Apnea hypopnea index supplied by CPAP devices: Time for standardization?

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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543 EEG-Based Deep Neural Network Model for Brain Age Prediction and Its Association with Patient Health Conditions

SLEEP ◽

10.1093/sleep/zsab072.541 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A214-A214

Author(s):

Yoav Nygate ◽

Sam Rusk ◽

Chris Fernandez ◽

Nick Glattard ◽

Jessica Arguelles ◽

...

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Population Sample ◽

Health Conditions ◽

Apnea Hypopnea Index ◽

Healthy Population ◽

Brain Health ◽

Patient Health ◽

Drug Problems ◽

Brain Age

Abstract Introduction Electroencephalogram (EEG) provides clinically relevant information for personalized patient health evaluation and comprehensive assessment of sleep. EEG-based indices have been associated with neurodegenerative conditions, psychiatric disorders, and metabolic and cardiovascular disease, and hold promise as a biomarker for brain health. Methods A deep neural network (DNN) model was trained to predict the age of patients using raw EEG signals recorded during clinical polysomnography (PSG). The DNN was trained on N=126,241 PSGs, validated on N=6,638, and tested on a holdout set of N=1,172. The holdout dataset included several categories of patient demographic and diagnostic parameters, allowing us to examine the association between brain age and a variety of medical conditions. Brain age was assessed by subtracting the individual’s chronological brain age from their EEG-predicted brain age (Brain Age Index; BAI), and then taking the absolute value of this variable (Absolute Brain Age Index; ABAI). We then constructed two regression models to test the relationship between BAI/ABAI and the following list of patient parameters: sex, BMI, depression, alcohol/drug problems, memory/concentration problems, epilepsy/seizures, diabetes, stroke, severe excessive daytime sleepiness (e.g., Epworth Sleepiness Scale ≥ 16; EDS), apnea-hypopnea index (AHI), arousal index (ArI), and sleep efficiency (SE). Results The DNN brain age model produced a mean absolute error of 4.604 and a Pearson’s r value of 0.933 which surpass the performance of prior research. In our regression analyses, we found a statistically significant relationship between the ABAI and: epilepsy and seizure disorders, stroke, elevated AHI, elevated ArI, and low SE (all p<0.05). This demonstrates these health conditions are associated with deviations of one’s predicted brain age from their chronological brain age. We also found patients with diabetes, depression, severe EDS, hypertension, and/or memory and concentration problems showed, on average, an elevated BAI compared to the healthy population sample (all p<0.05). Conclusion We show DNNs can accurately predict the brain age of healthy patients based on their raw, PSG derived, EEG recordings. Furthermore, we reveal indices, such as BAI and ABAI, display unique characteristics within different diseased populations, highlighting their potential value as novel diagnostic biomarker and potential “vital sign” of brain health. Support (if any):

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447 Cost-Effectiveness of a 3-Year Tele-OSA Intervention

SLEEP ◽

10.1093/sleep/zsab072.446 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A177-A177

Author(s):

Jaejin An ◽

Dennis Hwang ◽

Jiaxiao Shi ◽

Amy Sawyer ◽

Aiyu Chen ◽

...

Keyword(s):

Cost Effectiveness ◽

Willingness To Pay ◽

Incremental Cost ◽

Economic Benefits ◽

Small Sample ◽

Apnea Hypopnea Index ◽

Obstructive Sleep ◽

Group 2 ◽

The Cost

Abstract Introduction Trial-based tele-obstructive sleep apnea (OSA) cost-effectiveness analyses have often been inconclusive due to small sample sizes and short follow-up. In this study, we report the cost-effectiveness of Tele-OSA using a larger sample from a 3-month trial that was augmented with 2.75 additional years of epidemiologic follow-up. Methods The Tele-OSA study was a 3-month randomized trial conducted in Kaiser Permanente Southern California that demonstrated improved adherence in patients receiving automated feedback messaging regarding their positive airway pressure (PAP) use when compared to usual care. At the end of the 3 months, participants in the intervention group pseudo-randomly either stopped or continued receiving messaging. This analysis included those participants who had moderate-severe OSA (Apnea Hypopnea Index >=15) and compared the cost-effectiveness of 3 groups: 1) no messaging, 2) messaging for 3 months only, and 3) messaging for 3 years. Costs were derived by multiplying medical service use from electronic medical records times costs from Federal fee schedules. Effects were average nightly hours of PAP use. We report the incremental cost per incremental hour of PAP use as well as the fraction acceptable. Results We included 256 patients with moderate-severe OSA (Group 1, n=132; Group 2, n=79; Group 3, n=45). Group 2, which received the intervention for 3 months only, had the highest costs and fewest hours of use and was dominated by the other two groups. Average 1-year costs for groups 1 and 3 were $6035 (SE, $477) and $6154 (SE, $575), respectively; average nightly hours of PAP use were 3.07 (SE, 0.23) and 4.09 (SE, 0.42). Compared to no messaging, messaging for 3 years had an incremental cost ($119, p=0.86) per incremental hour of use (1.02, p=0.03) of $117. For a willingness-to-pay (WTP) of $500 per year ($1.37/night), 3-year messaging has a 70% chance of being acceptable. Conclusion Long-term Tele-OSA messaging was more effective than no messaging for PAP use outcomes but also highly likely cost-effective with an acceptable willingness-to-pay threshold. Epidemiologic evidence suggests that this greater use will yield both clinical and additional economic benefits. Support (if any) Tele-OSA study was supported by the AASM Foundation SRA Grant #: 104-SR-13

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Case report: fast reversal of malignant obesity hypoventilation syndrome after noninvasive ventilation and pulmonary rehabilitation

Sleep Science and Practice ◽

10.1186/s41606-021-00062-6 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Shengyu Hao ◽

Lingling Pang ◽

Liang Xie ◽

Xu Wu ◽

Zilong Liu ◽

...

