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Diagnostics
Special Issues
Diagnosis and Management of Sleep Disorders
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Diagnosis and Management of Sleep Disorders

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 15780

Special Issue Editors

Prof. Dr. Lino Nobili

E-Mail Website
Guest Editor
1. Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16128 Genova, Italy
2. Child Neuropsychiatry Unit, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Giannina Gaslini, 16147 Genoa, Italy
Interests: sleep medicine; sleep and epilepsy; epilepsy surgery; pediatric sleep medicine
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Raffaele Ferri

E-Mail Website
Guest Editor
Sleep Research Centre, Department of Neurology IC, Oasi ResearchInstitute-IRCCS, 94018 Troina, Italy
Interests: sleep medicine, neurophysiology; neurology; neurosciences

Special Issue Information

Dear Colleagues,

Sleep disorders are a rapidly growing field of scientific and clinical interest. This field developed as an interdisciplinary area and receives contributions from neuroscientists, neurologists, psychiatrists, neuropsychiatrists, pediatricians, pulmonologists, and otolaryngologists.

Sleep disorders are widespread in both adult and pediatric populations and have a significant impact on people’s quality of life. Sleep is involved in many biological processes that play crucial roles in an individual's overall health. Sleep deprivation and sleep disturbances negatively impact several biological functions involving the immune and autonomic nervous systems, inflammation, and metabolism. Sleep alterations or sleep deprivation may lead to cognitive impairments and cause mood changes, hyperactivity, and conduct problems. Moreover, the quality of sleep is crucial to the mechanisms of plasticity and connectivity, as well as the maturation of the brain during life. Therefore, the study of sleep disorders in the pediatric population is also an interesting and growing field of interest. However, the diagnosis of sleep disorders, particularly in children, can be difficult, and their manifestations may be overlooked.

This Special Issue aims to deepen the diagnostic paths of sleep disorders by integrating data from traditional methods of diagnosing sleep disorders with the most innovative approaches. In addition, we aim to increase our knowledge regarding the management of these disorders in both adults and children, including the use of pharmacological and non-pharmacological options. Therefore, we invite colleagues to present original research, case reports and series, and review papers on the diagnosis and management of sleep disorders to advance the diagnostic workup and treatment of sleep disorders in both children and adults.

Prof. Dr. Lino Nobili
Prof. Dr. Raffaele Ferri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Pediatric sleep disorders
  • Insomnia
  • Sleep-related breathing disorders
  • Hypersomnolence
  • Circadian rhythm disorders
  • Parasomnias
  • Sleep-related movement disorders
  • Quantified sleep EEG analysis
  • Narcolepsy.

Published Papers (6 papers)

