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Healthcare (Basel, Switzerland) May 2021(1) Background-Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a multifaceted illness characterized by profound and persistent fatigue unrelieved by rest... (Review)
Review
(1) Background-Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a multifaceted illness characterized by profound and persistent fatigue unrelieved by rest along with a range of other debilitating symptoms. Experiences of unrefreshing and disturbed sleep are frequently described by ME/CFS patients. This is the first systematic review assessing sleep characteristics in ME/CFS. The aim of this review is to determine whether there are clinical characteristics of sleep in ME/CFS patients compared to healthy controls using objective measures such as polysomnography and multiple sleep latency testing. (2) Methods-the following databases-Pubmed, Embase, Medline (EBSCO host) and Web of Science, were systematically searched for journal articles published between January 1994 to 19 February 2021. Articles that referred to polysomnography or multiple sleep latency testing and ME/CFS patients were selected, and further refined through use of specific inclusion and exclusion criteria. Quality and bias were measured using the Joanna Briggs Institute checklist. (3) Results-twenty observational studies were included in this review. The studies investigated objective measures of sleep quality in ME/CFS. Subjective measures including perceived sleep quality and other quality of life factors were also described. (4) Conclusions-Many of the parameters measured including slow- wave sleep, apnea- hypopnea index, spectral activity and multiple sleep latency testing were inconsistent across the studies. The available research on sleep quality in ME/CFS was also limited by recruitment decisions, confounding factors, small sample sizes and non-replicated findings. Future well-designed studies are required to understand sleep quality in ME/CFS patients.
PubMed: 34065013
DOI: 10.3390/healthcare9050568 -
Journal of Clinical Medicine Aug 2021Sleep problems have commonly manifested in children and adolescents with autism spectrum disorder (ASD) with a complex and multifactorial interaction between clinical... (Review)
Review
BACKGROUND
Sleep problems have commonly manifested in children and adolescents with autism spectrum disorder (ASD) with a complex and multifactorial interaction between clinical and etiological components. These disorders are associated with functional impairment, and provoke significant physical and mental affliction. The purpose of this study is to update the existing literature about objective and subjective sleep parameters in children and adolescents with ASD, extrapolating information from polysomnography or sleep electroencephalography, and sleep related questionnaires.
METHODS
We have conducted a systematic review of case-control studies on this topic, performing a web-based search on PubMed, Scopus and the Web of Science databases according to the Preferred Reporting items for Systematic Review and Meta-analyses (PRISMA) guidelines.
RESULTS
Data collected from 20 survey result reports showed that children and adolescents with ASD experienced a higher rate of sleep abnormalities than in typically developing children. The macrostructural sleep parameters that were consistent with subjective parent reported measures unveil a greater percentage of nighttime signs of insomnia. Sleep microstructure patterns, in addition, pointed towards the bidirectional relationship between brain dysfunctions and sleep problems in children with ASD.
CONCLUSIONS
Today's literature acknowledges that objective and subjective sleep difficulties are more often recognized in individuals with ASD, so clinicians should assess sleep quality in the ASD clinical population, taking into consideration the potential implications on treatment strategies. It would be worthwhile in future studies to examine how factors, such as age, cognitive level or ASD severity could be related to ASD sleep abnormalities. Future research should directly assess whether sleep alterations could represent a specific marker for atypical brain development in ASD.
PubMed: 34501341
DOI: 10.3390/jcm10173893 -
JMIR MHealth and UHealth Mar 2024Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and... (Review)
Review
BACKGROUND
Despite being the gold-standard method for objectively assessing sleep, polysomnography (PSG) faces several limitations as it is expensive, time-consuming, and labor-intensive; requires various equipment and technical expertise; and is impractical for long-term or in-home use. Consumer wrist-worn wearables are able to monitor sleep parameters and thus could be used as an alternative for PSG. Consequently, wearables gained immense popularity over the past few years, but their accuracy has been a major concern.
