Higher AHI Research Articles

Exploring Sleep-Related Breathing Disorders in Pediatric Obesity and Prader-Willi Syndrome

ObjectiveTo analyze the differences of clinical and diagnostic features of sleep related breathing disorders (SRBDs) between children with PWS and obese children, considering obesity as a unifying risk factor for sleep apnea. Study designThis retrospective cohort study included ≥2 years of age children who had obesity and genetically confirmed Prader-Willi syndrome (PWS) or were non-PWS obese children. Out of 267 children, 58 children met inclusion criteria. Clinical data and records of standard overnight polysomnography (PSG) were collected and compared between groups during the study. ResultsObstructive sleep apnea (OSA) was identified in 97.2% non-PWS obese children and 72.7% PWS children (p=0.072). Central sleep apnea (CSA) events were more commonly found in children with PWS (p=0.035, OR 4.35, CI 95% 1.05-18.03) as well as sleep-related hypoventilation (p=0.016, OR 4.66, CI 95% 1.26-17.34). Sleep efficiency was higher in PWS patients (p=0.038). Sleep fragmentation was significantly associated with higher AHI only in non-PWS obese children (p=0.027). In the PWS group patients, a moderate correlation was found between BMI and age (p=0.025, r=0.559, CI 95% 0.087-0.826) as well as AHI and age (p=0.003, r=0.686, CI 95% 0.232-0.895). ConclusionsNon-PWS obese children, similar to those with PWS, exhibit a high risk of SRBDs. Although CSA and sleep-related hypoventilation may occur more frequently in patients with PWS, OSA remains the predominant disorder. Both patient groups are advised to undergo PSG due to the significant risk of SRBDs, particularly during adolescence.

The Impact of Lung Function on Sleep Monitoring in Obstructive Sleep Apnea Associated with Obstructive Lung Diseases: Insights from a Clinical Study.

Background/Objectives: Obstructive sleep apnea (OSA) and obstructive lung diseases (OLD) are common and interdependent respiratory disorders, where one condition may contribute to the development and worsening of the other (OLDOSA syndrome). The term OLDOSA syndrome includes two different conditions: Overlap syndrome (OVS: OSA + chronic obstructive pulmonary disease, COPD) and Alternative Overlap syndrome (aOVS: OSA + Asthma). Data on the interactions between lung function and respiratory monitoring during sleep in OLDOSA patients are few and controversial. Our study aims to evaluate the impact of lung function impairment on sleep breathing disorders, paying attention to the lack of literature about comparisons between OVS, aOVS, and the impact of small airways disease (SAD) in these patients. Methods: In total, 101 patients with a diagnosis of OSA and asthma or COPD underwent pulmonary function tests (PFTs) and nocturnal home sleep cardiorespiratory monitoring (HSCM). Exclusion criteria: Obesity hypoventilation syndrome (OHS) and other non-respiratory sleep disorders. Results: Sleep time with oxygen saturation below 90% (T90) was negatively correlated with forced expiratory volume in the first second, % of predicted (%FEV1), forced vital capacity, % of predicted (%FVC), forced expiratory flow at 25-75% of the pulmonary volume, % of predicted (%FEF25-75), and, after multivariable linear regression analysis, %FEF25-75 remained an independent factor for T90 with a negative correlation in mild and moderate OSA. Obstructive apnea index (oAI) and FEV1/FVC were negatively correlated in mild and moderate OSA. OVS presented with more severe OSA (higher AHI, oAI, and T90) and SAD (lower FEF25-75) compared to aOVS. Conclusions: This study highlights a possible interdependence between OLD and OSA; obstruction of the large and small airways at PFTs contributes to the worsening of these patients' nocturnal hypoxemia and obstructive events of the upper airway during sleep. Furthermore, this study shows that patients with OVS should be carefully monitored, as they present worse data at HSCM and have greater small airways involvement compared to aOVS.

Gender differences in obstructive sleep apnea syndrome: a pilot study

PurposeOSAS is a syndrome that often presents clinically differently between men and women. The aim of this study was to assess the clinical presentation, nocturnal home sleep cardiorespiratory monitoring and therapeutic adherence to CPAP in both sexes to identify the most frequent patterns.MethodsData from the first visit, the nocturnal home sleep cardiorespiratory monitoring and follow-up visit of 74 OSA patients were collected. Exclusion criteria included other respiratory and/or neuromuscular diseases (including Obesity hypoventilation syndrome) and other non-respiratory sleep disorders.ResultsMen were older and had a higher supine AHI and ODI compared to women. In addition, BMI and age correlated positively with AHI in males. Women had a higher hypopneas frequency and better therapeutic adherence to CPAP.ConclusionsMen were associated with a higher AHI when sleeping in the supine position and this may be useful to look for new therapeutic options in combination with or as an alternative to CPAP. BMI correlated positively with AHI in men and this should be considered to stimulate weight loss as the main treatment to reduce the number of apneas/hypopneas, as men also had less therapeutic adherence to CPAP in our study. Females presented a significantly higher frequency of hypopneas than men, as well as a lower number of desaturation events per hour (ODI): these differences in the nocturnal home sleep cardiorespiratory monitoring could reflect different pathophysiological mechanisms of OSAS onset between the two sexes, which should be investigated in future scientific studies.