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Research

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11 pages, 1494 KiB  
Article
National Knowledge-Driven Management of Obstructive Sleep Apnea—The Swedish Approach
by Ludger Grote, Carl-Peter Anderberg, Danielle Friberg, Gert Grundström, Kerstin Hinz, Göran Isaksson, Tarmo Murto, Zarita Nilsson, Jonas Spaak, Göran Stillberg, Karin Söderberg, Åke Tegelberg, Jenny Theorell-Haglöw, Martin Ulander and Jan Hedner
Diagnostics 2023, 13(6), 1179; https://doi.org/10.3390/diagnostics13061179 - 20 Mar 2023
Cited by 2 | Viewed by 3776
Abstract
Introduction: This paper describes the development of “Swedish Guidelines for OSA treatment” and the underlying managed care process. The Apnea Hypopnea Index (AHI) is traditionally used as a single parameter for obstructive sleep apnea (OSA) severity classification, although poorly associated with symptomatology and [...] Read more.
Introduction: This paper describes the development of “Swedish Guidelines for OSA treatment” and the underlying managed care process. The Apnea Hypopnea Index (AHI) is traditionally used as a single parameter for obstructive sleep apnea (OSA) severity classification, although poorly associated with symptomatology and outcome. We instead implement a novel matrix for shared treatment decisions based on available evidence. Methods: A national expert group including medical and dental specialists, nurses, and patient representatives developed the knowledge-driven management model. A Delphi round was performed amongst experts from all Swedish regions (N = 24). Evidence reflecting treatment effects was extracted from systematic reviews, meta-analyses, and randomized clinical trials. Results: The treatment decision in the process includes a matrix with five categories from a “very weak”” to “very strong” indication to treat, and it includes factors with potential influence on outcome, including (A) OSA-related symptoms, (B) cardiometabolic comorbidities, (C) frequency of respiratory events, and (D) age. OSA-related symptoms indicate a strong incitement to treat, whereas the absence of symptoms, age above 65 years, and no or well-controlled comorbidities indicate a weak treatment indication, irrespective of AHI. Conclusions: The novel treatment matrix is based on the effects of treatments rather than the actual frequency of respiratory events during sleep. A nationwide implementation of this matrix is ongoing, and the outcome is monitored in a prospective evaluation by means of the Swedish Sleep Apnea Registry (SESAR). Full article
(This article belongs to the Special Issue Diagnosis and Management of Sleep Disorders)
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15 pages, 1102 KiB  
Article
Guided Internet-Based Cognitive Behavioral Therapy for Insomnia: Prognostic and Treatment-Predictive Factors
by Polina Pchelina, Simone B. Duss, Corrado Bernasconi, Thomas Berger, Tobias Krieger, Claudio L. A. Bassetti and Antoine Urech
Diagnostics 2023, 13(4), 781; https://doi.org/10.3390/diagnostics13040781 - 19 Feb 2023
Cited by 2 | Viewed by 1901
Abstract
Understanding which factors predict the outcome of internet-based cognitive behavioral therapy for insomnia (iCBT-I) may help to tailor this intervention to the patient’s needs. We have conducted a secondary analysis of a randomized, controlled trial comparing a multicomponent iCBT-I (MCT) and an online [...] Read more.
Understanding which factors predict the outcome of internet-based cognitive behavioral therapy for insomnia (iCBT-I) may help to tailor this intervention to the patient’s needs. We have conducted a secondary analysis of a randomized, controlled trial comparing a multicomponent iCBT-I (MCT) and an online sleep restriction therapy (SRT) for 83 chronic insomnia patients. The difference in the Insomnia Severity Index from pre- to post-treatment and from pre-treatment to follow-up at 6 months after treatment was the dependent variable. Prognostic and treatment-predictive factors assessed at baseline were analyzed with multiple linear regression. The shorter duration of insomnia, female gender, high health-related quality of life, and the higher total number of clicks had prognostic value for a better outcome. Other factors were found to be prognostic for outcome at the follow-up assessment: treatment with benzodiazepines, sleep quality, and personal significance of sleep problems. A high level of dysfunctional beliefs and attitudes about sleep (DBAS) was a moderator for better effects in the MCT at post-treatment assessment. Various prognostic factors (e.g., duration of insomnia, gender, or quality of life) may influence the success of treatment. The DBAS scale may be recommended to select patients for MCT rather than SRT. Full article
(This article belongs to the Special Issue Diagnosis and Management of Sleep Disorders)
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9 pages, 876 KiB  
Article
A Machine Learning Approach for Detecting Idiopathic REM Sleep Behavior Disorder
