scholarly journals 0616 Validation of a Sleep Headband for Detecting Obstructive Sleep Apnea

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A236-A236
Author(s):  
A Guillot ◽  
T Moutakanni ◽  
M Harris ◽  
P J Arnal ◽  
V Thorey
Keyword(s):  
Obstructive Sleep Apnea ◽  
Deep Learning ◽  
Sleep Apnea ◽  
Cross Validation ◽  
Apnea Hypopnea Index ◽  
Learning Approach ◽  
Specificity And Sensitivity ◽  
Obstructive Sleep ◽  
Fold Cross Validation ◽  
At Home

Abstract Introduction Polysomnography (PSG) is the gold-standard to diagnose obstructive sleep apnea (OSA). OSA severity diagnosis is defined by the apnea-hypopnea index (AHI) defined as the number of apnea and hypopnea events measured per hour of sleep. The Dreem2 headband (DH) is a self-administered, easy to use device that measure EEG, breathing frequency, heart rate and sound at-home. In our study, we assessed the performance of the DH to automatically detects OSA compared to 3 sleep’s experts scoring on PSG. Methods 41 subjects (8 females, 42.6 ± 13.7 y.o.) having a suspicion of OSA performed a night at-home wearing both a PSG and the DH. Each PSG record was scored for apnea and hypopnea events by 3 independent trained sleep experts following AASM guidelines. The deep learning approach DOSED, was trained on the DH signals using the manual apnea scoring. 10-fold cross-validation was used to provide predictions for each of the 41 subjects with the DH. Results We observed an average AHI expert’s scoring of 13.6 ± 10.1 CI[10.5, 16.5] compared to 12.9 ± 10.3 CI[9.6, 15.8] for the DH. Both, the correlation between the 3 scorers (r= 0.88, p < 0.001) and the DH and the scorers (r=0.79, p< 0.001) were significant. The specificity and sensitivity to detect mild OSA (AHI ≤ 5) was 84.4 % and 96.4 % for the DH and 86.5 % and 86.0% for the scorers. Conclusion The results show that the DH using deep learning can detect OSA with an accuracy similar to the sleep experts. The use of DH paves the way for longitudinal monitoring of patients with a suspicion of OSA and its accessibility could lead to better screening of the general population. Support This Study has been supported by Dreem sas.

Reliability of Holter Oximetry for Home Sleep Apnea Testing

2008 ◽  
Vol 139 (2_suppl) ◽  
pp. P83-P84 ◽  
Author(s):  
Jordan C Stern ◽  
Conor Heneghan ◽  
Redmond Shouldice
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Apnea Hypopnea Index ◽  
Patients Âgés ◽  
Home Testing ◽  
Obstructive Sleep ◽  
Adults And Children ◽  
Home Sleep Apnea Testing ◽  
A Prospective Study ◽  
At Home

Objective To test the reliability of the Holter Oximeter for home testing of obstructive sleep apnea. Previous reports have shown a 96% correlation with simultaneous polysomnography and Holter Oximetry in the sleep laboratory. This study was designed to measure reliability of data obtained at home, as well as to obtain information from patients regarding comfort of the device. Methods A prospective study of 120 consecutive patients (ages 5 to 85) presenting to an otolaryngology practice during a 4-month period with complaints of snoring or sleep apnea symptoms. Device: The Holter Oximeter produces an apnea hypopnea index (AHI) based on an automated processing method of a continuous electrocardiogram and pulse oximeter. The reliability of the test was determined by the number of tests completed without interruption due to patient discomfort, electrode or device failure. Results There was 97% data recovery from the home testing device. Data failure was due to faulty memory cards in the device or surface electrode failure. All patients tolerated wearing the device at home, and there were no voluntary interruptions of the tests by patients. On a discomfort scale of 0 to 10 (0: no discomfort and 10: maximal discomfort), the average discomfort score was 2. Conclusions Holter Oximetry represents a new, easy to use, and reliable device for the home diagnosis of obstructive sleep apnea. It can also be used to measure outcomes for the surgical and non-surgical treatment of obstructive sleep apnea in adults and children.

