Identification of major depression patients using machine learning models based on heart rate variability during sleep stages for pre-hospital screening.

With the COVID-19 pandemic causing challenges in hospital admissions globally, the role of home health monitoring in aiding the diagnosis of mental health disorders has become increasingly important. This paper proposes an interpretable machine learning solution to optimise initial screening for major depressive disorder (MDD) in both male and female patients. The data is from the Stanford Technical Analysis and Sleep Genome Study (STAGES). We analyzed 5-min short-term electrocardiogram (ECG) signals during nighttime sleep stages of 40 MDD patients and 40 healthy controls, with a 1:1 gender ratio. After preprocessing, we calculated the time-frequency parameters of heart rate variability (HRV) based on the ECG signals and used common machine learning algorithms for classification, along with feature importance analysis for global decision analysis. Ultimately, the Bayesian optimised extremely randomized trees classifier (BO-ERTC) showed the best performance on this dataset (accuracy 86.32%, specificity 86.49%, sensitivity 85.85%, F1-score 0.86). By using feature importance analysis on the cases confirmed by BO-ERTC, we found that gender is one of the most important factors affecting the prediction of the model, which should not be overlooked in our assisted diagnosis. This method can be embedded in portable ECG monitoring systems and is consistent with the literature results.

Feasibility and parental perception of home sleep studies during COVID-19: a tertiary sleep centre experience.

OBJECTIVE: Rapid implementation of home sleep studies during the first UK COVID-19 'lockdown'-completion rates, family feedback and factors that predict success. DESIGN: We included all patients who had a sleep study conducted at home instead of as inpatient from 30 March 2020 to 30 June 2020. Studies with less than 4 hours of data for analysis were defined 'unsuccessful'. RESULTS: 137 patients were included. 96 underwent home respiratory polygraphy (HRP), median age 5.5 years. 41 had oxycapnography (O2/CO2), median age 5 years. 56% HRP and 83% O2/CO2 were successful. A diagnosis of autism predicted a lower success rate (29%) as did age under 5 years. CONCLUSION: Switching studies rapidly from an inpatient to a home environment is possible, but there are several challenges that include a higher failure rate in younger children and those with neurodevelopmental disorders.

A clinical trial to evaluate the dayzz smartphone app on employee sleep, health, and productivity at a large US employer.

Sleep deficiency is a hidden cost of our 24-7 society, with 70% of adults in the US admitting that they routinely obtain insufficient sleep. Further, it is estimated that 50-70 million adults in the US have a sleep disorder. Undiagnosed and untreated sleep disorders are associated with diminished health for the individual and increased costs for the employer. Research has shown that adverse impacts on employees and employers can be mitigated through sleep health education and sleep disorder screening and treatment programs. Smartphone applications (app) are increasingly commonplace and represent promising, scalable modalities for such programs. The dayzz app is a personalized sleep training program that incorporates assessment of sleep disorders and offers a personalized comprehensive sleep improvement solution. Using a sample of day workers affiliated with a large institution of higher education, we will conduct a single-site, parallel-group, randomized, waitlist control trial. Participants will be randomly assigned to either use the dayzz app throughout the study or receive the dayzz app at the end of the study. We will collect data on feasibility and acceptability of the dayzz app; employee sleep, including sleep behavioral changes, sleep duration, regularity, and quality; employee presenteeism, absenteeism, and performance; employee mood; adverse and safety outcomes; and healthcare utilization on a monthly basis throughout the study, as well as collect more granular daily data from the employee during pre-specified intervals. Our results will illuminate whether a personalized smartphone app is a viable approach for improving employee sleep, health, and productivity. Trial registration: ClinicalTrials.gov Identifier: NCT04224285.

Prevalence of Sleep Disordered Breathing in Children With Myelomeningocele.

BACKGROUND: Retrospective studies have shown high rates of sleep disordered breathing in children with myelomeningocele. However, most patients included in those studies underwent polysomnography because of symptoms, so the prevalence of sleep disordered breathing in this population is unknown. OBJECTIVE: To determine the prevalence of sleep disordered breathing in children with myelomeningocele using screening polysomnography. METHODS: In this cross-sectional study, all children with myelomeningocele seen in a multi-disciplinary spina bifida clinic between 2016 and 2020 were referred for polysomnography regardless of clinical symptoms. Included children had not previously undergone polysomnography. The primary outcome for this study was presence of sleep disordered breathing, defined as Apnea-Hypopnea Index (AHI, number of apnea or hypopnea events per hour of sleep) greater than 2.5. Clinical and demographic variables relevant to myelomeningocele were also prospectively collected and tested for association with presence of sleep apnea. RESULTS: A total of 117 participants underwent polysomnography (age 1 mo to 21 yr, 49% male). The majority were white, non-Hispanic. Median AHI was 1.9 (interquartile range 0.6-4.2). A total of 49 children had AHI 2.5 or greater, yielding a sleep disordered breathing prevalence of 42% (95% CI 33%-51%). In multivariable logistic regression analysis, children with more rostral neurological lesion levels had higher odds of sleep disordered breathing (OR for thoracic, mid-lumbar, and low-lumbar: 7.34, 3.70, 4.04, respectively, compared to sacral level, P = .043). CONCLUSION: Over 40% of a sample of children with myelomeningocele, who underwent screening polysomnography, had significant sleep disordered breathing. Routine screening polysomnography may be indicated in this population.