OBJECTIVE
A systematic review of the literature was conducted to appraise the performance of 3 recent-generation wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) in determining sleep parameters and sleep stages.
METHODS
Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, a comprehensive search was conducted using the PubMed, Web of Science, Google Scholar, Scopus, and Embase databases. Eligible publications were those that (1) involved the validity of sleep data of any marketed model of the candidate wearables and (2) used PSG or an ambulatory electroencephalogram monitor as a reference sleep monitoring device. Exclusion criteria were as follows: (1) incorporated a sleep diary or survey method as a reference, (2) review paper, (3) children as participants, and (4) duplicate publication of the same data and findings.
RESULTS
The search yielded 504 candidate articles. After eliminating duplicates and applying the eligibility criteria, 8 articles were included. WHOOP showed the least disagreement relative to PSG and Sleep Profiler for total sleep time (-1.4 min), light sleep (-9.6 min), and deep sleep (-9.3 min) but showed the largest disagreement for rapid eye movement (REM) sleep (21.0 min). Fitbit Charge 4 and Garmin Vivosmart 4 both showed moderate accuracy in assessing sleep stages and total sleep time compared to PSG. Fitbit Charge 4 showed the least disagreement for REM sleep (4.0 min) relative to PSG. Additionally, Fitbit Charge 4 showed higher sensitivities to deep sleep (75%) and REM sleep (86.5%) compared to Garmin Vivosmart 4 and WHOOP.
CONCLUSIONS
The findings of this systematic literature review indicate that the devices with higher relative agreement and sensitivities to multistate sleep (ie, Fitbit Charge 4 and WHOOP) seem appropriate for deriving suitable estimates of sleep parameters. However, analyses regarding the multistate categorization of sleep indicate that all devices can benefit from further improvement in the assessment of specific sleep stages. Although providers are continuously developing new versions and variants of wearables, the scientific research on these wearables remains considerably limited. This scarcity in literature not only reduces our ability to draw definitive conclusions but also highlights the need for more targeted research in this domain. Additionally, future research endeavors should strive for standardized protocols including larger sample sizes to enhance the comparability and power of the results across studies.
Topics: Child; Humans; Polysomnography; Reproducibility of Results; Sleep; Fitness Trackers; Wearable Electronic Devices
PubMed: 38557808
DOI: 10.2196/52192 -
Sleep Medicine Reviews Jun 2023This meta-analysis aimed to assess the effectiveness and safety of (adeno)tonsillectomy (AT) for uncomplicated pediatric obstructive sleep apnea (OSA) across different... (Meta-Analysis)
Meta-Analysis Review
This meta-analysis aimed to assess the effectiveness and safety of (adeno)tonsillectomy (AT) for uncomplicated pediatric obstructive sleep apnea (OSA) across different age groups. Four electronic databases were searched until April 2022, and 93 studies (9087 participants) were selected, including before-after studies, cohort studies, and randomized controlled trials. It has been suggested that age, disease severity, and length of follow-up are associated with surgical effects. Compared with older children (>7 years), patients receiving AT surgery before the age of 7 exhibited a significantly greater release of disease severity, as well as a greater decrease in hypoxemic burden, improvement in sleep quality, and better cardiovascular function. Cognitive/behavioral performance also improved after AT, although it was more related to the length of follow-up than the age at surgery. Notably, the surgical complication rate was considerably higher in patients younger than 3 years old. Overall, we suggest that the age of 3-7 years might be optimal for AT in polysomnography-diagnosed uncomplicated OSA to maximize potential benefits for both disease and comorbidities and balance the risks of surgery.
Topics: Child; Humans; Adolescent; Child, Preschool; Tonsillectomy; Sleep Apnea, Obstructive; Polysomnography; Adenoidectomy
PubMed: 37121134
DOI: 10.1016/j.smrv.2023.101782 -
Clinics (Sao Paulo, Brazil) 2024Summarize the evidence on drug therapies for obstructive sleep apnea. (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
Summarize the evidence on drug therapies for obstructive sleep apnea.