scholarly journals Cardiorespiratory Polygraphy for Detection of Obstructive Sleep Apnea in Patients With Atrial Fibrillation

2021 ◽  
Vol 8 ◽  
Author(s):  
Michiel Delesie ◽  
Lieselotte Knaepen ◽  
Johan Verbraecken ◽  
Karolien Weytjens ◽  
Paul Dendale ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Screening Tool ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Automated Algorithm ◽  
Obstructive Sleep ◽  
At Home

Background: Obstructive sleep apnea (OSA) is a modifiable risk factor of atrial fibrillation (AF) but is underdiagnosed in these patients due to absence of good OSA screening pathways. Polysomnography (PSG) is the gold standard for diagnosing OSA but too resource-intensive as a screening tool. We explored whether cardiorespiratory polygraphy (PG) devices using an automated algorithm for Apnea-Hypopnea Index (AHI) determination can meet the requirements of a good screening tool in AF patients.Methods: This prospective study validated the performance of three PGs [ApneaLink Air (ALA), SOMNOtouch RESP (STR) and SpiderSAS (SpS)] in consecutive AF patients who were referred for PSG evaluation. Patients wore one of the three PGs simultaneously with PSG, and a different PG during each of three consecutive nights at home. Severity of OSA was classified according to the AHI during PSG (<5 = no OSA, 5–14 = mild, 15–30 = moderate, >30 = severe).Results: Of the 100 included AF patients, PSG diagnosed at least moderate in 69% and severe OSA in 33%. Successful PG execution at home was obtained in 79.1, 80.2 and 86.8% of patients with the ALA, STR and SpS, respectively. For the detection of clinically relevant OSA (AHI ≥ 15), an area under the curve of 0.802, 0.772 and 0.803 was calculated for the ALA, STR and SpS, respectively.Conclusions: This study indicates that home-worn PGs with an automated AHI algorithm can be used as OSA screening tools in AF patients. Based on an appropriate AHI cut-off value for each PG, the device can guide referral for definite PSG diagnosis.

Improvement in Obstructive Sleep Apnea (OSA) in Super Morbidly Obese Patients After Bariatric Surgery

2020 ◽  
Vol 103 (8) ◽  
pp. 725-728
Keyword(s):  
Bariatric Surgery ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Lifestyle Modification ◽  
Apnea Hypopnea Index ◽  
Morbidly Obese ◽  
Obese Patients ◽  
Obstructive Sleep ◽  
Objective Evidence

Background: Lifestyle modification is the mainstay therapy for obese patients with obstructive sleep apnea (OSA). However, most of these patients are unable to lose the necessary weight, and bariatric surgery (BS) has been proven to be an effective modality in selected cases. Objective: To provide objective evidence that BS can improve OSA severity. Materials and Methods: A prospective study was conducted in super morbidly obese patients (body mass index [BMI] greater than 40 kg/m² or BMI greater than 35 kg/m² with uncontrolled comorbidities) scheduled for BS. Polysomnography (PSG) was performed for preoperative assessment and OSA was treated accordingly. After successful surgery, patients were invited to perform follow-up PSG at 3, 6, and 12 months. Results: Twenty-four patients with a mean age of 35.0±14.0 years were enrolled. After a mean follow-up period of 7.8±3.4 months, the mean BMI, Epworth sleepiness scale (ESS), and apnea-hypopnea index (AHI) significantly decreased from 51.6±8.7 to 38.2±6.8 kg/m² (p<0.001), from 8.7±5.9 to 4.7±3.5 (p=0.003), and from 87.6±38.9 to 28.5±21.5 events/hour (p<0.001), respectively. Conclusion: BS was shown to dramatically improve clinical and sleep parameters in super morbidly obese patients. Keywords: Morbid obesity, Bariatric surgery, Obstructive sleep apnea (OSA)

scholarly journals Accurate Deep Learning-Based Sleep Staging in a Clinical Population with Suspected Obstructive Sleep Apnea

