Sleep-related leg movements in obstructive sleep apnea: definitions, determinants, and clinical consequences

Obstructive sleep apnea and periodic limb movement in children: is there really an association?

PURPOSE

Periodic limb movements (PLMs) can be found isolated or related to other sleep disorders, as Obstructive Sleep Apnea (OSA). Nevertheless, this association was described before the proposal for modification of the World Association of Sleep Medicine (WASM), which incorporated major changes modifying the definition of respiratory-related leg movements (RRLM) so that the relationship between OSA and PLM could be affected.

METHODS

A total of 131 PSG were studied (children with ages from 5 to 12 years old), all referred because of a suspicion of sleep-disordered breathing (65 children were diagnosed of OSA, and 66 presented snoring but no sleep apnea). Leg movements were manually scored according to both 2006 and 2016 WASM/IRLSSG criteria.

RESULTS

According to 2006 WASM rules, statistical differences were found, not only for PLM index (p 0.002), but all indexes. Nevertheless, according to new 2016 WASM rules, no statistical differences were found for PLM index (p 0.677), non-REM PLM index (p 0.299), REM PLM index (P 0.511) or PLM with arousal index (p 0.180), between OSA and non-OSA group. Positive correlation between PLM and RRLM have been found with both set of rules. The percentage of children with PLM>5/h is higher when using the prior PLM scoring criteria developed in 2006 (38.93%) versus the updated PLM scoring criteria (19.08%).

CONCLUSION

The lack of association when using the new WASM/IRLSSG scoring rules together with the absence of a previous clear etiopathology explanation may suggest that the association between OSA and PLM might be indeed overestimated and that, perhaps, it really did not exist.

Temporal association between leg movements and respiratory events in patients with obstructive sleep apnea: description and differences between the AASM and WASM scoring criteria

PURPOSE

To describe the temporal association between leg movements (LMs) and respiratory events in patients with obstructive sleep apnea (OSA), and to quantify the difference in scoring respiratory-related leg movement (RRLM) between the American Academy of Sleep Medicine (AASM) criterion and the criterion recommended by the World Association of Sleep Medicine (WASM).

METHODS

Patients with OSA who presented with > 10 LMs of any type per hour of sleep were included in this study. For each participant, RRLMs were scored using both the AASM criterion and the recommended WASM criterion. The occurrence of LMs in relation to respiratory events and the difference in scoring RRLM between the AASM criterion and the criterion recommended by the WASM were quantified.

RESULTS

In 32 patients enrolled, mean age was 48.1 ± 11.0 years and 78% were men. LMs were significantly more frequent after respiratory events, followed by before respiratory events, and were rare during respiratory events (P < 0.01). Compared with the AASM criterion, more LMs were classified as RRLMs based on the recommended WASM criterion (P = 0.01).

CONCLUSION

LMs are more frequent after respiratory events than before and during respiratory events, and more LMs are scored as RRLMs based on the recommended WASM criterion than based on the AASM criterion.

The accuracy and difference of scoring rules and methods to score respiratory event-related leg movements in obstructive sleep apnea patients

OBJECTIVE

To compare manual scoring: 1) to the American Academy of Sleep Medicine (AASM) auto-scoring rules. 2) to the AASM and World Association of Sleep Medicine (WASM) rules, and evaluate the accuracy of the AASM and WASM for respiratory event-related limb movements (RRLM) in diagnostic and continuous positive airway pressure (CPAP) titration polysomnography (PSG).

METHODS

We retrospectively, re-scored diagnostic and CPAP titration PSGs of 16 patients with obstructive sleep apnea (OSA), using manual re-scoring by the AASM (mAASM) and WASM (mWASM) criteria for RRLM, periodic limb movements during sleep (PLMS), and limb movements (LM), which were compared to auto-scoring by the AASM (aAASM).