METHODS
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. PubMed, Embase, Scopus, Web of Science, SciELO, LILACS, Scopus, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov were searched on February 17th, 2023. A search strategy retrieved randomized clinical trials comparing the Apnea-Hypopnea Index (AHI) in pharmacotherapies. Studies were selected and data was extracted by two authors independently. The risk of bias was assessed using the Cochrane Risk of Bias tool. RevMan 5.4. was used for data synthesis.
RESULTS
4930 articles were obtained, 68 met inclusion criteria, and 29 studies (involving 11 drugs) were combined in a meta-analysis. Atomoxetine plus oxybutynin vs placebo in AHI mean difference of -7.71 (-10.59, -4.83) [Fixed, 95 % CI, I2 = 50 %, overall effect: Z = 5.25, p < 0.001]. Donepezil vs placebo in AHI mean difference of -8.56 (-15.78, -1.33) [Fixed, 95 % CI, I2 = 21 %, overall effect: Z = 2.32, p = 0.02]. Sodium oxybate vs placebo in AHI mean difference of -5.50 (-9.28, -1.73) [Fixed, 95 % CI, I2 = 32 %, overall effect: Z = 2.86, p = 0.004]. Trazodone vs placebo in AHI mean difference of -12.75 (-21.30, -4.19) [Fixed, 95 % CI, I2 = 0 %, overall effect: Z = 2.92, p = 0.003].
CONCLUSION
The combination of noradrenergic and antimuscarinic drugs shows promising results. Identifying endotypes may be the key to future drug therapies for obstructive sleep apnea. Moreover, studies with longer follow-up assessing the safety and sustained effects of these treatments are needed.
PROSPERO REGISTRATION NUMBER
CRD42022362639.
Topics: Humans; Sleep Apnea, Obstructive; Atomoxetine Hydrochloride; Donepezil; Norepinephrine
PubMed: 38341903
DOI: 10.1016/j.clinsp.2024.100330 -
Journal of Clinical Medicine May 2023Although polysomnography is the gold standard method to diagnose obstructive sleep apnea syndrome (OSAS), there is an ongoing quest for simpler and relatively... (Review)
Review
Although polysomnography is the gold standard method to diagnose obstructive sleep apnea syndrome (OSAS), there is an ongoing quest for simpler and relatively inexpensive biomarkers of disease presence and severity. To address this issue, we conducted a systematic review of the potential diagnostic role of the red blood cell distribution width (RDW), a routine hematological parameter of red blood cell volume variability, in OSAS. A total of 1478 articles were initially identified in the databases PubMed, Web of Science, Scopus, Embase, and Google Scholar, from their inception to February 2023, and 20 were selected for final analysis. The RDW was significantly higher in OSAS than in non-OSAS subjects (SMD = 0.44, 95% CI 0.20 to 0.67, < 0.001; low certainty of evidence). In univariate meta-regression, the mean oxygen saturation (SpO) was significantly associated with the effect size. No significant between-group differences were observed in subgroup analyses. Notably, in OSAS subjects, the RDW SMD progressively increased with disease severity. In conclusion, these results suggest that the RDW is a promising biomarker of OSAS (PROSPERO registration number: CRD42023398047).