Sleepiness and Vitamin D Levels in Patients with Obstructive Sleep Apnea.

The aim of this cross-sectional study is to explore the association between serum 25-hydroxyvitamin D [25(OH)D] levels, a marker of Vitamin D status, and excessive daytime sleepiness (EDS), expressed as increased scores of the Epworth Sleepiness Scale (ESS), in a group of prospectively enrolled patients with obstructive sleep apnea (OSA). Newly diagnosed patients with OSA, divided into two groups, those with EDS (ESS > 10) and those without EDS (ESS < 10). All patients underwent night polysomnography. Measurement of serum 25(OH)D vitamin was performed using a radioimmunoassay. In total, 217 patients with OSA (197 males and 20 females) were included. Patients with EDS had higher AHI (p < 0.001) values and lower mean serum 25(OH)D levels, compared with those of non-somnolent patients [17.4 (12.2-25.7) versus 21.1 (15.3-28.8) ng/mL, respectively, p = 0.005]. In patients with EDS, serum 25(OH)D levels correlated with average oxyhemoglobin saturation during sleep (r = 0.194, p = 0.043), and negatively with ESS score (r = -0.285, p = 0.003), AHΙ (r = -0.197, p = 0.040) and arousal index (r = -0.256, p = 0.019). Binary regression analysis identified Vit D serum levels (β = -0.045, OR: 0.956, 95% CI: 0.916-0.997, p = 0.035), total sleep time (β = 0.011, OR: 1.011, 95% CI: 1.002-1.021, p = 0.016) and AHI (β = 0.022, OR: 1.022, 95% CI: 1.003-1.043, p = 0.026) as independent predictors of EDS in patients with OSA. In patients with EDS, multiple regression analysis indicated that ESS score was negatively associated with Vit D serum levels (β = -0.135, p = 0.014) and minimum oxyhemoglobin saturation during sleep (β = -0.137, p = 0.043). In the present study, EDS in patients with OSA is associated with low levels of Vitamin D, while sleep hypoxia may play a role in this process.

Changes of Serum Adiponectin Level in Patients with Obstructive Sleep Apnea Hypopnea Syndrome and Its Relationship with Sleep Monitoring Indexes.

To observe the changes of serum adiponectin (AP) levels in patients with obstructive sleep apnea hypopnea syndrome (OSAHS) and explore the correlation between serum AP and polysomnography (PSG) parameters in patients with OSAHS. The data of subjects who underwent PSG at the hospital between January 2021 and December 2022 were collected retrospectively and divided into simple snoring group (AHI < 5 times/h, n = 45), mild OSAHS group (5 ≤ AHI < 15 times/h, n = 63), moderate OSAHS group (15 ≤ AHI ≤ 30 times/h, n = 52), and severe OSAHS group (AHI > 30 times/h, n = 60). The general data, PSG indices, and serological indices of the subjects were collected and compared between groups. Pearson correlation analysis and partial correlation analysis were employed to examine the correlation between serum AP level and PSG parameters. Ordered logistic regression was employed to analyze the risk factors influencing the severity of OSAHS. The predictive capability of the serum AP level in determining the occurrence of OSAHS was assessed using ROC. The serum AP levels of subjects with different subtypes of PSG indicators were compared. In the simple snoring group, mild OSAHS group, moderate OSAHS group, and severe OSAHS group, there were statistically significant differences in microarousal count, MAI, AHI, times of blood oxygen decreased by ≥ 3%, L-SaO2, and TS90% among the 4 groups (P < 0.05). The level of serum AP was positively correlated with L-SaO2 and negatively correlated with the proportion of REM, microarousal count, MAI, AHI, times of blood oxygen decreased by ≥ 3%, TS90%, and LP (P < 0.05). High AHI was a risk factor affecting the severity of OSAHS (95% CI: 1.446-4.170). The AUC of serum AP level in diagnosing OSAHS was 0.906 (95% CI: 0.8601-0.9521), and when the Youden Index was 0.678, the sensitivity was 88.9%, and the specificity was 78.9% (P < 0.0001). In the population with a high microarousal count, high AHI, and high times of blood oxygen decreased by ≥ 3% and high TS90%, the serum AP level was lower than that in the low-level population (P < 0.05). In the population with high L-SaO2, the serum AP level was higher than that in low-level population (P < 0.05). The level of serum AP decreased with the increase of the disease severity of patients with OSAHS and demonstrates a significant predictive capability for the occurrence of OSAHS. Monitoring the level of serum AP can effectively forecast the risk of OSAHS. Furthermore, alterations in serum AP levels are associated with both hypoxemia and a heightened frequency of arousal in patients with OSAHS.

