sleep apnea
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2022 ◽  
Vol 3 (2) ◽  
pp. 1-16
Author(s):  
Md Juber Rahman ◽  
Bashir I. Morshed

Artificial Intelligence-enabled applications on edge devices have the potential to revolutionize disease detection and monitoring in future smart health (sHealth) systems. In this study, we investigated a minimalist approach for the severity classification, severity estimation, and progression monitoring of obstructive sleep apnea (OSA) in a home environment using wearables. We used the recursive feature elimination technique to select the best feature set of 70 features from a total of 200 features extracted from polysomnogram. We used a multi-layer perceptron model to investigate the performance of OSA severity classification with all the ranked features to a subset of features available from either Electroencephalography or Heart Rate Variability (HRV) and time duration of SpO2 level. The results indicate that using only computationally inexpensive features from HRV and SpO2, an area under the curve of 0.91 and an accuracy of 83.97% can be achieved for the severity classification of OSA. For estimation of the apnea-hypopnea index, the accuracy of RMSE = 4.6 and R-squared value = 0.71 have been achieved in the test set using only ranked HRV and SpO2 features. The Wilcoxon-signed-rank test indicates a significant change (p < 0.05) in the selected feature values for a progression in the disease over 2.5 years. The method has the potential for integration with edge computing for deployment on everyday wearables. This may facilitate the preliminary severity estimation, monitoring, and management of OSA patients and reduce associated healthcare costs as well as the prevalence of untreated OSA.


Author(s):  
Ritwick Agrawal ◽  
Andrew M. Spiegelman ◽  
Venkata D. Bandi ◽  
Max Hirshkowitz ◽  
Amir Sharafkhaneh

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Shan Shan ◽  
Shuyu Wang ◽  
Xue Yang ◽  
Fan Liu ◽  
Linying Xiu

Abstract Background Previous studies did not comprehensively examine the effect of adenotonsillectomy on growth and development, emotional state, quality of life, attention ability, and cognitive dysfunction in children with obstructive sleep apnea (OSA). This study aimed to explore the improvement effects of adenotonsillectomy on the growth, development, quality of life, and attention ability in children with OSA. Methods This prospective single-arm study involved children with OSA admitted at The No. 980 Hospital, Joint Logistics Support Force, PLA, China (02/2017–02/2018). The Myklebust Pupil Rating Scale (PRS), Inventory of Subjective Life Quality (ISLQ), Zung Self-rating Anxiety Scale (SAS), Conners Parent Symptom Questionnaire (PSQ), and Continuous Performance Task (CPT) were examined before and at 6 months after adenotonsillectomy. Results Forty-nine patients were enrolled. They all completed the 6-month follow-up. The body mass index increased after surgery (from 18.8 ± 4.9 to 19.3 ± 4.3 kg/m2, P = 0.008). The total PRS score increased 6 months after surgery (from 73.8 ± 12.7 to 84.6 ± 10.3, P < 0.001). All aspects of the ISLQ, except anxiety experience and physical emotion, were improved at 6 months after adenotonsillectomy (all P < 0.01). The SAS score also decreased from 20.1 ± 10.0 to 12.8 ± 6.6 (P < 0.001). All six dimensions of the PSQ, as assessed by the legal guardians, decreased after adenotonsillectomy (all P < 0.01). The proportions of children with auditory and/or visual sustained attention abnormalities decreased after surgery. Conclusions After adenotonsillectomy, the PRS, ISLQ, and PSQ improved, and anxiety and auditory/visual sustained attention abnormalities decreased, suggesting positive impacts on the growth, development, quality of life, and comprehensive cognitive abilities of children with OSA.


2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Yuriko Hajika ◽  
Yuji Kawaguchi ◽  
Kenji Hamazaki ◽  
Yasuro Kumeda