PubMed: 37176740
DOI: 10.3390/jcm12093302 -
Sensors (Basel, Switzerland) May 2023Sleep is essential to physical and mental health. However, the traditional approach to sleep analysis-polysomnography (PSG)-is intrusive and expensive. Therefore, there... (Review)
Review
Sleep is essential to physical and mental health. However, the traditional approach to sleep analysis-polysomnography (PSG)-is intrusive and expensive. Therefore, there is great interest in the development of non-contact, non-invasive, and non-intrusive sleep monitoring systems and technologies that can reliably and accurately measure cardiorespiratory parameters with minimal impact on the patient. This has led to the development of other relevant approaches, which are characterised, for example, by the fact that they allow greater freedom of movement and do not require direct contact with the body, i.e., they are non-contact. This systematic review discusses the relevant methods and technologies for non-contact monitoring of cardiorespiratory activity during sleep. Taking into account the current state of the art in non-intrusive technologies, we can identify the methods of non-intrusive monitoring of cardiac and respiratory activity, the technologies and types of sensors used, and the possible physiological parameters available for analysis. To do this, we conducted a literature review and summarised current research on the use of non-contact technologies for non-intrusive monitoring of cardiac and respiratory activity. The inclusion and exclusion criteria for the selection of publications were established prior to the start of the search. Publications were assessed using one main question and several specific questions. We obtained 3774 unique articles from four literature databases (Web of Science, IEEE Xplore, PubMed, and Scopus) and checked them for relevance, resulting in 54 articles that were analysed in a structured way using terminology. The result was 15 different types of sensors and devices (e.g., radar, temperature sensors, motion sensors, cameras) that can be installed in hospital wards and departments or in the environment. The ability to detect heart rate, respiratory rate, and sleep disorders such as apnoea was among the characteristics examined to investigate the overall effectiveness of the systems and technologies considered for cardiorespiratory monitoring. In addition, the advantages and disadvantages of the considered systems and technologies were identified by answering the identified research questions. The results obtained allow us to determine the current trends and the vector of development of medical technologies in sleep medicine for future researchers and research.
Topics: Humans; Respiratory Rate; Sleep; Polysomnography
PubMed: 37299762
DOI: 10.3390/s23115038 -
Journal of the Korean Association of... Oct 2022The relationship between obstructive sleep apnea (OSA) and diverse types of pain conditions have been proposed. However, no consensus on the relationship between OSA and... (Review)
Review
The relationship between obstructive sleep apnea (OSA) and diverse types of pain conditions have been proposed. However, no consensus on the relationship between OSA and painful temporomandibular disorders (TMDs) has been established. Therefore, this systematic review has been conducted to review the existing literatures and provide comprehensive synthesis of such literatures about OSA and painful TMDs using the evidence-based methodology. A literature search was conducted using two electronic databases, Scopus, and PubMed. Risk of bias was assessed using the risk-ofbias assessment tool for non-randomized study version 2.0. A total of 158 articles were screened from the initial search and eventually, 5 articles were included in this systematic review. One study adopted both the longitudinal prospective cohort and case-control designs and other 4 articles adopted the cross-sectional design. Two studies employed polysomnography (PSG) for the diagnosis of OSA and mentioned the results from the PSG. All crosssectional studies demonstrated higher OSA prevalence among patients with TMD, and one cohort study suggested OSA as a risk factor for TMD. OSA appears to have potential influences on the development of TMD; however, the role of TMD in the development of OSA remains to be unknown owing to the lack of high-quality evidences.
PubMed: 36316183
DOI: 10.5125/jkaoms.2022.48.5.259 -
Journal of Medical Internet Research Sep 2022American Academy of Sleep Medicine guidelines suggest that clinical prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) without... (Review)
Review
BACKGROUND
American Academy of Sleep Medicine guidelines suggest that clinical prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) without replacing polysomnography, the gold standard.
OBJECTIVE
We aimed to identify, gather, and analyze existing machine learning approaches that are being used for disease screening in adult patients with suspected OSA.
METHODS
We searched the MEDLINE, Scopus, and ISI Web of Knowledge databases to evaluate the validity of different machine learning techniques, with polysomnography as the gold standard outcome measure and used the Prediction Model Risk of Bias Assessment Tool (Kleijnen Systematic Reviews Ltd) to assess risk of bias and applicability of each included study.