Abstract 19050: Polysomnography and Sleep Symptom-Based Patient Profiles Associated With Atrial Fibrillation Development

Introduction: Although sleep disorders are linked to atrial fibrillation (AF), the complex interplay remains unclear. Investigating sleep-based profiles associated with AF can deepen understanding and identify at-risk patients. Hypothesis: We hypothesized discrete phenotypes of symptoms and polysomnography (PSG)-based data differ in relation to incident AF. Methods: This retrospective cohort study of Cleveland Clinic patients (age&gt;18) who underwent PSG 11/27/2004-12/30/2015 identified patient clusters using latent class analysis of 23 sleep-related symptoms, Epworth Sleepiness Scale (ESS) score, and 24 PSG measures of sleep disordered breathing and architecture. Cox proportional hazards models with cluster membership as the independent variable and incident AF as the dependent variable were adjusted for age, sex, race, BMI, cardiopulmonary disease and risk factors, anti-arrhythmic medication, and positive airway pressure with follow up 7.6±3.4 years. Results: Of the sample (n=43,433, age 52±15, 52% male, 74% White) 9% developed AF. Five clusters were identified: 1) Hypoxic + Sleepy (n=3,245): highest % time SaO 2 below 90%, highest ESS, 2) Apneas + Arousals (n=4,592): highest AHI, highest arousal index, 3) Short sleep + Low %REM (n=6,126): shortest sleep duration, longest REM latency, lowest %REM, 4) Hypopneas (n=2,661): most hypopneas, 5) Long sleep + High %REM (n=26,809): longest sleep duration, shortest REM latency, highest %REM (reference). Compared to reference, Hypoxic + Sleepy had 48% (HR=1.48, 95%CI=1.34-1.64), Apneas + Arousals had 22% (HR=1.22, 95%CI=1.11-1.35), and Short Sleep + Low %REM had 11% (HR=1.11, 95%CI=1.01-1.22) higher risk of AF development. Internal validation indicated reasonable predictive accuracy. Sensitivity analysis excluding split night studies confirmed the associations observed. Conclusions: Of 5 patient profiles identified, Hypoxic + Sleepy conferred the strongest AF risk. Consistent with prior evidence of hypoxia as an AF driver and cardiovascular risk of the sleepy phenotype, this constellation of symptoms and physiology illustrates risk in the clinical setting, providing potential value as a risk prediction tool. Future investigation will focus on external validation of these findings.

O011 Exploring Nocturnal Blood Pressure Surges Relationships with Brain Health and Cognitive Function.

Abstract Introduction Cerebral small vessel disease is a possible mechanism to explain the link between long-term incompletely treated obstructive sleep apnoea (OSA) and dementia. Recent evidence suggests nocturnal blood pressure (BP) surges triggered by OSA-related sympathetic hyperactivity could play a critical role. However, this remains to be determined as they often occur concurrently with desaturation events. Methods During an in-lab polysomnography study of 7 controls [AHI≤5] and 20 untreated OSA patients [AHI&amp;gt;5] aged 45-65 years the frequency of blood pressure surges (&amp;gt;10% systolic ↑BP) in the presence or not of desaturation events (↓SpO2&amp;gt;3%) were quantified with a SOMNOtouch™ NIBP device. Cerebral perfusion was assessed with pCASL MRI and brain lesions with anatomical MRI scans. The global deficit score was determined for cognitive function assessment. Inflammation was quantified with blood hs-CRP. Results After controlling for age, BMI, gender, blood glucose and cholesterol, higher AHI was associated with more frequent BP surges (r=0.52, P=0.03), BP surges occurring with desaturation events (r=0.87, P&amp;lt;0.001), but not with BP surges without oxygen desaturation (P = 0.11). Concurrent BP surges and oxygen desaturation was associated with increased hs-CRP (r=0.55, P=0.02). Frequency of BP surges was not related to cerebral perfusion, brain lesions or the global deficit score. Conclusions Recording nocturnal blood pressure surges during polysomnography may provide insight into the cardiovascular burden associated with OSA. Interestingly, an inflammatory response is associated with BP surges only during desaturations, i.e. during respiratory events. Further work is needed to assess the utility of BP surges in predicting longer-term cognitive deficits.

The Application of Ultrasound to Quantify Hyoid Motion During Drug-Induced Sleep Endoscopy.

The significance of hyoid dynamics in OSA pathophysiology remains unclear. Drug-induced sleep endoscopy (DISE) is often used for evaluating patients intolerant to positive airway pressure (PAP) therapy. We performed DISE with concurrent hyoid-focused ultrasonography to quantify hyoid dynamics during obstructive and non-obstructive breathing. A cross-sectional analysis from a prospective cohort of patients undergoing DISE with PAP titration (DISE-PAP) and hyoid-focused ultrasound was conducted. Hyoid ultrasound was performed during obstructive breathing, and non-obstructive breathing after PAP administration. Motion was quantified by generating displacement curves based on echo-tracking hyoid movement. The image analysis protocol for quantifying hyoid displacement was performed independently by two researchers, and reliability of measures was assessed. Univariate and multivariate regressions were performed for various clinical data and hyoid displacement during obstructive breathing. Twenty patients met inclusion criteria. On average, the cohort was male (75%), elderly (65.9 ± 10 years), overweight (29.3 ± 3.99 kg/m2 ), and with moderate-to-severe OSA (29.3 ± 12.5 events/h). Mean hyoid displacement during obstructive breathing was 5.81 mm (±3.48). In all patients, hyoid displacement decreased after PAP administration (-3.94 mm [95% CI: -5.10, -2.78]; p < 0.0001). Inter-rater reliability for measures of hyoid displacement was excellent. After multivariate regression, hyoid displacement at baseline was associated with higher AHI (β [95% CI] = 0.18 [0.03, 0.33], p = 0.020). During DISE, hyoid displacement is greater during obstructive breathing with significant variability amongst patients. Further, these ultrasonographic measurements had excellent intra- and inter-rater reliability. Additional, larger studies are needed to understand contributors to hyoid mobility. 4 Laryngoscope, 133:3221-3227, 2023.