by Maria Salsone, Andrea Quattrone, Basilio Vescio, Luigi Ferini-Strambi and Aldo Quattrone
Diagnostics 2022, 12(11), 2689; https://doi.org/10.3390/diagnostics12112689 - 4 Nov 2022
Cited by 1 | Viewed by 1817
Abstract
Background and purpose: Growing evidence suggests that Machine Learning (ML) models can assist the diagnosis of neurological disorders. However, little is known about the potential application of ML in diagnosing idiopathic REM sleep behavior disorder (iRBD), a parasomnia characterized by a high risk [...] Read more.
Background and purpose: Growing evidence suggests that Machine Learning (ML) models can assist the diagnosis of neurological disorders. However, little is known about the potential application of ML in diagnosing idiopathic REM sleep behavior disorder (iRBD), a parasomnia characterized by a high risk of phenoconversion to synucleinopathies. This study aimed to develop a model using ML algorithms to identify iRBD patients and test its accuracy. Methods: Data were acquired from 32 participants (20 iRBD patients and 12 controls). All subjects underwent a video-polysomnography. In all subjects, we measured the components of heart rate variability (HRV) during 24 h recordings and calculated night-to-day ratios (cardiac autonomic indices). Discriminating performances of single HRV features were assessed. ML models based on Logistic Regression (LR), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) were trained on HRV data. The utility of HRV features and ML models for detecting iRBD was evaluated by area under the ROC curve (AUC), sensitivity, specificity and accuracy corresponding to optimal models. Results: Cardiac autonomic indices had low performances (accuracy 63–69%) in distinguishing iRBD from control subjects. By contrast, the RF model performed the best, with excellent accuracy (94%), sensitivity (95%) and specificity (92%), while XGBoost showed accuracy (91%), specificity (83%) and sensitivity (95%). The mean triangular index during wake (TIw) was the best discriminating feature between iRBD and HC, with 81% accuracy, reaching 84% accuracy when combined with VLF power during sleep using an LR model. Conclusions: Our findings demonstrated that ML algorithms can accurately identify iRBD patients. Our model could be used in clinical practice to facilitate the early detection of this form of RBD. Full article
(This article belongs to the Special Issue Diagnosis and Management of Sleep Disorders)
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10 pages, 1754 KiB  
Article
Obstructive Sleep Apnea and Auditory Dysfunction—Does Snoring Sound Play a Role?
by Chun-Ting Lu, Li-Ang Lee, Guo-She Lee and Hsueh-Yu Li
Diagnostics 2022, 12(10), 2374; https://doi.org/10.3390/diagnostics12102374 - 30 Sep 2022
Cited by 7 | Viewed by 2407
Abstract
The objective of the study was to investigate the relationship between obstructive sleep apnea (OSA) and auditory dysfunction, and to clarify the role of snoring sounds in contributing to auditory dysfunction. A comprehensive assessment of OSA and the auditory system was performed, including [...] Read more.
The objective of the study was to investigate the relationship between obstructive sleep apnea (OSA) and auditory dysfunction, and to clarify the role of snoring sounds in contributing to auditory dysfunction. A comprehensive assessment of OSA and the auditory system was performed, including overnight polysomnography, detection of the intra-ear canal snoring sound energy (SSE), pure tone average (PTA), tinnitus pitch matching, the tinnitus handicap inventory (THI), and the Epworth sleepiness scale (ESS). The patients were identified as having tinnitus if their THI score was higher than zero or their tinnitus pitches were matched to specific frequencies. The median age, body mass index, and apnea–hypopnea index score were 41 years, 26.4 kg/m2, and 29.9 events/h, respectively. Among the 50 participants, 46 (92%) had a normal PTA, and only 4 (8%) patients had mild hearing loss. There was no significant difference in PTA among OSA severities (p = 0.52). Among the 50 participants, 33 patients (66%) were identified as having tinnitus. In the tinnitus group (n = 33), the ESS score (p = 0.01) and intra-ear canal SSE of 851–1500 Hz (p = 0.04) were significantly higher than those in the non-tinnitus group (n = 17). OSA patients with a higher ESS score had a higher risk of tinnitus (odds ratio 1.22 [95% CI: 1.01–1.46]). OSA-related auditory dysfunction emerged in tinnitus rather than in hearing impairment. OSA patients with daytime sleepiness had a higher risk of tinnitus. High-frequency SSE can jeopardize cochlea and is a potential mechanism contributing to tinnitus. Detection of snoring sounds through an intra-ear canal device may be more precise in assessing acoustic trauma from snoring sounds to vulnerable auditory system and thus warrants further research. Full article
(This article belongs to the Special Issue Diagnosis and Management of Sleep Disorders)
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Review