Abstract Background Adaptive support ventilation (ASV) is a proposed treatment option for central sleep apnea (CSA). Although the effectiveness of ASV remains unclear, some studies have reported promising results regarding the use of ASV in patients with heart failure with preserved ejection fraction (HfpEF). To illustrate the importance of suspecting and diagnosing sleep-disordered breathing (SDB) in older adults unable to recognize symptoms, we discuss a case in which ASV was effective in a patient with CSA and HfpEF, based on changes in the Holter electrocardiogram (ECG). Case presentation. An 82-year-old man presented to our hospital with vomiting on April 19, 2021. Approximately 10 years before admission, he was diagnosed with type 1 diabetes mellitus and recently required full support from his wife for daily activities due to cognitive dysfunction. Two days before admission, his wife was unable to administer insulin due to excessively high glucose levels, which were displayed as “high” on the patient’s glucose meter; therefore, we diagnosed the patient with diabetic ketoacidosis. After recovery, we initiated intensive insulin therapy for glycemic control. However, the patient exhibited excessive daytime sleepiness, and numerous premature ventricular contractions were observed on his ECG monitor despite the absence of hypoglycemia. As we suspected sleep-disordered breathing (SDB), we performed portable polysomnography (PSG), which revealed CSA. PSG revealed a central type of apnea and hypopnea due to an apnea–hypopnea index of 37.6, which was > 5. Moreover, the patient had daytime sleepiness; thus, we diagnosed him with CSA. We performed ASV and observed its effect using portable PSG and Holter ECG. His episodes of apnea and hypopnea were resolved, and an apparent improvement was confirmed through Holter ECG. Conclusion Medical staff should carefully monitor adult adults for signs of or risk factors for SDB to prevent serious complications. Future studies on ASV should focus on older patients with arrhythmia, as the prevalence of CSA may be underreported in this population and determine the effectiveness of ASV in patients with HfpEF, especially in older adults.


2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Patricia Peñacoba ◽  
Maria Antònia Llauger ◽  
Ana María Fortuna ◽  
Xavier Flor ◽  
Gabriel Sampol ◽  
...  

Abstract Background The coordination between different levels of care is essential for the management of obstructive sleep apnea (OSA). The objective of this multicenter project was to develop a screening model for OSA in the primary care setting. Methods Anthropometric data, clinical history, and symptoms of OSA were recorded in randomly selected primary care patients, who also underwent a home sleep apnea test (HSAT). Respiratory polygraphy or polysomnography were performed at the sleep unit to establish definite indication for continuous positive airway pressure (CPAP). By means of cross-validation, a logistic regression model (CPAP yes/no) was designed, and with the clinical variables included in the model, a scoring system was established using the β coefficients (PASHOS Test). In a second stage, results of HSAT were added, and the final accuracy of the model was assessed. Results 194 patients completed the study. The clinical test included the body mass index, neck circumference and observed apneas during sleep (AUC 0.824, 95% CI 0.763–0.886, P < 0.001). In a second stage, the oxygen desaturation index (ODI) of 3% (ODI3% ≥ 15%) from the HSAT was added (AUC 0.911, 95% CI 0.863–0.960, P < 0.001), with a sensitivity of 85.5% (95% CI 74.7–92.1) and specificity of 67.8% (95% CI 55.1–78.3). Conclusions The use of this model would prevent referral to the sleep unit for 55.1% of the patients. The two-stage PASHOS model is a useful and practical screening tool for OSA in primary care for detecting candidates for CPAP treatment. Clinical Trial Registration Registry: ClinicalTrials.gov; Name: PASHOS Project: Advanced Platform for Sleep Apnea Syndrome Assessment; URL: https://clinicaltrials.gov/ct2/show/NCT02591979; Identifier: NCT02591979. Date of registration: October 30, 2015.


2022 ◽  
Vol 11 (2) ◽  
pp. 415
Author(s):  
Catherine A. McCall ◽  
Nathaniel F. Watson

Obstructive sleep apnea (OSA) and post-traumatic stress disorder (PTSD) are often co-morbid with implications for disease severity and treatment outcomes. OSA prevalence is higher in PTSD sufferers than in the general population, with a likely bidirectional effect of the two illnesses. There is substantial evidence to support the role that disturbed sleep may play in the pathophysiology of PTSD. Sleep disturbance associated with OSA may interfere with normal rapid eye movement (REM) functioning and thus worsen nightmares and sleep-related movements. Conversely, hyperarousal and hypervigilance symptoms of PTSD may lower the arousal threshold and thus increase the frequency of sleep fragmentation related to obstructive events. Treating OSA not only improves OSA symptoms, but also nightmares and daytime symptoms of PTSD. Evidence suggests that positive airway pressure (PAP) therapy reduces PTSD symptoms in a dose-dependent fashion, but also presents challenges to tolerance in the PTSD population. Alternative OSA treatments may be better tolerated and effective for improving both OSA and PTSD. Further research avenues will be introduced as we seek a better understanding of this complex relationship.


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