0891 Sex-Specific Differences in Polysomnographic Biomarkers of Sleep Disruption and Sleep Disordered Breathing in Migraine

Abstract Introduction The importance of sex as a biological variable on the relationship of migraine and sleep disturbance has not been well-characterized. Given evidence of 1)bidirectional relationships of poor sleep and migraine severity and 2)greater activation of brain regions involved in emotional processing in women compared to men with migraine, we hypothesized that sleep architectural disruption may contribute to sex-specific differences in quality of life measures, particularly those attributed to emotional processing. Methods This was a retrospective cohort study of migraine patients aged &amp;gt;18 years seen in the Cleveland Clinic headache program with polysomnogram data. Migraine burden was measured by the 20-item migraine-specific quality of life(MSQOL) encompassing three domains: emotional function(EF), role function-preventative, and role function-restrictive. Linear regression models were used to assess the association of each MSQOL domain with sleep architectural measures and the statistical interaction with sex was examined. Coefficients and 95% confidence intervals were estimated and compared with adjustment of age, race, body mass index(BMI) and comorbidities. Results Of 245 patients with migraine,37(15.1%) were male. Males had higher AHI (10.0 [5.3, 18.5] vs. 5.7[1.8, 11.4], p=0.006). The difference in MSQOL-EF scores was not statistically significant (males:73.3[53.3,86.7] vs. females:60.0 [33.3,80.0], p= 0.066). There was no statistical difference in percent N2 or REM between sexes, though males had greater %N1, and lower %N3 (10.9[5.9,19.2] vs. 6.6[4.1,11.9],p=0.039). The association of MSQOL-EF with percent of N2 and REM sleep differed by sex. For each 5% increase in N2, there was a 5% reduction of MSQOL-EF 2.08 (-2.08, 95%CI [-6.86,2.70],p=0.39) in females compared to a 6.84 reduction in males (-6.84, 95%CI [-15.9,2.22],p=0.14), p-value for interaction=0.044. For each 5% increase in REM, MSQOL-EF increased 1.26 (1.26, 95%CI [-3.68,6.21],p=0.61) in females, and increased by 6.27 in males (6.27, 95%CI [-3.11,15.6], p=0.19),p-value for interaction=0.044. Conclusion Although males had greater sleep disruption compared to females, there was no significant difference in MSQOL-EF scores. However, sex-specific differences of extent of sleep stage composition and MSQOL-EF were observed suggesting influence of sleep architectural alterations on greater responsivity of migraine emotional processing in men versus women. Future investigation should better characterize longitudinal relationships and underlying neurobiological mechanisms underlying these findings. Support (if any) Association of Migraine Disorders

Alzheimer's disease biomarkers in patients with obstructive sleep apnea hypopnea syndrome and effects of surgery: A prospective cohort study.

Obstructive sleep apnea hypopnea syndrome (OSAHS) may cause Alzheimer's disease (AD), t-tau, p-tau, Aβ42, and Aβ40 are important elements in the process of AD, and changes in the levels of these biomarkers may affect the cognitive functioning of patients. Our objective was to investigate whether uvulopalatopharyngoplasty could reduce the plasma levels of AD biomarkers in OSAHS patients and the potential correlations of AD biomarkers with cognitive impairment and sleepiness, and explore the independent influencing factors of cognitive function. Alzheimer's disease biomarkers were measured in the plasma of 35 patients with severe OSAHS requiring surgical treatment and 16 healthy controls without OSAHS. The cognitive function and sleepiness of OSAHS patients was also evaluated. The case group was given uvulopalatopharyngoplasty and followed at the postoperative sixth month, the follow-up cases were 27, and plasma AD biomarker levels, cognitive function, and sleepiness were re-evaluated. The preoperative and postoperative AD biomarker levels OSAHS patients were compared with each other and those of the control group. Linear stepwise regression and lasso regression were used to explore the relationships of AD biomarkers with cognitive impairment and sleepiness. Significantly higher Aβ40, t-tau, p-tau in plasma were observed preoperatively in OSAHS patients comparing to controls (29.24 ± 32.52 vs. 13.18 ± 10.78, p = 0.049; 11.88 ± 7.05 vs. 7.64 ± 4.17, p = 0.037; 26.31 ± 14.41 vs. 17.34 ± 9.12, p = 0.027). The sixth month of postoperation, the plasma AD biomarkers (Aβ42, Aβ40, t-tau, p-tau) in plasma levels decreased significantly (0.23 ± 0.17 vs. 0.20 ± 0.16, p = 0.0001; 29.24 ± 32.52 vs. 23.52 ± 24.46, p = 0.0046; 11.88 ± 7.05 vs. 8.88 ± 6.21, p = 0.0001;26.31 ± 14.41 vs. 20.43 ± 10.50, p = 0.0001). A comparison of MMSE and ESS scores from before to after surgery revealed obvious differences (27.14 ± 1.65 vs. 29.07 ± 1.78, p = 0.0001; 11.91 ± 4.84 vs. 5.89 ± 2.83, p = 0.0001). Changes in cognitive function and sleepiness scores from before to after uvulopalatopharyngoplasty were significantly correlated with AD biomarkers. Body mass index and t-tau were potential influencing factors cognitive function. Obstructive sleep apnea hypopnea syndrome can increase plasma AD biomarkers levels. Uvulopalatopharyngoplasty can improve patients' cognition and sleepiness, and the mechanism may be related to changes in plasma AD biomarkers. Higher AHI and higher t-tau level were identified as independent risk factors for cognitive decline.