RESULTS

In diagnostic PSG, significant differences were found in LMs (p < 0.05), RRLM (p = 0.009) and the mean duration of PLMS sequences (p = 0.013). In CPAP titration PSG, there was a significant difference in RRLM (p = 0.008) and PLMS with arousal index (p = 0.036). aAASM underestimated LM and RRLM, especially in severe OSA. Changes in RRLM and PLMS with arousal index between diagnostic and titration PSG were significantly different between aAASM and mAASM, but there was no significant difference between scoring by mAASM and mWASM. The ratio of PLMS and RRLM changes between diagnostic and CPAP titration PSG was 0.257 in mAASM and 0.293 in mWASM.

CONCLUSIONS

In addition to the overestimation of RRLM by mAASM compared to aAASM, mAASM may also be more sensitive than aAASM in detecting RRLM changes in the titration PSG. Despite intuitive differences in the definition of RRLM between AASM and WASM rules, RRLM results between mAASM and mWASM were not significant and about 30% of RRLMs might be scored as PLMS by both scoring rules.

Should we treat with continuous positive airway pressure severe non-sleepy obstructive sleep apnea individuals without underlying cardiovascular disease?

The majority of the current international obstructive sleep apnea (OSA) guidelines base the recommendation to treat OSA with continuous positive airway pressure (CPAP) on the presence of symptoms (principally, albeit not exclusively on daytime hypersomnolence). In nonsleepy patients, even with severe OSA, controversies remain, as clear evidence supporting CPAP treatment of this subgroup of OSA patients is lacking. However, given the nonnegligible proportion of non-sleepy OSA patients, clinicians often face a serious dilemma since CPAP treatment in these patients may prove to be not cost-effective. Here, we propose a simple three-step-based algorithm that attempts to better phenotype non-sleepy OSA patients prior to reaching a CPAP treatment decision while also considering a series of clinically relevant elements in the process that may improve with CPAP therapy. Such algorithm focuses on the presence of several OSA symptoms that are susceptible to benefit from treatment and also relies on OSA phenotypes that need to be considered in an effort to achieve optimal cardiovascular prevention. Here, we attempt to establish a framework for clinicians who are evaluating severe nonsleepy OSA patients in their practices. However, the algorithm proposal needs to be extensively validated before being systematically implemented in clinical settings.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Computer-assisted analysis of polysomnographic recordings improves inter-scorer associated agreement and scoring times

STUDY OBJECTIVES

To investigate inter-scorer agreement and scoring time differences associated with visual and computer-assisted analysis of polysomnographic (PSG) recordings.

METHODS

A group of 12 expert scorers reviewed 5 PSGs that were independently selected in the context of each of the following tasks: (i) sleep staging, (ii) scoring of leg movements, (iii) detection of respiratory (apneic-related) events, and (iv) of electroencephalographic (EEG) arousals. All scorers independently reviewed the same recordings, hence resulting in 20 scoring exercises per scorer from an equal amount of different subjects. The procedure was repeated, separately, using the classical visual manual approach and a computer-assisted (semi-automatic) procedure. Resulting inter-scorer agreement and scoring times were examined and compared among the two methods.

RESULTS

Computer-assisted sleep scoring showed a consistent and statistically relevant effect toward less time required for the completion of each of the PSG scoring tasks. Gain factors ranged from 1.26 (EEG arousals) to 2.41 (leg movements). Inter-scorer kappa agreement was also consistently increased with the use of supervised semi-automatic scoring. Specifically, agreement increased from Κ = 0.76 to K = 0.80 (sleep stages), Κ = 0.72 to K = 0.91 (leg movements), Κ = 0.55 to K = 0.66 (respiratory events), and Κ = 0.58 to Κ = 0.65 (EEG arousals). Inter-scorer agreement on the examined set of diagnostic indices did also show a trend toward higher Interclass Correlation Coefficient scores when using the semi-automatic scoring approach.