Keyword(s):

Noninvasive Ventilation ◽

Pulmonary Rehabilitation ◽

Good Condition ◽

Program Improvement ◽

Apnea Hypopnea Index ◽

High Morbidity ◽

Obesity Hypoventilation Syndrome ◽

Extreme Obesity ◽

Hypoventilation Syndrome ◽

Obesity Hypoventilation

Abstract Background Malignant obesity hypoventilation syndrome (MOHS) is described as a subtype condition of OHS, characterized by extreme obesity, obese-related hypoventilation, and multiorgan dysfunction. Because of low awareness and inadequate treatment, MOHS leads to high morbidity and mortality. Case presentation A 53-year-old man was diagnosed with MOHS evidenced by extreme obesity and multiorgan abnormalities. After taken noninvasive ventilation (NIV) treatment, he was rescued. And at the end of the six-month pulmonary rehabilitation (PR) program, improvement in terms of respiratory parameters, BMI, apnea-hypopnea index (AHI), and pulmonary hypertension were observed in the patient. Two years later, the patient was still in good condition. Conclusions This case highlights the awareness and proper use of NIV to rescue MOHS patients. Furthermore, the benefits of PR were explored in this case, which has not been considered within the therapeutic options for MOHS 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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Detecting Apnea/Hypopnea Events Time Location from Sound Recordings for Patients with Severe or Moderate Sleep Apnea Syndrome

Applied Sciences ◽

10.3390/app11156888 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6888

Author(s):

Georgia Korompili ◽

Lampros Kokkalas ◽

Stelios A. Mitilineos ◽

Nicolas-Alexander Tatlas ◽

Stelios M. Potirakis

Keyword(s):

Sleep Apnea ◽

Sleep Apnea Syndrome ◽

Apnea Hypopnea Index ◽

Event Time ◽

Severity Estimation ◽

Apnea Duration ◽

Respiratory Events ◽

Moderate Sensitivity ◽

Apnea Syndrome

The most common index for diagnosing Sleep Apnea Syndrome (SAS) is the Apnea-Hypopnea Index (AHI), defined as the average count of apnea/hypopnea events per sleeping hour. Despite its broad use in automated systems for SAS severity estimation, researchers now focus on individual event time detection rather than the insufficient classification of the patient in SAS severity groups. Towards this direction, in this work, we aim at the detection of the exact time location of apnea/hypopnea events. We particularly examine the hypothesis of employing a standard Voice Activity Detection (VAD) algorithm to extract breathing segments during sleep and identify the respiratory events from severely altered breathing amplitude within the event. The algorithm, which is tested only in severe and moderate patients, is applied to recordings from a tracheal and an ambient microphone. It proves good sensitivity for apneas, reaching 81% and 70.4% for the two microphones, respectively, and moderate sensitivity to hypopneas—approx. 50% were identified. The algorithm also presents an adequate estimator of the Mean Apnea Duration index—defined as the average duration of the detected events—for patients with severe or moderate apnea, with mean error 1.7 s and 3.2 s for the two microphones, respectively.

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Analysis of nocturnal desaturation waveforms using algorithms in patients with idiopathic pulmonary fibrosis

Sleep And Breathing ◽

10.1007/s11325-021-02456-3 ◽

2021 ◽

Author(s):

Yuichiro Yasuda ◽

Tatsuya Nagano ◽

Shintaro Izumi ◽

Mina Yasuda ◽

Kosuke Tsuruno ◽

...

Keyword(s):

Sleep Apnea ◽

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Diagnostic Algorithm ◽

Sleep Time ◽

Periodic Pattern ◽

Apnea Hypopnea Index ◽

Apnea Test ◽

Eligibility Criteria ◽

Obstructive Sleep

Abstract Purpose Sleep-disordered breathing is recognized as a comorbidity in patients with idiopathic pulmonary fibrosis (IPF). Among them, nocturnal hypoxemia has been reported to be associated with poor prognosis and disease progression. We developed a diagnostic algorithm to classify nocturnal desaturation from percutaneous oxygen saturation (SpO2) waveform patterns: sustained pattern, periodic pattern, and intermittent pattern. We then investigated the prevalence of nocturnal desaturation and the association between the waveform patterns of nocturnal desaturation and clinical findings of patients with IPF. Methods We prospectively enrolled patients with IPF from seven general hospitals between April 2017 and March 2020 and measured nocturnal SpO2 and nasal airflow by using a home sleep apnea test. An algorithm was used to classify the types of nocturnal desaturation. We evaluated the association between sleep or clinical parameters and each waveform pattern of nocturnal desaturation. Results Among 60 patients (47 men) who met the eligibility criteria, there were 3 cases with the sustained pattern, 49 cases with the periodic pattern, and 41 cases with the intermittent pattern. Lowest SpO2 during sleep and total sleep time spent with SpO2 < 90% were associated with the sustained pattern, and apnea–hypopnea index was associated with the intermittent pattern. Conclusion We demonstrated the prevalence of each waveform and association between each waveform and sleep parameters in patients with IPF. This classification algorithm may be useful to predict the degree of hypoxemia or the complication of obstructive sleep apnea.

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