Validation of the System One RemStar Auto A-Flex for Obstructive Sleep Apnea Treatment and Detection of Residual Apnea-Hypopnea Index: A European Randomized Trial

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)

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

ORL ◽

10.1159/000516243 ◽

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

Objective: 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. Methods: 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. Results: By comparison with the preoperative value, all postoperative subjective symptoms statistically improved (p < 0.05), while the Apnea-Hypopnea Index (AHI) changed little (p = 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 p < 0.01). A significant difference was derived for correlation between the alteration of simulation metrics with subjective improvements (p < 0.05), except with the AHI (p > 0.05). Conclusion: 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.

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

Journal of Clinical Medicine ◽

10.3390/jcm10071387 ◽

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.

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

SLEEP ◽

10.1093/sleep/zsab010 ◽

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 < 0.001) with a small increase in apnea–hypopnea index (AHI3A: 6.5 (7.7) vs 1.9 (2.3); p < 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 < 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.

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

Sleep And Breathing ◽

10.1007/s11325-021-02301-7 ◽

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.

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Short-Term HRV Analysis Using Nonparametric Sample Entropy for Obstructive Sleep Apnea

Entropy ◽

10.3390/e23030267 ◽

2021 ◽

Vol 23 (3) ◽

pp. 267

Author(s):

Duan Liang ◽

Shan Wu ◽

Lan Tang ◽

Kaicheng Feng ◽

Guanzheng Liu

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Sample Entropy ◽

Biomedical Signal Processing ◽

Apnea Hypopnea Index ◽

Short Term ◽

Autonomic Nervous System Dysfunction ◽

Obstructive Sleep ◽

Hrv Analysis ◽

Frequency Power

Obstructive sleep apnea (OSA) is associated with reduced heart rate variability (HRV) and autonomic nervous system dysfunction. Sample entropy (SampEn) is commonly used for regularity analysis. However, it has limitations in processing short-term segments of HRV signals due to the extreme dependence of its functional parameters. We used the nonparametric sample entropy (NPSampEn) as a novel index for short-term HRV analysis in the case of OSA. The manuscript included 60 6-h electrocardiogram recordings (20 healthy, 14 mild-moderate OSA, and 26 severe OSA) from the PhysioNet database. The NPSampEn value was compared with the SampEn value and frequency domain indices. The empirical results showed that NPSampEn could better differentiate the three groups (p < 0.01) than the ratio of low frequency power to high frequency power (LF/HF) and SampEn. Moreover, NPSampEn (83.3%) approached a higher OSA screening accuracy than the LF/HF (73.3%) and SampEn (68.3%). Compared with SampEn (|r| = 0.602, p < 0.05), NPSampEn (|r| = 0.756, p < 0.05) had a significantly stronger association with the apnea-hypopnea index (AHI). Hence, NPSampEn can fully overcome the influence of individual differences that are prevalent in biomedical signal processing, and might be useful in processing short-term segments of HRV signal.

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Endothelial dysfunction in obstructive sleep apnea patients

Sleep And Breathing ◽

10.1007/s11325-021-02382-4 ◽

2021 ◽

Author(s):

Michał Harańczyk ◽

Małgorzata Konieczyńska ◽

Wojciech Płazak

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Endothelial Dysfunction ◽

Right Ventricular ◽

Contractile Function ◽

Sleep Apnea Syndrome ◽

Apnea Hypopnea Index ◽

Endothelin 1 ◽

Obstructive Sleep

Abstract Purpose Obstructive sleep apnea syndrome (OSAS) is an independent risk factor for cardiovascular diseases. The aim of the study was to assess the influence of OSAS on endothelial dysfunction and thrombosis biomarkers and to evaluate the effect of treatment with continuous positive airway pressure (CPAP) on biomarker levels. Methods NT-proBNP, sICAM-1, endothelin-1, von Willebrand factor, D-dimers, and thrombin-antithrombin complex (TAT) were measured in 50 patients diagnosed with moderate-to-severe OSAS. All patients underwent transthoracic echocardiography, and 38 months after the inclusion, 16 CPAP users and 22 non-CPAP users were reassessed. Results Sleep-related indices of apnea-hypopnea index (AHI) and mean SpO2 were associated with higher sICAM-1 levels (AHI < 30: 7.3 ± 4.7 vs. AHI ≥ 30: 19.5 ± 19.4 mg/ml, p = 0.04; SpO2 ≥ 90%: 11.9 ± 9.3 vs. SpO2 < 90%: 23.6 ± 25.8, p = 0.04). sICAM-1 levels were significantly higher in obese patients, particularly with BMI ≥ 40. Plasma levels of TAT were significantly correlated with the increased right ventricular size (right ventricular diameter ≤ 37 mm: 0.86 ± 0.70 vs. > 37 mm: 1.96 ± 1.20 ng/ml, p = 0.04). Endothelin-1 levels were higher in patients with decreased right ventricular function (right ventricle TDI-derived S′ ≥ 12 cm/s: 11.5 ± 10.9 vs. < 12 cm/s: 26.0 ± 13.2 pg/ml, p = 0.04). An increase in NT-proBNP was related to impaired parameters of the right ventricular contractile function. There were no correlations between long-term CPAP therapy and the levels of biomarkers. Conclusion Severe OSAS influences endothelial damage as manifested by an increase in sICAM-1 levels. Changes in right ventricular structure and function, observed mainly in patients with higher TAT and endothelin-1 levels, are also manifested by an increase in NT-proBNP levels. Long-term CPAP treatment does not seem to influence biomarkers in patients with moderate-to-severe OSAS, which may help to explain the lack of influence of CPAP on cardiovascular risk reduction.

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