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Diagnostics
Special Issues
Patient Monitoring and Management in Sleep Medicine
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Patient Monitoring and Management in Sleep Medicine

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

Deadline for manuscript submissions: 31 May 2024 | Viewed by 5668

Special Issue Editor

Dr. Wojciech Kukwa

E-Mail Website
Guest Editor
Department of Otorhinolaryngology, Faculty of Dental Medicine, Medical University of Warsaw, 19/25 Stepinska Street, 00-739 Warsaw, Poland
Interests: sleep medicine; obstructive sleep apnea; epidemiological sleep studies; pathophysiology of snoring and sleep apnea
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We spend around a third of our lives sleeping. Still, we do not have any perfect tools to monitor sleep. Polysomnography, which is the gold standard in the study of sleep, is non-physiological and was developed for in-laboratory analyses. Personalized sleep medicine requires comfortable sensors that enable long-term sleep monitoring in the patient’s home. Artificial intelligence, machine learning, big data projects, and the development of new sensors will certainly revolutionize sleep monitoring and sleep disorder management in both children and adults. Studies show that the high night-to-night variability in multiple sleep parameters requires multi-night monitoring processes. Therefore, emerging technologies together with automatic big data analysis give promise for real advancements in monitoring and management in sleep medicine.

The purpose of this Special Issue is to introduce innovative approaches to the process of monitoring and managing sleep and sleep disorders. Original research and review articles, case studies, and research briefs are all welcomed.

Dr. Wojciech Kukwa
Guest Editor

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

  • sleep monitoring
  • obstructive sleep apnea
  • snoring
  • circadian rhythm
  • CPAP
  • sleep/wake cycle
  • restless leg syndrome
  • insomnia
  • narcolepsy

Published Papers (4 papers)

