for the assessment of severity of restless legs syndrome (Willis-Ekbom disease). SLEEP 2013;36(7):1101-1109.

Sleep/wake estimation using only anterior tibialis electromyography data

BACKGROUND

In sleep efficiency monitoring system, actigraphy is the simplest and most commonly used device. However, low specificity to wakefulness of actigraphy was revealed in previous studies. In this study, we assumed that sleep/wake estimation using actigraphy and electromyography (EMG) signals would show different patterns. Furthermore, each EMG pattern in two states (sleep, wake during sleep) was analysed. Finally, we proposed two types of method for the estimation of sleep/wake patterns using only EMG signals from anterior tibialis muscles and the results were compared with PSG data.

METHODS

Seven healthy subjects and five patients (2 obstructive sleep apnea, 3 periodic limb movement disorder) participated in this study. Night time polysomnography (PSG) recordings were conducted, and electrooculogram, EMG, electroencephalogram, electrocardiogram, and respiration data were collected. Time domain analysis and frequency domain analysis were applied to estimate the sleep/wake patterns. Each method was based on changes in amplitude or spectrum (total power) of anterior tibialis electromyography signals during the transition from the sleep state to the wake state. To obtain the results, leave-one-out-cross-validation technique was adopted.

RESULTS

Total sleep time of the each group was about 8 hours. For healthy subjects, the mean epoch-by-epoch results between time domain analysis and PSG data were 99%, 71%, 80% and 0.64 (sensitivity, specificity, accuracy and kappa value), respectively. For frequency domain analysis, the corresponding values were 99%, 73%, 81% and 0.67, respectively. Absolute and relative differences between sleep efficiency index from PSG and our methods were 0.8 and 0.8% (for frequency domain analysis). In patients with sleep-related disorder, our proposed methods revealed the substantial agreement (kappa > 0.61) for OSA patients and moderate or fair agreement for PLMD patients.

CONCLUSIONS

The results of our proposed methods were comparable to those of PSG. The time and frequency domain analyses showed the similar sleep/wake estimation performance.

Sleep and menopause

Understanding sleep complaints of menopausal women is an emerging area of clinical and research interest. In this article, we summarize the most relevant and recent literature to provide an update on sleep in perimenopause and postmenopause. Our discussion includes the causes, clinical diagnosis, and treatment of sleep disorders in perimenopausal and postmenopausal women.