RESULTS
Our search retrieved 5479 articles, of which 63 (1.15%) articles were included. We found 23 studies performing diagnostic model development alone, 26 with added internal validation, and 14 applying the clinical prediction algorithm to an independent sample (although not all reporting the most common discrimination metrics, sensitivity or specificity). Logistic regression was applied in 35 studies, linear regression in 16, support vector machine in 9, neural networks in 8, decision trees in 6, and Bayesian networks in 4. Random forest, discriminant analysis, classification and regression tree, and nomogram were each performed in 2 studies, whereas Pearson correlation, adaptive neuro-fuzzy inference system, artificial immune recognition system, genetic algorithm, supersparse linear integer models, and k-nearest neighbors algorithm were each performed in 1 study. The best area under the receiver operating curve was 0.98 (0.96-0.99) for age, waist circumference, Epworth Somnolence Scale score, and oxygen saturation as predictors in a logistic regression.
CONCLUSIONS
Although high values were obtained, they still lacked external validation results in large cohorts and a standard OSA criteria definition.
TRIAL REGISTRATION
PROSPERO CRD42021221339; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=221339.
Topics: Adult; Bayes Theorem; Humans; Machine Learning; Neural Networks, Computer; Polysomnography; Sleep Apnea, Obstructive
PubMed: 36178720
DOI: 10.2196/39452 -
Sleep Medicine Reviews Aug 2022Obstructive Sleep Apnea (OSA) has been recognized as a major health concern worldwide, given its increasing prevalence, difficulties in diagnosis and treatment, and... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Obstructive Sleep Apnea (OSA) has been recognized as a major health concern worldwide, given its increasing prevalence, difficulties in diagnosis and treatment, and impact on health, economy, and society. Clinical guidelines highlight the need of biomarkers to guide OSA clinical decision-making, but so far, without success. In this systematic review and meta-analysis, registered on the International Prospective Register of Systematic Reviews database (ID CRD42020132556), we proposed to gather and further explore candidates identified in the literature as potential OSA biomarkers.
METHODS
Search strategies for eight different databases (PubMed/Medline, Cochrane Library, Biblioteca Virtual da Saúde, Web of Science, EMBASE, World Intellectual Property Organization database, and bioRxiV and medRxiV Preprint Servers) were developed. We identified studies exploring potential biomarkers of OSA, in peripheral samples of adults, with and without OSA, with no comorbidities defined in study inclusion criteria, published after the last systematic review and meta-analysis conducted on OSA biomarkers, until May 31st, 2020. Risk of bias was assessed through the 14-item Quality Assessment Tool for Diagnostic Accuracy Studies. Demographic, clinical, and candidate biomarkers' data were collected and analyzed via random effects meta-analyses.
FINDINGS
Among the 1512 unique studies screened, 120 met the inclusion criteria and 16 studies with low risk of bias were selected for meta-analyses. The selected 16 studies enrolled a total of 2156 participants, from which 1369 were diagnosed with OSA and 787 were disease-free controls. The assessed variables showed high heterogeneity. From the 38 biomarker candidates evaluated, only two were evaluated in more than one study. Most studies pinpointed candidates with more potential for OSA prognosis. ADAM29, FLRT2 and SLC18A3 mRNA levels in PBMCs, Endocan and YKL-40 levels in serum, and IL-6 and Vimentin levels in plasma revealed the most promising candidates for OSA diagnosis.
INTERPRETATION
Although the current systematic review and meta-analysis allowed us to identify candidates to further explore as potential biomarkers in future studies, it is evident that OSA biomarkers research is still at an early stage. Most findings derive from small-size single-center study cohorts and single-candidate studies. We point several gaps in current OSA biomarker research that may guide into new directions and approaches towards the identification of OSA biomarkers.
Topics: Adult; Biomarkers; Humans; Polysomnography; Prevalence; Prognosis; Sleep Apnea, Obstructive
PubMed: 35753150
DOI: 10.1016/j.smrv.2022.101659