CONCLUSIONS

Computer-assisted analysis can improve inter-scorer agreement and scoring times associated with the review of PSG studies resulting in higher efficiency and overall quality in the diagnosis sleep disorders.

A Comprehensive Review: Computational Models for Obstructive Sleep Apnea Detection in Biomedical Applications

Obstructive sleep apnea (OSA) is a sleep disorder characterized by periodic episodes of partial or complete upper airway obstruction caused by narrowing or collapse of the pharyngeal airway despite ongoing breathing efforts during sleep. Fall in the blood oxygen saturation and cortical arousals are prompted by this reduction in the airflow which lasts for at least 10 seconds. Impaired labor performance, debilitated quality of life, excessive daytime sleepiness, high snoring, and tiredness even after a whole night's sleep are the primary symptoms of OSA. In due course, the long-standing contributions of OSA culminate in hypertension, arrhythmia, cerebrovascular disease, and heart failure. The traditional diagnostic approach of OSA is the laboratory-based polysomnography (PSG) overnight sleep study, which is a tedious and labor-intensive process that exaggerates the discomfort to the patient. With the advent of computer-aided diagnosis (CAD), automatic detection of OSA has gained increasing interest among researchers in the area of sleep disorders as it influences both diagnostic and therapeutic decisions. The research literature on sleep apnea published during the last decade has been surveyed, focusing on the varied screening approaches accustomed to identifying OSA events and the developmental knowledge offered by multiple contributors from the software perspective. The current study presents an overview of the pathophysiology of OSA, the detection methods, physiological signals related to OSA, the different preprocessing, feature extraction, feature selection, and classification techniques employed for the detection and classification of OSA. Consequently, the research challenges and research gaps in the diagnosis of OSA are identified, critically analyzed, and presented in the best possible light.

Periodic limb movements in patients with obstructive sleep apnea syndrome

The aim of the study was to assess the factors associated with periodic limb movements during sleep (PLMS) among obstructive sleep apnea syndrome (OSAS) patients and identify the role of PLMS in patients with OSAS. 303 adult patients with OSAS were included in the study. All patients completed physical examination, Epworth sleepiness scale (ESS), and polysomnography. Diagnosis of PLMS was made if the periodic leg movements index (PLMI) was ≥ 15. Chi-square test, ANOVA, univariate and multivariate logistic regression analyses were conducted to identify factors associated with PLMS among OSAS patients. Statistical analyses were performed with SPSS 26.0 for mac. Statistically significant difference was considered if P value < 0 .05. Among the 303 adult patients with OSAS, 98 patients had significant PLMS and the other 205 had no significant PLMS. Compared with OSAS patients without PLMS, OSAS patient with PLMS were older, had shorter REM duration and greater apnea–hypopnea index (AHI) (P < 0.05). The study suggests that PLMS is a matter of concern among patients with OSAS. A better understanding of the role of PLMS among OSAS patients could be useful in better recognition, intervention and treatment of OSAS.

Different scoring rules for respiratory event-related leg movements: effects on the prevalence of periodic limb movements during sleep and their association with depressive symptoms in patients with obstructive sleep apnea

BACKGROUND

We compared the prevalence of periodic leg movements during sleep (PLMS) according to two different scoring rules of the American Academy of Sleep Medicine (AASM) 2012 and World Association of Sleep Medicine (WASM) 2016 and determined their association with depressed mood in patients with obstructive sleep apnea (OSA).

METHODS

PLMS, defined as a periodic leg movements index of >15, were diagnosed on a diagnostic and continuous positive airway pressure (CPAP) titration polysomnography using the AASM 2012 and WASM 2016 rules. The Beck Depression Inventory (BDI) and Epworth Sleepiness Scale (ESS) were used, and multiple regression analyses were performed.