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Research

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12 pages, 2016 KiB  
Article
Relationships between Heart Chamber Morphology or Function and Respiratory Parameters in Patients with HFrEF and Various Types of Sleep-Disordered Breathing
by Karolina Simionescu, Danuta Łoboda, Mariusz Adamek, Jacek Wilczek, Michał Gibiński, Rafał Gardas, Jolanta Biernat and Krzysztof S. Gołba
Diagnostics 2023, 13(21), 3309; https://doi.org/10.3390/diagnostics13213309 - 25 Oct 2023
Cited by 1 | Viewed by 820
Abstract
Sleep-disordered breathing (SDB), i.e., central sleep apnea (CSA) and obstructive sleep apnea (OSA), affects the prognosis of patients with heart failure with reduced ejection fraction (HFrEF). The study assessed the relationships between heart chamber size or function and respiratory parameters in patients with [...] Read more.
Sleep-disordered breathing (SDB), i.e., central sleep apnea (CSA) and obstructive sleep apnea (OSA), affects the prognosis of patients with heart failure with reduced ejection fraction (HFrEF). The study assessed the relationships between heart chamber size or function and respiratory parameters in patients with HFrEF and various types of SDB. The 84 participants were patients aged 68.3 ± 8.4 years (80% men) with an average left ventricular ejection fraction (LVEF) of 25.5 ± 6.85% who qualified for cardioverter-defibrillator implantation with or without cardiac resynchronization therapy. SDB, defined by an apnea–hypopnea index (AHI) ≥ five events/hour, was diagnosed in 76 patients (90.5%); SDB was severe in 31 (36.9%), moderate in 26 (31.0%), and mild in 19 (22.6%). CSA was the most common type of SDB (64 patients, 76.2%). A direct proportional relationship existed only in the CSA group between LVEF or stroke volume (SV) and AHI (p = 0.02 and p = 0.07), and between LVEF or SV and the percentage of total sleep time spent with hemoglobin oxygen saturation < 90% (p = 0.06 and p = 0.07). In contrast, the OSA group was the only group in which right ventricle size showed a positive relationship with AHI (for basal linear dimension [RVD1] p = 0.06), mean duration of the respiratory event (for RVD1 p = 0.03, for proximal outflow diameter [RVOT proximal] p = 0.009), and maximum duration of respiratory event (for RVD1 p = 0.049, for RVOT proximal p = 0.006). We concluded that in HFrEF patients, SDB severity is related to LV systolic function and SV only in CSA, whereas RV size correlates primarily with apnea/hypopnea episode duration in OSA. Full article
(This article belongs to the Special Issue Patient Monitoring and Management in Sleep Medicine)
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13 pages, 2106 KiB  
Article
Automatic Heart Rate Detection during Sleep Using Tracheal Audio Recordings from Wireless Acoustic Sensor
by Julia Zofia Tomaszewska, Marcel Młyńczak, Apostolos Georgakis, Christos Chousidis, Magdalena Ładogórska and Wojciech Kukwa
Diagnostics 2023, 13(18), 2914; https://doi.org/10.3390/diagnostics13182914 - 11 Sep 2023
Viewed by 1207
Abstract
Background: Heart rate is an essential diagnostic parameter indicating a patient’s condition. The assessment of heart rate is also a crucial parameter in the diagnostics of various sleep disorders, including sleep apnoea, as well as sleep/wake pattern analysis. It is usually measured using [...] Read more.
Background: Heart rate is an essential diagnostic parameter indicating a patient’s condition. The assessment of heart rate is also a crucial parameter in the diagnostics of various sleep disorders, including sleep apnoea, as well as sleep/wake pattern analysis. It is usually measured using an electrocardiograph (ECG)—a device monitoring the electrical activity of the heart using several electrodes attached to a patient’s upper body—or photoplethysmography (PPG). Methods: The following paper investigates an alternative method for heart rate detection and monitoring that operates on tracheal audio recordings. Datasets for this research were obtained from six participants along with ECG Holter (for validation), as well as from fifty participants undergoing a full night polysomnography testing, during which both heart rate measurements and audio recordings were acquired. Results: The presented method implements a digital filtering and peak detection algorithm applied to audio recordings obtained with a wireless sensor using a contact microphone attached in the suprasternal notch. The system was validated using ECG Holter data, achieving over 92% accuracy. Furthermore, the proposed algorithm was evaluated against whole-night polysomnography-derived HR using Bland-Altman’s plots and Pearson’s Correlation Coefficient, reaching the average of 0.82 (0.93 maximum) with 0 BPM error tolerance and 0.89 (0.97 maximum) at ±3 BPM. Conclusions: The results prove that the proposed system serves the purpose of a precise heart rate monitoring tool that can conveniently assess HR during sleep as a part of a home-based sleep disorder diagnostics process. Full article
(This article belongs to the Special Issue Patient Monitoring and Management in Sleep Medicine)
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17 pages, 1221 KiB  
Article
Orthodontic and Facial Characteristics of Craniofacial Syndromic Children with Obstructive Sleep Apnea
by Suliman Alsaeed, Nelly Huynh, David Wensley, Kevin Lee, Mona M. Hamoda, Evan Ayers, Kate Sutherland and Fernanda R. Almeida
Diagnostics 2023, 13(13), 2213; https://doi.org/10.3390/diagnostics13132213 - 29 Jun 2023
Viewed by 1538
Abstract
Introduction: Obstructive sleep apnea (OSA) is a disorder in which ventilation becomes disrupted due to a complete or partial upper airway obstruction Altered craniofacial morphology is one of the most important anatomical factors associated with obstructive sleep apnea (OSA). Studies have assessed craniofacial [...] Read more.
Introduction: Obstructive sleep apnea (OSA) is a disorder in which ventilation becomes disrupted due to a complete or partial upper airway obstruction Altered craniofacial morphology is one of the most important anatomical factors associated with obstructive sleep apnea (OSA). Studies have assessed craniofacial features in the non-syndromic pediatric population. The aim of this study was to analyze the orthodontic and facial characteristic of craniofacial syndromic children referred for polysomnography (PSG) and to assess the correlation with the apnea–hypopnea index (AHI). Methods: In the current cross-sectional study, consecutive syndromic patients referred for PSG were invited to participate. A systematic clinical examination including extra- and intra-oral orthodontic examination was performed by calibrated orthodontists. Standardized frontal and profile photographs with reference points were taken and analyzed using ImageJ® software to study the craniofacial morphology. PSG data were analyzed for correlation with craniofacial features. STROBE guidelines were strictly adopted during the research presentation. Results: The sample included 52 syndromic patients (50% females, mean age 9.38 ± 3.36 years) diagnosed with 17 different syndromes, of which 24 patients had craniofacial photography analysis carried out. Most of the sample (40%) had severe OSA, while only 5.8% had no OSA. Down’s syndrome (DS) was the most common syndrome (40%) followed by Goldenhar syndrome (5%), Pierre Robin Sequence (5%), and other syndromes. The severity of AHI was significantly correlated with decreased midfacial height. increased thyromental angle and cervicomental angle, decreased mandibular angle, and decreased upper facial height. All patients with DS were diagnosed with OSA (57% severe OSA), and their ODI was significantly correlated with increased intercanthal distance. Obesity was not correlated to the severity of AHI for syndromic patients. Conclusions: Decreased midfacial height and obtuse thyromental angle were correlated with increased AHI for syndromic patients. Increased intercanthal distance of DS patients could be a major predictor of OSA severity. Obesity does not seem to play a major role in the severity of OSA for syndromic patients. Further studies with larger samples are necessary to confirm these findings. Full article
(This article belongs to the Special Issue Patient Monitoring and Management in Sleep Medicine)
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Review

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14 pages, 320 KiB  
Review
Alternatives to Polysomnography for the Diagnosis of Pediatric Obstructive Sleep Apnea
by Taylor B. Teplitzky, Audrey J. Zauher and Amal Isaiah
Diagnostics 2023, 13(11), 1956; https://doi.org/10.3390/diagnostics13111956 - 3 Jun 2023
Cited by 1 | Viewed by 1564
Abstract
Diagnosis of obstructive sleep apnea (OSA) in children with sleep-disordered breathing (SDB) requires hospital-based, overnight level I polysomnography (PSG). Obtaining a level I PSG can be challenging for children and their caregivers due to the costs, barriers to access, and associated discomfort. Less [...] Read more.
Diagnosis of obstructive sleep apnea (OSA) in children with sleep-disordered breathing (SDB) requires hospital-based, overnight level I polysomnography (PSG). Obtaining a level I PSG can be challenging for children and their caregivers due to the costs, barriers to access, and associated discomfort. Less burdensome methods that approximate pediatric PSG data are needed. The goal of this review is to evaluate and discuss alternatives for evaluating pediatric SDB. To date, wearable devices, single-channel recordings, and home-based PSG have not been validated as suitable replacements for PSG. However, they may play a role in risk stratification or as screening tools for pediatric OSA. Further studies are needed to determine if the combined use of these metrics could predict OSA. Full article
(This article belongs to the Special Issue Patient Monitoring and Management in Sleep Medicine)
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