Effect of Respiratory Events on Health-Related Quality of Life in Patients Treated with Long-Term Noninvasive Ventilation

Background: Long-term noninvasive ventilation (NIV) can increase or maintain health-related quality of life (HRQoL) for patients with chronic hypercapnic respiratory failure (CHRF). Evidence from studies systematically assessing how NIV-specific factors influence HRQoL is limited. Objectives: The objective of this study was to describe HRQoL measured by the Severe Respiratory Insufficiency Questionnaire (SRI) in patients with CHRF treated with long-term NIV and to analyze the associations between HRQoL and hypoxemia, hypercapnia, and respiratory events such as apneas, hypopneas (AHI), and patient ventilator asynchrony (PVA) occurring during long-term NIV. Methods: We included sixty-seven stable patients with established long-term NIV due to neuromuscular disease or thoracic cage disorders in a prospective cross-sectional study at Oslo University Hospital. Patients answered the SRI and underwent daytime arterial blood gases, nocturnal pulse oximetry, sleep polygraphy, and nocturnal transcutaneous CO₂. Results: The mean global SRI for 62 patients was 64.8 ± 14.5, with the highest score in SRI Social Relationships (79.5 ± 15.6). There were no differences in HRQoL between the different patient groups. Compliant patients had a significantly higher score in SRI Attendant and Sleep. Residual nocturnal hypoxemia affected both the subscale SRI “Respiratory Complaints” and SRI “Attendant Symptoms and Sleep.” Persisting daytime hypercapnia, nocturnal hypoventilation, and high AHI affected the subscale SRI “Anxiety” negatively, while frequent PVA was associated with a lower score in SRI “Physical Function.” Conclusion: In a group of patients with long-term NIV, undesired respiratory events during NIV are associated with lower HRQoL in several of the SRI subscales. We suggest designing interventional studies to confirm the possible relationship between HRQoL and respiratory events during long-term NIV.

0757 Cluster Analysis for Identifying Good CPAP Adherence Using the PSG Parameters and Patient Characteristics

Abstract Introduction CPAP is the standard treatment for obstructive sleep apnea (OSA). One of the important clinical issues to be solved is poor CPAP adherence. A growing body of studies has identified predictive factors for CPAP adherence including AHI, BMI, age, gender, symptoms, etc. When our sleep physicians prescribe CPAP, we would consider these known factors in multiple ways. One may want to know factors' combinations rather than each factor. In this case, cluster analysis might be useful since it is a powerful data-mining tool to sort various factors into meaningful groups. Recently, cluster analysis has been adopted for research of sleep breathing disorders. However, no one has adopted to predict CPAP adherence. In this study, we aimed to explore the usefulness of cluster analysis to predict CPAP adherence using the diagnostic PSG parameters and patients’ characteristics. Methods The study design was a retrospective observational multi-center study including 5 certified sleep centers in Japan. For 2 years from 2017, 1133 patients who were diagnosed with OSA with in-lab PSG and newly initiated CPAP therapy were enrolled. We performed cluster analysis using the K-means clustering. Variables for clustering were determined by several sleep physicians among PSG parameters and patients’ characteristics. We assessed CPAP adherence for 90 days and 365 days after CPAP initiation in each created cluster. We adopted CMS criteria for good CPAP adherence, which is, more than four hours of use on 70% of nights. Results Cluster analysis classified 5 clusters. A significant difference in CPAP adherence for 90 days and 365 days was seen among 5 clusters with a test of independence (p=0.001, p=0.005, respectively). The cluster presenting moderate obese, very high AHI and ODI, and apnea predominant indicated good adherence, whereas the cluster presenting morbid obese, very high AHI and ODI, sustained severe hypoxia, younger age, and daytime sleepiness indicated poor adherence according to the post-hoc Chi-square test. Conclusion Cluster analysis successfully distinguished the different CPAP adherence and identified a combination of OSA patients’ profiles. Thus, cluster analysis would be a useful tool for predicting long-term CPAP adherence. Support (If Any)

Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation

BackgroundHigh loop gain (unstable ventilatory control) is an important—but difficult to measure—contributor to obstructive sleep apnea (OSA) pathogenesis, predicting OSA sequelae and/or treatment response. Our objective was to develop and validate a clinical prediction tool of loop gain.MethodsA retrospective cohort of consecutive adults with OSA (apnea–hypopnea index, AHI > 5/hour) based on in-laboratory polysomnography 01/2017–12/2018 was randomly split into a training and test-set (3:1-ratio). Using a customized algorithm (“reference standard”) loop gain was quantified from raw polysomnography signals on a continuous scale and additionally dichotomized (high > 0.7). Candidate predictors included general patient characteristics and routine polysomnography data. The model was developed (training-set) using linear regression with backward selection (tenfold cross-validated mean square errors); the predicted loop gain of the final linear regression model was used to predict loop gain class. More complex, alternative models including lasso regression or random forests were considered but did not meet pre-specified superiority-criteria. Final model performance was validated on the test-set.ResultsThe total cohort included 1055 patients (33% high loop gain). Based on the final model, higher AHI (beta = 0.0016; P < .001) and lower hypopnea-percentage (beta = −0.0019; P < .001) predicted higher loop gain values. The predicted loop gain showed moderate-to-high correlation with the reference loop gain (r = 0.48; 95% CI 0.38–0.57) and moderate discrimination of patients with high versus low loop gain (area under the curve = 0.73; 95% CI 0.67–0.80).ConclusionTo our knowledge this is the first prediction model of loop gain based on readily-available clinical data, which may facilitate retrospective analyses of existing datasets, better patient selection for clinical trials and eventually clinical practice.

Influence of age on adherence to auto-CPAP: experience from a sleep center in Portugal.

Obstructive sleep apnea (OSA) is a disorder characterized by obstructive apneas, hypopneas, and/or arousals related to respiratory effort caused by repetitive collapse of the upper airway during sleep. Left untreated, or with poor adherence to treatment, is likely to lead to negative outcomes, especially cardiac or cerebrovascular diseases. Our objective was to investigate age as a potential factor that may interfere with adherence to treatment with automatic positive airway pressure (APAP). This is a cross-sectional study on 1151 patients with OSA and we analyzed the adherence data of all patients who had been on APAP for at least six months during the period from July 1, 2019 to December 31, 2020 at Centro de Medicina do Sono. Spearman correlation was used in the bivariate analysis and to determine the factors associated with APAP adherence, a logistic regression was performed. Of 1151 patients included, 780 patients were men (67.1%) and the majority was under 65 years (59.4%). APAP adherence was higher in older age groups (p<0.001) and in patients with a higher AHI (p < 0.001), no differences were observed with regards to gender. In the multivariable regression analysis, the main factors associated with adherence were age group over 65 years (OR = 2.435; 95% CI = 1.862-3.185), AHI 15-30/h (OR = 1.733; 95% CI = 1.242-2.416), and AHI > 30/h (OR = 3.406; 95% CI = 2.426-4.782). Patients older than 65 years have better adherence to APAP than younger ones and with moderate but especially severe AHI have better adherence than those with the milder form of the disease.

Obstruktive Schlafapnoe: Modell zur Vorhersage des Loop Gains aus polysomnographischen Routinedaten

&lt;b&gt;Background:&lt;/b&gt; High loop gain (unstable ventilatory control) is an important – but difficult to measure – contributor to obstructive sleep apnea (OSA) pathogenesis, predicting OSA sequelae and/or treatment response. Our objective was to develop and validate a clinical prediction tool of loop gain. &lt;b&gt;Methods:&lt;/b&gt; A retrospective cohort of consecutive adults with OSA (apnea–hypopnea index, AHI &amp;#x3e; 5/hour) based on in-laboratory polysomnography 01/2017–12/2018 was randomly split into a training and test-set (3:1-ratio). Using a customized algorithm («reference standard») loop gain was quantified from raw polysomnography signals on a continuous scale and additionally dichotomized (high &amp;#x3e; 0.7). Candidate predictors included general patient characteristics and routine polysomnography data. The model was developed (training-set) using linear regression with backward selection (tenfold cross-validated mean square errors); the predicted loop gain of the final linear regression model was used to predict loop gain class. More complex, alternative models including lasso regression or random forests were considered but did not meet pre-specified superiority-criteria. Final model performance was validated on the test-set. &lt;b&gt;Results:&lt;/b&gt; The total cohort included 1055 patients (33% high loop gain). Based on the final model, higher AHI (beta = 0.0016; P &amp;#x3c; .001) and lower hypopnea-percentage (beta = -0.0019; P &amp;#x3c; .001) predicted higher loop gain values. The predicted loop gain showed moderate-to-high correlation with the reference loop gain (r = 0.48; 95% CI 0.38–0.57) and moderate discrimination of patients with high versus low loop gain (area under the curve = 0.73; 95% CI 0.67–0.80). &lt;b&gt;Conclusion:&lt;/b&gt; To our knowledge this is the first prediction model of loop gain based on readily-available clinical data, which may facilitate retrospective analyses of existing datasets, better patient selection for clinical trials and eventually clinical practice.