RESULTS

Among 160 OSA patients, the proportion with PLMS scored by the WASM 2016 criteria was significantly higher than that scored by the AASM 2012 criteria in a diagnostic study (20.6% vs. 16.3%, respectively; P = 0.016) but not in CPAP titration study and only in patients with severe OSA. In adjusted models, PLMS were positively associated with BDI scores and a BDI of ≥10 on both diagnostic and CPAP titration studies when scored by the WASM 2016. By contrast, when scored by the AASM 2012, PLMS were associated with BDI scores (but not BDI of ≥10) only in a CPAP titration study.

CONCLUSIONS

There are significant differences in the prevalence of PLMS and their association with depressed mood depending on the scoring rules in patients with OSA. The current AASM scoring criteria underestimate the prevalence of PLMS, and PLMS are more likely associated with depressed mood according to the WASM scoring criteria.

Periodic Leg Movements During Sleep

Periodic leg movements during sleep (PLMS) are a frequent finding in nocturnal sleep registrations that include tibialis anterior electromyographic signals. Different PLMS scoring rules exist and can have a major impact on PLMS frequency, which tends to be underappreciated. There is no consistent evidence that frequent PLMS are a causal risk factor for clinically significant outcomes. Several critical open questions are identified that need to be addressed, including but not limited to the consideration of the full range of all sleep-related leg movement activity.

Clinical characteristics of periodic limb movements during sleep categorized by continuous positive airway pressure titration polysomnography in patients with obstructive sleep apnea

PURPOSE

The presence of periodic limb movements during sleep (PLMS) varies among patients with obstructive sleep apnea (OSA) undergoing treatment with continuous positive airway pressure (CPAP). The factors associated with this variation are unknown.

METHODS

PLMS were defined as a periodic leg movements index of > 15/h. Patients with OSA and PLMS were categorized into four groups depending on diagnostic and CPAP titration polysomnography (PSG). A multinomial logistic regression analysis was performed using a non-PLMS group as the reference category.

RESULTS

This study included 861 patients with OSA who underwent a full-night CPAP titration PSG. The proportions of the subjects with PLMS on both PSGs (persistent PLMS), those with CPAP-emergent PLMS, and those with CPAP-resolved PLMS were 12.9%, 9.2%, and 3.9%, respectively. Compared with the non-PLMS group, the persistent group was more likely to be of older age and male sex and has a higher body mass index and restless legs syndrome (RLS). Patients in the CPAP-emergent group were also older and more likely to have RLS as well as more severe apnea. Patients in the CPAP-resolved group were more likely to be women, of older age, have a higher body mass index, but less severe apnea.

CONCLUSIONS

PLMS elicited by CPAP are more likely to occur in older patients with more severe sleep apnea and comorbid RLS, whereas OSA patients in which PLMS resolve after CPAP are more likely to be women and have milder sleep apnea. Persistent PLMS share clinical characteristics with PLMS in general population.

Obstructive Sleep Apnea as a Cardiovascular Risk Factor-Beyond CPAP

Patients with obstructive sleep apnea (OSA) experience repetitive partial or complete airway collapse during sleep resulting in nocturnal hypoxia-normoxia cycling, and are at increased cardiovascular risk. The number of apneas and hypopneas indexed per hour of sleep (apnea-hypopnea index) along with the associated intermittent hypoxia predict the increased cardiovascular risk; thus, their attenuation or prevention are objectives of OSA therapy. Continuous positive airway pressure (CPAP) is the gold standard treatment for OSA and, when effective, mitigates the apnea-hypopnea index and hypoxemia. As such, it is reasonable to expect CPAP would decrease cardiovascular risk. However, 3 recent randomized clinical trials of CPAP vs usual care did not show any significant effects of CPAP in attenuating incident cardiovascular events in patients with OSA. In this review, we discuss these studies in addition to potential complementary therapeutic options to CPAP (eg, neurostimulation) and conclude with suggested therapeutic targets for future interventional studies (eg, the autonomic nervous system). Although these areas of research are exciting, they have yet to be tested to any similar degree of rigour as CPAP.