Rise in nocturnal respiratory rate during CPAP may be an early sign of COVID-19 in patients with obstructive sleep apnea.

None: A middle-aged man with obstructive sleep apnea who had been treated with continuous positive airway pressure developed COVID-19. An analysis of airflow records from the continuous positive airway pressure machine revealed a rise in his respiratory rate on the night before the onset of COVID-19-related symptoms, while his nocturnal respiratory rate had been stable during the 18-month period prior to the presently reported episode. The present case suggests that a rise in respiratory rate detected using continuous positive airway pressure machine data could be an important sign of impending acute illness, such as COVID-19. Studies to elucidate the usefulness of this method are warranted.

Technical Tips: Keeping It Clean during COVID-19.

Since 1995, ASET has periodically published updates to recommendations for best practices in infection prevention for Neurodiagnostic technologists. The latest installment was accepted in December 2019 for publication in Volume 60, Issue 1, before we had much knowledge or understanding about the SARS-CoV-2, the virus that causes COVID-19. This Technical Tips article is presented as an addendum to the 2020 update and includes important information about infection prevention measures specific to procedure protocols when working with patients positive or under investigation for a highly infectious disease, and when working with patients in general during the current pandemic. All Neurodiagnostic technologists who have direct patient care are responsible for ensuring the use of best practices to prevent the spread of infection.

The impact of the COVID-19 pandemic on sleep medicine practices.

STUDY OBJECTIVES: The COVID-19 pandemic required sleep centers to consider and implement infection control strategies to mitigate viral transmission to patients and staff. Our aim was to assess measures taken by sleep centers due to the COVID-19 pandemic and plans surrounding reinstatement of sleep services. METHODS: We distributed an anonymous online survey to health care providers in sleep medicine on April 29, 2020. From responders, we identified a subset of unique centers by region and demographic variables. RESULTS: We obtained 379 individual responses, which represented 297 unique centers. A total of 93.6% of unique centers reported stopping all or nearly all sleep testing of at least one type, without significant differences between adult and pediatric labs, geographic region, or surrounding population density. By contrast, a greater proportion of respondents continued home sleep apnea testing services. A total of 60.3% reduced home sleep apnea testing volume by at least 90%, compared to 90.4% that reduced in-laboratory testing by at least 90%. Respondents acknowledged that they implemented a wide variety of mitigation strategies. While no respondents reported virtual visits to be ≥ 25% of clinical visits prior to the pandemic, more than half (51.9%) anticipated maintaining ≥ 25% virtual visits after the pandemic. CONCLUSIONS: Among surveyed sleep centers, the vast majority reported near-cessation of in-laboratory sleep studies, while a smaller proportion reported reductions in home sleep apnea tests. A large increase in the use of telemedicine was reported, with the majority of respondents expecting the use of telehealth to endure in the future.

Sleep Breathing Disorders in the COVID-19 Era: Italian Thoracic Society Organizational Models for a Correct Approach to Diagnosis and Treatment.

The attenuation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, at least in Italy, allows a gradual resumption of diagnostic and therapeutic activities for sleep respiratory disorders. The knowledge on this new disorder is growing fast, but our experience is still limited and when a physician cannot rely on evidence-based medicine, the experience of his peers can support the decision-making and operational process of reopening sleep laboratories. The aim of this paper is to focus on the safety of patients and operators accessing hospitals and the practice of diagnosing and treating sleep-related respiratory disorders. The whole process requires a careful plan, starting with a triage preceding the access to the facility, to minimize the risk of infection. Preparation of the medical record can be performed through standard questionnaires administered over the phone or by e-mail, including an assessment of the COVID-19 risk. The home sleep test should include single-patient sensors or easy-to-sanitize material. The use of nasal cannulas is discouraged in view of the risk of the virus colonizing the internal reading chamber, since no filter has been tested and certified to be used extensively for coronavirus due to its small size. The adaptation to positive airway pressure (PAP) treatment can also be performed mainly using telemedicine procedures. In the adaptation session, the mask should be new or correctly sanitized and the PAP device, without a humidifier, should be protected by an antibacterial/antiviral filter, then sanitized and reassigned after at least 4 days since SARS-CoV-2 was detected on some surfaces up to 72 h after. Identification of pressure should preferably be performed by telemedicine. The patient should be informed of the risk of spreading the disease in the family environment through droplets and how to reduce this risk. The follow-up phase can again be performed mainly by telemedicine both for problem solving and the collection of data. Public access to hospital should be minimized and granted to patients only. Constant monitoring of institutional communications will help in implementing the necessary recommendations.