2019 ◽  
pp. 1-1 ◽  
Author(s):  
Henri Korkalainen ◽  
Timo Leppanen ◽  
Juhani Aakko ◽  
Sami Nikkonen ◽  
Samu Kainulainen ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Deep Learning ◽  
Sleep Apnea ◽  
Clinical Population ◽  
Sleep Staging ◽  
Obstructive Sleep

Aerodynamics Analysis of the Impact of Nasal Surgery on Patients with Obstructive Sleep Apnea and Nasal Obstruction

ORL ◽  
2021 ◽  
pp. 1-8
Author(s):  
Lifeng Li ◽  
Demin Han ◽  
Hongrui Zang ◽  
Nyall R. London
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Nasal Obstruction ◽  
Upper Airway ◽  
Apnea Hypopnea Index ◽  
Nasal Surgery ◽  
Subjective Sleep Quality ◽  
Obstructive Sleep ◽  
Significant Difference ◽  
The Impact

<b><i>Objective:</i></b> The purpose of this study was to evaluate the effects of nasal surgery on airflow characteristics in patients with obstructive sleep apnea (OSA) by comparing the alterations of airflow characteristics within the nasal and palatopharyngeal cavities. <b><i>Methods:</i></b> Thirty patients with OSA and nasal obstruction who underwent nasal surgery were enrolled. A pre- and postoperative 3-dimensional model was constructed, and alterations of airflow characteristics were assessed using the method of computational fluid dynamics. The other subjective and objective clinical indices were also assessed. <b><i>Results:</i></b> By comparison with the preoperative value, all postoperative subjective symptoms statistically improved (<i>p</i> &#x3c; 0.05), while the Apnea-Hypopnea Index (AHI) changed little (<i>p</i> = 0.492); the postoperative airflow velocity and pressure in both nasal and palatopharyngeal cavities, nasal and palatopharyngeal pressure differences, and total upper airway resistance statistically decreased (all <i>p</i> &#x3c; 0.01). A significant difference was derived for correlation between the alteration of simulation metrics with subjective improvements (<i>p</i> &#x3c; 0.05), except with the AHI (<i>p</i> &#x3e; 0.05). <b><i>Conclusion:</i></b> Nasal surgery can decrease the total resistance of the upper airway and increase the nasal airflow volume and subjective sleep quality in patients with OSA and nasal obstruction. The altered airflow characteristics might contribute to the postoperative reduction of pharyngeal collapse in a subset of OSA patients.

scholarly journals High Plasma Cystine Levels Are Associated with Blood Pressure and Reversed by CPAP in Patients with Obstructive Sleep Apnea

2021 ◽  
Vol 10 (7) ◽  
pp. 1387
Author(s):  
Raphael Boneberg ◽  
Anita Pardun ◽  
Lena Hannemann ◽  
Olaf Hildebrandt ◽  
Ulrich Koehler ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Mononuclear Cells ◽  
Vascular Risk Factor ◽  
High Plasma ◽  
Apnea Hypopnea Index ◽  
Hypoxic Stress ◽  
Peripheral Blood Mononuclear ◽  
Obstructive Sleep