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12 pages, 2336 KiB  
Review
Problems in the Development of the Sleep–Wake Rhythm Influence Neurodevelopmental Disorders in Children
by Kyoko Hoshino
Diagnostics 2023, 13(11), 1859; https://doi.org/10.3390/diagnostics13111859 - 26 May 2023
Cited by 2 | Viewed by 1775
Abstract
Development of the sleep–wake rhythm has a significant effect on the physical and mental development of children. The sleep–wake rhythm is controlled by aminergic neurons in the brainstem’s ascending reticular activating system, which is associated with synaptogenesis and the promotion of brain development. [...] Read more.
Development of the sleep–wake rhythm has a significant effect on the physical and mental development of children. The sleep–wake rhythm is controlled by aminergic neurons in the brainstem’s ascending reticular activating system, which is associated with synaptogenesis and the promotion of brain development. The sleep–wake rhythm develops rapidly within the first year after birth. At 3–4 months of age, the framework of the circadian rhythm is established. The objective of the present review is to assess a hypothesis concerning problems in the development of the sleep–wake rhythm and their effect on neurodevelopmental disorders. Autism spectrum disorder is characterised by a delay in the development of sleep rhythms at 3–4 months of age and also insomnia and night-time awakenings, as supported by several reports. Melatonin may shorten the sleep latency in ASD. Rett syndrome sufferers kept awake during the daytime were analysed by the Sleep–wake Rhythm Investigation Support System (SWRISS) (IAC, Inc., (Tokyo, Japan)), and the cause was found to be the dysfunction of aminergic neurons. Children and adolescents with attention deficit hyperactivity disorder show sleep problems such as resistance to bedtime, difficulty falling asleep, sleep apnoea, and restless legs syndrome. Sleep deprivation syndrome in schoolchildren is deeply influenced by Internet use, games, and smartphones, and this syndrome affects emotion, learning, concentration, and executive functioning. Sleep disorders in adults are strongly considered to affect not only the physiological/autonomic nervous system but also neurocognitive/psychiatric symptoms. Even adults cannot avoid serious problems, much less children, and the impact of sleep problems is considerably greater in adults. Paediatricians and nurses should be aware of the significance, from birth, of sleep development and sleep hygiene education for carers and parents. This research was reviewed and approved by the ethical committee of the Segawa Memorial Neurological Clinic for Children (No. SMNCC23-02). Full article
(This article belongs to the Special Issue Diagnosis and Management of Sleep Disorders)
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24 pages, 1190 KiB  
Review
Diagnosis and Management of NREM Sleep Parasomnias in Children and Adults
by Greta Mainieri, Giuseppe Loddo, Federica Provini, Lino Nobili, Mauro Manconi and Anna Castelnovo
Diagnostics 2023, 13(7), 1261; https://doi.org/10.3390/diagnostics13071261 - 27 Mar 2023
Cited by 6 | Viewed by 3046
Abstract
Non-rapid eye movement (NREM) sleep parasomnias are recurrent abnormal behaviors emerging as incomplete arousals out of NREM sleep. Mounting evidence on NREM sleep parasomnias calls for an update of clinical and therapeutical strategies. In the current review, we summarize the state of the [...] Read more.
Non-rapid eye movement (NREM) sleep parasomnias are recurrent abnormal behaviors emerging as incomplete arousals out of NREM sleep. Mounting evidence on NREM sleep parasomnias calls for an update of clinical and therapeutical strategies. In the current review, we summarize the state of the art and provide the necessary background to stimulate a critical revision of diagnostic criteria of disorders of arousal (DoA), the most common NREM sleep parasomnia. In particular, we highlight the poor sensitivity of the diagnostic items related to amnesia and absence of conscious experiences during DoA episodes, encourage the role of video-polysomnography and home-video recordings in the diagnostic and treatment work-up, and suggest three levels of diagnostic certainty based on clinical and objective findings. Furthermore, we highlight current gaps of knowledge that prevent the definition of standard guidelines and future research avenues. Full article
(This article belongs to the Special Issue Diagnosis and Management of Sleep Disorders)
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