A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy

BackgroundSleep apnea patients on CPAP therapy exhibit differences in how they adhere to the therapy. Previous studies have demonstrated the benefit of describing adherence in terms of discernible longitudinal patterns. However, these analyses have been done on a limited number of patients, and did not properly represent the temporal characteristics and heterogeneity of adherence.MethodsWe illustrate the potential of identifying patterns of adherence with a latent-class heteroskedastic hurdle trajectory approach using generalized additive modeling. The model represents the adherence trajectories on three aspects over time: the daily hurdle of using the therapy, the daily time spent on therapy, and the day-to-day variability. The combination of these three characteristics has not been studied before.ResultsApplying the proposed model to a dataset of 10,000 patients in their first three months of therapy resulted in nine adherence groups, among which 49% of patients exhibited a change in adherence over time. The identified group trajectories revealed a non-linear association between the change in the daily hurdle of using the therapy, and the average time on therapy. The largest difference between groups was observed in the patient motivation score. The adherence patterns were also associated with different levels of high residual AHI, and day-to-day variability in leakage.ConclusionThe inclusion of the hurdle model and the heteroskedastic model into the mixture model enabled the discovery of additional adherence patterns, and a more descriptive representation of patient behavior over time. Therapy adherence was mostly affected by a lack of attempts over time, suggesting that encouraging these patients to attempt therapy on a daily basis, irrespective of the number of hours used, could drive adherence. We believe the methodology is applicable to other domains of therapy or medication adherence.

422 Influence of Sex-Specific Differences in Inpatient Sleep Testing Approach for Diagnosis of Obstructive Sleep Apnea

Abstract Introduction Increased attention has been focused on sex-specific differences in approaches to diagnostic testing for obstructive sleep apnea (OSA) given differences in hypoxia, arousal thresholds and sleep state dependent influences, but with sparse data available for inpatient testing. We postulate that women are more likely to have a lesser degree of sleep apnea on inpatient home sleep apnea testing (HSAT) versus polysomnography (PSG). Methods The Cleveland Clinic Sleep Laboratory registry was queried for inpatient sleep testing (HSAT or PSG conducted over the last 15 years. Demographics, comorbidities, and sleep study (Nihon Kohden®) data were collated. Logistic regression was used to examine sleep study type predictive of OSA at various severity thresholds (apnea hypopnea index (AHI, 3 or 4% hypopnea rule)&amp;gt;5,&amp;gt;15 and &amp;gt;30 and hypoxia (11% (median) time spent with SaO2&amp;lt;90%) adjusted for age, race and body mass index and comorbidities (hypertension, coronary artery disease, arrhythmias, heart failure, diabetes, stroke, chronic obstructive pulmonary disease, mood disorders, respiratory failure and epilepsy with a sex interaction term) (OR, 95%CI presented). Results The analytic sample was comprised of 639 patients: age:55.8±16.3 years, 45% female, 73% Caucasian, BMI:37.5 ± 13.3kg/m2, 74% had OSA and 51% HSAT. Men had higher AHI:16.2 [5.9, 42.3] vs 8.2 [2.9, 20.7]p&amp;lt;0.001, higher arousal index:33.1[18.9,.54] vs 25.3 [15.6, 39.2]p=0.003. Women had higher BMI:40.2 ±14.7, vs 36 ±11.7kg/m2,p&amp;lt;0.001. Unlike AHI&amp;gt;5, at AHI&amp;gt;15, men had lower odds of OSA: OR=0.51:0.32–0.80,p=0.004 for HSAT versus PSG compared to women: OR=1.03:0.61–1.72,p=0.92; interaction p-value=0.046. Men had lower odds of OSA (AHI &amp;gt;30): OR=0.57(0.35,0.92,p=0.022) in HSAT vs PSG; albeit sex-interaction was not statistically significant. Men versus women had 2-versus 3-fold higher hypoxia ie. OR=2.04:1.22–3.41,p=0.006 in men undergoing HSAT versus PSG with strength of association higher in women: OR=3.03:1.68–5.46,p=0.001, interaction p-value=0.32 Conclusion We unexpectedly observe sex-specific differences in inpatient sleep testing such that men had an overall lower odds of detection of moderate to severe and OSA and nocturnal hypoxia relative to women with HSAT versus PSG. Future investigation focused on concurrent inpatient PSG and HSAT should verify these sex-specific findings and clarify potential biophysiologic rationale Support (if any) Transformative Neuroscience Research Development Program: Multimodal Neurocardiorespiratory Physiologic Sleep Signal Repository Transformative Resource Facilitating Transdisciplinary Research Opportunities