Obstructive sleep apnea (OSA) independent of obesity (OBS) imposes severe cardiovascular risk. To what extent plasma cystine concentration (CySS), a novel pro-oxidative vascular risk factor, is increased in OSA with or without OBS is presently unknown. We therefore studied CySS together with the redox state and precursor amino acids of glutathione (GSH) in peripheral blood mononuclear cells (PBMC) in untreated male patients with OSA (apnea-hypopnea-index (AHI) > 15 h−1, n = 28) compared to healthy male controls (n = 25) stratifying for BMI ≥ or < 30 kg m−2. Fifteen OSA patients were reassessed after 3–5-months CPAP. CySS correlated with cumulative time at an O2-saturation <90% (Tu90%) (r = 0.34, p < 0.05) beside BMI (r = 0.58, p < 0.001) and was higher in subjects with “hypoxic stress” (59.4 ± 2.0 vs. 50.1 ± 2.7 µM, p < 0.01) defined as Tu90% ≥ 15.2 min (corresponding to AHI ≥ 15 h−1). Moreover, CySS significantly correlated with systolic (r = 0.32, p < 0.05) and diastolic (r = 0.31, p < 0.05) blood pressure. CPAP significantly lowered CySS along with blood pressure at unchanged BMI. Unexpectedly, GSH antioxidant capacity in PBMC was increased with OSA and reversed with CPAP. Plasma CySS levels are increased with OSA-related hypoxic stress and associated with higher blood pressure. CPAP decreases both CySS and blood pressure. The role of CySS in OSA-related vascular endpoints and their prevention by CPAP warrants further studies.

scholarly journals Altered K-complex morphology during sustained inspiratory airflow limitation is associated with next-day lapses in vigilance in obstructive sleep apnea

SLEEP ◽  
2021 ◽  
Author(s):  
Ankit Parekh ◽  
Korey Kam ◽  
Anna E Mullins ◽  
Bresne Castillo ◽  
Asem Berkalieva ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Spectral Characteristics ◽  
Sleep Time ◽  
Airflow Limitation ◽  
Apnea Hypopnea Index ◽  
Complex Morphology ◽  
Obstructive Sleep ◽  
Inspiratory Airflow Limitation ◽  
Psychomotor Vigilance

Abstract Study Objectives Determine if changes in K-complexes associated with sustained inspiratory airflow limitation (SIFL) during N2 sleep are associated with next-day vigilance and objective sleepiness. Methods Data from thirty subjects with moderate-to-severe obstructive sleep apnea who completed three in-lab polysomnograms: diagnostic, on therapeutic continuous positive airway pressure (CPAP), and on suboptimal CPAP (4 cmH2O below optimal titrated CPAP level) were analyzed. Four 20-min psychomotor vigilance tests (PVT) were performed after each PSG, every 2 h. Changes in the proportion of spontaneous K-complexes and spectral characteristics surrounding K-complexes were evaluated for K-complexes associated with both delta (∆SWAK), alpha (∆αK) frequencies. Results Suboptimal CPAP induced SIFL (14.7 (20.9) vs 2.9 (9.2); %total sleep time, p &lt; 0.001) with a small increase in apnea–hypopnea index (AHI3A: 6.5 (7.7) vs 1.9 (2.3); p &lt; 0.01) versus optimal CPAP. K-complex density (num./min of stage N2) was higher on suboptimal CPAP (0.97 ± 0.7 vs 0.65±0.5, #/min, mean ± SD, p &lt; 0.01) above and beyond the effect of age, sex, AHI3A, and duration of SIFL. A decrease in ∆SWAK with suboptimal CPAP was associated with increased PVT lapses and explained 17% of additional variance in PVT lapses. Within-night during suboptimal CPAP K-complexes appeared to alternate between promoting sleep and as arousal surrogates. Electroencephalographic changes were not associated with objective sleepiness. Conclusions Sustained inspiratory airflow limitation is associated with altered K-complex morphology including the increased occurrence of K-complexes with bursts of alpha as arousal surrogates. These findings suggest that sustained inspiratory flow limitation may be associated with nonvisible sleep fragmentation and contribute to increased lapses in vigilance.

scholarly journals Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study

2021 ◽  
Author(s):  
Satoru Tsuiki ◽  
Takuya Nagaoka ◽  
Tatsuya Fukuda ◽  
Yuki Sakamoto ◽  
Fernanda R. Almeida ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Apnea Hypopnea Index ◽  
Cephalometric Analysis ◽  
Obstructive Sleep ◽  
Main Region

