Validity and Cost-Effectiveness of Pediatric Home Respiratory Polygraphy for the Diagnosis of Obstructive Sleep Apnea in Children: Rationale, Study Design, and Methodology

Retrospective review of treatment outcomes and costs in children with sleep disordered breathing assessed with multi-channel studies

Current UK guidance on OSA management recommends only selective use of sleep studies - when there is diagnostic uncertainty, in children with comorbidities or to evaluate perioperative risk in those with suspected severe OSA. Routine use of sleep studies to confirm a diagnosis of obstructive sleep apnoea (OSA) in children before adenotonsillectomy is not currently recommended. We report the findings of a novel paediatric sleep service based on routine use of multi-channel sleep studies (MCSS) before adenotonsillectomy and present the results of a service evaluation assessing the impact of our practise on treatment outcomes and cost. We conducted a retrospective study of 264 children with sleep disordered breathing seen in our centre between July 2018-June 2019, using medical records and a sleep study database to determine treatment outcomes and costs. Using responses from a questionnaire completed by otolaryngologists for a separate prospective study, we compare our costs with estimates of those associated with a standard UK model of care i.e. with selective use of sleep studies. We estimate that our routine use of MCSS reduced the number of adenotonsillectomies by 44 % but at higher monetary costs than those estimated for the standard model of care. We note however, that reconfiguring our service to arrange a sleep study before the initial appointment, rather than after, would result in the service being cost neutral compared with the standard model. We also estimate that use of home multi-channel studies in our service would bring a significant cost saving (∼£50,000 - £80,000 per annum) compared to standard care.

Is the Pediatric Sleep Questionnaire sensitive for sleep-disordered breathing in children with complex chronic disease?

PURPOSE

Sleep-disordered breathing (SDB) is a disease defined by breathing or breathing irregularities while asleep. The current study examines the association between results of polysomnography (PSG) and the Pediatric Sleep Questionnaire (PSQ), and the specificity and sensitivity of the PSQ for obstructive sleep apnea (OSA) in patients with chronic illnesses.

METHODS

Demographic and clinical attributes, in addition to PSQ and PSG outcomes were examined retrospectively among patients who underwent polysomnography (PSG) at our facility between 2012 and 2021.

RESULTS

Of 745 patients included in the study, 462 (62%) were male. The median age was 81 months (34-151 months). 117 of the patients (15/8%) had chronic lung disease, and 80 (10.7%) had cerebral palsy. The most common indications for PSG were symptoms of OSA (n = 426; 57.1%). According to obstructive apnea-hypopnea index (AHI), 361 patients (48.5%) had normal PSG. The median PSQ score was 0.40 (0.22-0.57). The sensitivity and specificity of the PSQ were 71.8% and 40.4%, respectively, for individuals aged 2 to 18 years. Among the disease subgroups, the cerebral palsy group had the highest sensitivity of PSQ (88.8%) for diagnosis of OSA.

CONCLUSION

Questionnaires for evaluating SDB are not sensitive or specific for identification of OSA in children with chronic conditions, and PSG remains the best method.

Diagnosis of Paediatric Obstructive Sleep-Disordered Breathing beyond Polysomnography

Obstructive sleep-disordered breathing (SDB) has significant impacts on health, and therefore, a timely and accurate diagnosis is crucial for effective management and intervention. This narrative review provides an overview of the current approaches utilised in the diagnosis of SDB in children. Diagnostic methods for SDB in children involve a combination of clinical assessment, medical history evaluation, questionnaires, and objective measurements. Polysomnography (PSG) is the diagnostic gold standard. It records activity of brain and tibial and submental muscles, heart rhythm, eye movements, oximetry, oronasal airflow, abdominal and chest movements, body position. Despite its accuracy, it is a time-consuming and expensive tool. Respiratory polygraphy instead monitors cardiorespiratory function without simultaneously assessing sleep and wakefulness; it is more affordable than PSG, but few paediatric studies compare these techniques and there is optional recommendation in children. Nocturnal oximetry is a simple and accessible exam that has high predictive value only for children at high risk. The daytime nap PSG, despite the advantage of shorter duration and lower costs, is not accurate for predicting SDB. Few paediatric data support the use of home testing during sleep. Finally, laboratory biomarkers and radiological findings are potentially useful hallmarks of SDB, but further investigations are needed to standardise their use in clinical practice.

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.

Diagnosis and Treatment of Sleep Apnea in Children: A Future Perspective Is Needed

Obstructive sleep apnea (OSA) in children is a prevalent, but still, today, underdiagnosed illness, which consists of repetitive episodes of upper airway obstruction during sleep with important repercussions for sleep quality. OSA has relevant consequences in the pediatric population, mainly in the metabolic, cardiovascular (CV), and neurological spheres. However, contrary to adults, advances in diagnostic and therapeutic management have been scarce in the last few years despite the increasing scientific evidence of the deleterious consequences of pediatric OSA. The problem of underdiagnosis and the lack of response to treatment in some groups make an update to the management of OSA in children necessary. Probably, the heterogeneity of OSA is not well represented by the classical clinical presentation and severity parameters (apnea/hypopnea index (AHI)), and new strategies are required. A specific and consensus definition should be established. Additionally, the role of simplified methods in the diagnosis algorithm should be considered. Finally, the search for new biomarkers for risk stratification is needed in this population. In conclusion, new paradigms based on personalized medicine should be implemented in this population.

What’s New in Pediatric Obstructive Sleep Apnea?