468 Optimizing treatment of the intra-oral negative air pressure for obstructive sleep apnea

Abstract Introduction The intra-oral negative air pressure device (iNAP) is designed to develop a negative pressure gradient in the oral cavity of the user. The pressure gradient provides a force to move the tongue and soft palate forward. Previous works show the treatment response rate of intra-oral pressure therapy varying between 25–79%. However, for those OSA patients with very high BMI or AHI, they may need higher pressure to achieve optimizing treatment outcome. Methods To provide an optimizing treatment of intra-oral pressure, 30 patients treated with iNAP successfully completed one baseline PSG and one treatment PSG with in-laboratory pressure adjustment. When conducting the iNAP titration PSG, the initial treatment pressure is 40mmHg. iNAP pressure should be increased by at least 10mmHg an interval no shorter than 15 min. In order to eliminate obstructive respiratory events, iNAP pressure should be increased when observe obstructive apnea or hypopnea or unambiguous snoring. Results A total of 30 patients presented their consent to participate in this study. The mean age of the patients was 51.2 ± 13.97 years, and their mean body mass index (BMI) was 25.87 ± 3.41 kg/m2. The mean baseline AHI was 39.59 ± 20.05 events/h, which decreased significantly to 8.17 ± 8.11 events/h. No significant change in sleep efficacy, and percentage of N1 stage was found in the treatment PSG. However, significant improvements in the percentage of N3 stage, Min SpO2, and arousal index were observed in the treatment PSG. Conclusion In this study, the clinical response rate, as defined by the Sher criteria, was 86% (26/30 patients), when the Tx PSG response was compared with the baseline values. Besides, the mean AHI under final titration pressure is 2.58. The results show that increasing intraoral pressure would help to further improve the sleep apnea. Support (if any) This study was sponsored by Somnics, Inc.

OBSTRUCTIVE SLEEP APNEA AS A RISK FACTOR OF INSULIN RESISTANCE IN NONDIABETIC PATIENTS

Objective: Obstructive sleep apnea (OSA) is a common sleep-breathing disorder characterised by collapsing of upper airway during sleep. The aim of this research was to assess relationship beetwen prevalence and severity of OSA and insulin resistance in nondiabetic individuals among patients with increased risk of OSA without diabetes mellitus. Design and method: Our study group estimated 102 individuals with suspected OSA, 71 men and 31 women, mean age 53.02 SD ± 12.37. We excluded individuals with diabetes mellitus and taking hypoglycemic drugs. All patients underwent standardized full night polysomnography in sleep laboratory to diagnose OSA. The Epworth Sleepiness Scale was used to assess daytime sleepiness. Serum insulin and glucose levels were analyzed by Laboratory. The HOMA index was calculated. Results: OSA was diagnosed in 85 patients. Mean AHI in whole study group was 25.78 ± 24.84, mean AHI in group with diagnosed OSA amount to 30.49 ± 24.64, mean AHI in nonapneic patients stands up to 2.23 ± 1.49. The difference was statistically significant p &lt; 0.001. The oxygen desaturation index (ODI) in our study sample estimated about 25 (24.99 ± 23.25), the difference between group with OSA (mean ODI 29.31 ± 23.14) and group without OSA (mean ODI 3.38 ± 2.42) was statistically relevant p &lt; 0.001. The statistically significant differences have occured between patients with (AHI = 15 or AHI &gt; 15) and AHI &lt; 15 taking into account level of insulin and the Homa index p &lt; 0.05, but no statistically significant difference was observed between patients with (ESS = 9 or ESS &gt; 9) and ESS &lt; 9. Conclusions: Individuals with moderate to severe obstructive sleep apnea without diabetes mellitus have higher insulin resistance estimated with HOMA- IR index. This study revealed that there is no evidence if the evaluation of daytime sleepiness using Epworth Sleepiness Scale is a predicting factor of developing IR. Higher AHI and ODI levels beyond individuals from our study sample are independent risk factors for higher fasting insulin levels and higher HOMA index. Increased duration of desaturation time below 90% is an independent risk factor for higher fasting glucose levels.

PAP-therapy adherence in patients with obstructive sleep apnea and cardiovascular diseases

Materials and methods. The study included 119 patients with obstructive sleep apnea (OSA) and cardiovascular diseases (CVD) who were followed up at the National Medical Research Center of Cardiology of the Ministry of Health of the Russian Federation in the period from 2012 to 2020, and have been receiving positive airway pressure (PAP) therapy (93 men, 78.2%). The median follow-up was 3.0 years [1.5; 5.0]. The adherence criteria were the following: the usage of the PAP device for at least 71% of nights a year, and at least 4 hours per night.&#x0D; Results. 64.3% of patients met the criteria for adherence to PAP therapy (use more than 4 hours/night, more than 71% of nights). The adherent patients were older (64.0 years [58.5; 68.0] versus 59.0 years [53.0; 65.0] resp., p=0.03) and had a higher apnea-hypopnea index AHI (47.7 events/h [37.5; 64.4] versus 38.2 events/h [30.4; 52.7] resp., p=0.04).&#x0D; Patients with stage III of hypertension were using a PAP device every night significantly less (3.4 h/night [1.1; 3.6] versus 6.3 h/night [5.3; 7.4] respectively, p=0.00) in comparison with patients with hypertension stages III. The adherence of patients with or without coronary artery disease (CAD) and paroxysmal atrial fibrillation (AF) did not differ. There was no significant difference in the incidence of stage III hypertension, CAD, and permanent AF between the groups of adherent and non-adherent to PAP therapy patients.&#x0D; Conclusion. 63.4% of patients with CVD were adherent to PAP therapy. Adherent patients were older and had a higher AHI. Patients with stage III hypertension were worse adherent to PAP therapy in comparison with patients with hypertension of lesser stages. The CVDs course in adherent and non-adherent patients did not differ.