Abstract Purpose In 2-dimensional lateral cephalometric radiographs, patients with severe obstructive sleep apnea (OSA) exhibit a more crowded oropharynx in comparison with non-OSA. We tested the hypothesis that machine learning, an application of artificial intelligence (AI), could be used to detect patients with severe OSA based on 2-dimensional images. Methods A deep convolutional neural network was developed (n = 1258; 90%) and tested (n = 131; 10%) using data from 1389 (100%) lateral cephalometric radiographs obtained from individuals diagnosed with severe OSA (n = 867; apnea hypopnea index > 30 events/h sleep) or non-OSA (n = 522; apnea hypopnea index < 5 events/h sleep) at a single center for sleep disorders. Three kinds of data sets were prepared by changing the area of interest using a single image: the original image without any modification (full image), an image containing a facial profile, upper airway, and craniofacial soft/hard tissues (main region), and an image containing part of the occipital region (head only). A radiologist also performed a conventional manual cephalometric analysis of the full image for comparison. Results The sensitivity/specificity was 0.87/0.82 for full image, 0.88/0.75 for main region, 0.71/0.63 for head only, and 0.54/0.80 for the manual analysis. The area under the receiver-operating characteristic curve was the highest for main region 0.92, for full image 0.89, for head only 0.70, and for manual cephalometric analysis 0.75. Conclusions A deep convolutional neural network identified individuals with severe OSA with high accuracy. Future research on this concept using AI and images can be further encouraged when discussing triage of OSA.

scholarly journals Initiation of therapy for obstructive sleep apnea syndrome: a randomized comparison of outcomes of telemetry-supported home-based vs. sleep lab-based therapy initiation

2021 ◽  
Author(s):  
Ingo Fietze ◽  
Sebastian Herberger ◽  
Gina Wewer ◽  
Holger Woehrle ◽  
Katharina Lederer ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Control Group ◽  
Sleep Laboratory ◽  
Home Therapy ◽  
Home Management ◽  
Therapy Initiation ◽  
Home Based ◽  
Obstructive Sleep ◽  
At Home

Abstract Purpose Diagnosis and treatment of obstructive sleep apnea are traditionally performed in sleep laboratories with polysomnography (PSG) and are associated with significant waiting times for patients and high cost. We investigated if initiation of auto-titrating CPAP (APAP) treatment at home in patients with obstructive sleep apnea (OSA) and subsequent telemonitoring by a homecare provider would be non-inferior to in-lab management with diagnostic PSG, subsequent in-lab APAP initiation, and standard follow-up regarding compliance and disease-specific quality of life. Methods This randomized, open-label, single-center study was conducted in Germany. Screening occurred between December 2013 and November 2015. Eligible patients with moderate-to-severe OSA documented by polygraphy (PG) were randomized to home management or standard care. All patients were managed by certified sleep physicians. The home management group received APAP therapy at home, followed by telemonitoring. The control group received a diagnostic PSG, followed by therapy initiation in the sleep laboratory. The primary endpoint was therapy compliance, measured as average APAP usage after 6 months. Results The intention-to-treat population (ITT) included 224 patients (110 home therapy, 114 controls); the per-protocol population (PP) included 182 patients with 6-month device usage data (89 home therapy, 93 controls). In the PP analysis, mean APAP usage at 6 months was not different in the home therapy and control groups (4.38 ± 2.04 vs. 4.32 ± 2.28, p = 0.845). The pre-specified non-inferiority margin (NIM) of 0.3 h/day was not achieved (p = 0.130); statistical significance was achieved in a post hoc analysis when NIM was set at 0.5 h/day (p < 0.05). Time to APAP initiation was significantly shorter in the home therapy group (7.6 ± 7.2 vs. 46.1 ± 23.8 days; p < 0.0001). Conclusion Use of a home-based telemonitoring strategy for initiation of APAP in selected patients with OSA managed by sleep physicians is feasible, appears to be non-inferior to standard sleep laboratory procedures, and facilitates faster access to therapy.

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