Obstructive sleep apnea (OSA) is common children. There is a demand for more family-focused evaluation and novel diagnostic approaches. Drug-induced sleep endoscopy is increasingly being used clinically in children with Down syndrome and other comorbidities. Several studies have examined the association between OSA and other comorbidities during childhood. Therapeutic options for OSA in children remain limited. Recent studies have examined the utility of hypoglossal nerve stimulation in children with Down syndrome. Positive airway pressure has been a mainstay of OSA treatment. Several recent studies have assessed factors associated with adherence. Infants are challenging to treat for OSA.

Cluster Analysis of Home Polygraphic Recordings in Symptomatic Habitually-Snoring Children: A Precision Medicine Perspective

(1) Background: Sleep-disordered breathing (SDB) is a frequent problem in children. Cluster analyses offer the possibility of identifying homogeneous groups within a large clinical database. The application of cluster analysis to anthropometric and polysomnographic measures in snoring children would enable the detection of distinctive clinically-relevant phenotypes; (2) Methods: We retrospectively collected the results of nocturnal home-based cardiorespiratory polygraphic recordings and anthropometric measurements in 326 habitually-snoring otherwise healthy children. K-medoids clustering was applied to standardized respiratory and anthropometric measures, followed by Silhouette-based statistics. Respiratory Disturbance Index (RDI) and oxygen desaturation index (≤3%) were included in determining the optimal number of clusters; (3) Results: Mean age of subjects was 8.1 ± 4.1 years, and 57% were males. Cluster analyses uncovered an optimal number of three clusters. Cluster 1 comprised 59.5% of the cohort (mean age 8.69 ± 4.14 years) with a mean RDI of 3.71 ± 3.23 events/hour of estimated sleep (e/ehSleep). Cluster 2 included 28.5% of the children (mean age 6.92 ± 3.43 years) with an RDI of 6.38 ± 3.92 e/ehSleep. Cluster 3 included 12% of the cohort (mean age 7.58 ± 4.73 years) with a mean RDI of 25.5 ± 19.4 e/ehSleep. Weight z-score was significantly lower in cluster 3 [-0.14 ± 1.65] than in cluster 2 [0.86 ± 1.78; p = 0.015] and cluster 1 [1.04 ± 1.78; p = 0.002]. Similar findings emerged for BMI z scores. However, the height z-score was not significantly different among the 3 clusters; (4) Conclusions: Cluster analysis of children who are symptomatic habitual snorers and are referred for clinical polygraphic evaluation identified three major clusters that differed in age, RDI, and anthropometric measures. An increased number of children in the cluster with the highest RDI had reduced body weight. We propose that the implementation of these approaches to a multicenter-derived database of home-based polygraphic recordings may enable the delineation of objective unbiased severity categories of pediatric SDB. Our findings could be useful for clinical implementation, formulation of therapeutic decision guidelines, clinical management, prevision of complications, and long-term follow-up.

Environmental Benefits of Sleep Apnoea Detection in the Home Environment

Sleep Apnoea (SA) is a common chronic illness that affects nearly 1 billion people around the world, and the number of patients is rising. SA causes a wide range of psychological and physiological ailments that have detrimental effects on a patient’s wellbeing. The high prevalence and negative health effects make SA a public health problem. Whilst the current gold standard diagnostic procedure, polysomnography (PSG), is reliable, it is resource-expensive and can have a negative impact on sleep quality, as well as the environment. With this study, we focus on the environmental impact that arises from resource utilisation during SA detection, and we propose remote monitoring (RM) as a potential solution that can improve the resource efficiency and reduce travel. By reusing infrastructure technology, such as mobile communication, cloud computing, and artificial intelligence (AI), RM establishes SA detection and diagnosis support services in the home environment. However, there are considerable barriers to a widespread adoption of this technology. To gain a better understanding of the available technology and its associated strength, as well as weaknesses, we reviewed scientific papers that used various strategies for RM-based SA detection. Our review focused on 113 studies that were conducted between 2018 and 2022 and that were listed in Google Scholar. We found that just over 50% of the proposed RM systems incorporated real time signal processing and around 20% of the studies did not report on this important aspect. From an environmental perspective, this is a significant shortcoming, because 30% of the studies were based on measurement devices that must travel whenever the internal buffer is full. The environmental impact of that travel might constitute an additional need for changing from offline to online SA detection in the home environment.

Classification of Factors Effect on Sleep in Individuals with Down Syndrome

BACKGROUND

Sleep disordered breathing (SDB) is a frequent disorder with serious adverse health consequences in people with Down syndrome (DS). This study aims to evaluate and classify sleep and physical activity (PA) characteristics in adults with DS.

METHODS

Forty participants with DS wore an accelerometer for seven consecutive days to measure physical activity and sleep-wake patterns. The corresponding data were also obtained by survey and polysomnography. The apnea-hypopnea index (AHI) is calculated from the number of apneas and hypopneas per hour of sleep according to international guidelines.

RESULTS

Polysomnography showed SDB based on AHI in 95% of adults: 50% had severe SDB, 22.5% presented moderate and 22.5% mild SDB, predominantly in males. They had poor sleep quality (80.1%) and low PA levels. Using statistical classification methods, we observed three clusters with two opposite profiles. Clusters 2 and 3 showed low PA indices (daily steps: 5719 and 5310, respectively) and severe SDB (AHI = 33.6 and 55.5 events/h), high age and high gonial angle. Cluster 1 showed high PA (mean count of daily steps: 6908) and mild to moderate SDB (AHI = 16.8 events/h), low age and low gonial angle.

CONCLUSIONS

Our findings suggest that there are different profiles (age, gender, obesity, gonial angle) that are associated with SDB in adults with DS. These results suggest that this may represent important factors to consider when planning health promotion and prevention.