Suspected Obstructive Sleep Apnea Patients Research Articles

Beat-to-beat cardiac repolarization lability increases during hypoxemia and arousals in obstructive sleep apnea patients.

Obstructive sleep apnea (OSA) is associated with the progression of cardiovascular diseases, arrhythmias, and sudden cardiac death (SCD). However, the acute impacts of OSA and its consequences on heart function are not yet fully elucidated. We hypothesized that desaturation events acutely destabilize ventricular repolarization, and the presence of accompanying arousals magnifies this destabilization. Ventricular repolarization lability measures, comprising heart rate corrected QT (QTc), short-time-variability of QT (STVQT), and QT variability index (QTVI), were calculated before, during, and after 20,955 desaturations from lead II electrocardiography signals of 492 patients with suspected OSA (52% men). Variations in repolarization parameters were assessed during and after desaturations, both with and without accompanying arousals, and groupwise comparisons were performed based on desaturation duration and depth. Regression analyses were used to investigate the influence of confounding factors, comorbidities, and medications. The standard deviation (SD) of QT, mean QTc, SDQTc, and STVQT increased significantly (P < 0.01), whereas QTVI decreased (P < 0.01) during and after desaturations. The changes in SDQT, mean QTc, SDQTc, and QTVI were significantly amplified (P < 0.01) in the presence of accompanying arousals. Desaturation depth was an independent predictor of increased SDQTc (β = 0.405, P < 0.01), STVQT (β = 0.151, P < 0.01), and QTVI (β = 0.009, P < 0.01) during desaturation. Desaturations cause acute changes in ventricular repolarization, with deeper desaturations and accompanying arousals independently contributing to increased ventricular repolarization lability. This may partially explain the increased risk of arrhythmias and SCD in patients with OSA, especially when the OSA phenotype includes high hypoxic load and fragmented sleep.NEW & NOTEWORTHY Nocturnal desaturations are associated with increased ventricular repolarization lability. Deeper desaturations with accompanying arousals increase the magnitude of alterations, independent of confounding factors, comorbidities, and medications. Changes associated with desaturations can partially explain the increased risk of arrhythmias and sudden cardiac death in patients with OSA, especially in patients with high hypoxic load and fragmented sleep. This highlights the importance of detailed electrocardiogram analytics for patients with OSA.

Utilizing Envelope Analysis of a Nasal Pressure Signal for Sleep Apnea Severity Estimation.

Obstructive sleep apnea (OSA) severity assessment is based on manually scored respiratory events and their arbitrary definitions. Thus, we present an alternative method to objectively evaluate OSA severity independently of the manual scorings and scoring rules. A retrospective envelope analysis was conducted on 847 suspected OSA patients. Four parameters were calculated from the difference between the nasal pressure signal's upper and lower envelopes: average (AV), median (MD), standard deviation (SD), and coefficient of variation (CoV). We computed the parameters from the entirety of the recorded signals to perform binary classifications of patients using three different apnea-hypopnea index (AHI) thresholds (5-15-30). Additionally, the calculations were undertaken in 30-second epochs to estimate the ability of the parameters to detect manually scored respiratory events. Classification performances were assessed with areas under the curves (AUCs). As a result, the SD (AUCs ≥ 0.86) and CoV (AUCs ≥ 0.82) were the best classifiers for all AHI thresholds. Furthermore, non-OSA and severe OSA patients were separated well with SD (AUC = 0.97) and CoV (AUC = 0.95). Respiratory events within the epochs were identified moderately with MD (AUC = 0.76) and CoV (AUC = 0.82). In conclusion, envelope analysis is a promising alternative method by which to assess OSA severity without relying on manual scoring or the scoring rules of respiratory events.

O029 Sleep architecture differs for individuals manifesting excessive daytime sleepiness with and without obstructive sleep apnea

Abstract Introduction The mechanism underlying the development of excessive daytime sleepiness (EDS) in obstructive sleep apnea (OSA) remains unclear. Thus, we characterised the association between sleep architecture and EDS in individuals with and without OSA. Methods 1876 suspected OSA patients reporting daytime sleepiness underwent in-lab polysomnography and next-day multiple sleep latency test (MSLT). We investigated sleep architecture characteristics in OSA (apnea-hypopnea index [AHI]≥5, n=1508) and non-OSA (AHI&amp;lt;5, n=368) patients with and without EDS (MSLT≤10-minutes and MSLT&amp;gt;10-minutes). Sleep architecture was quantified by N1, N2, N3, REM, total sleep time (TST), and wake after sleep onset (WASO). Results OSA patients with EDS had less N1 (median: 10.0 vs 12.0-minutes, p&amp;lt;0.05) and N3 (60.2 vs 71.5-minutes, p&amp;lt;0.05) sleep, less WASO (43.0 vs 51.0-minutes, p&amp;lt;0.05), more N2 (210.5 vs 189.0-minutes, p&amp;lt;0.05) sleep, and higher TST (365.0 vs 351.5-minutes, p&amp;lt;0.05) than non-EDS patients. No difference was observed in the amount of REM (70.0 vs 67.5-minutes, p=0.46) sleep. Non-OSA patients with EDS had less WASO (31.5 vs 40.0-minutes, p&amp;lt;0.05), more N2 (188.5 vs 177.5-minutes, p&amp;lt;0.05) sleep, and higher TST (374.5 vs 359.0-minutes, p&amp;lt;0.05) and the amount of REM sleep (76.5 vs 68.5-minutes, p&amp;lt;0.05) than non-EDS patients. Discussion While EDS was associated with less WASO and greater TST and N2 in both OSA and non-OSA groups, there was also characteristic differences. Non-OSA patients with EDS have greater REM sleep duration, while OSA patients with EDS have less N3 sleep. There is likely a complex bi-directional relationship between sleep architecture and EDS reflecting acute/chronic sleep disruption and compensatory mechanisms.

Incidence of difficult airway among adult patients of undiagnosed obstructive sleep apnea who are undergoing elective surgery: a prospective cohort study

Introduction: Obstructive sleep apnea (OSA) is a dangerous medical disorder marked by obstruction of the upper airway during sleep that is frequently undiagnosed before surgery. Preoperative identification of suspected OSA patients necessitates appropriate preparation and prevents unfavorable outcomes. The incidence of difficult airway in adult patients with OSA who are undergoing elective surgery is significantly increased. Materials and method: The study population was separated into high and low-risk groups based on STOP-BANG scores of ≥3 and &lt;3, respectively. The rate of occurrence was compared between the study groups. SPSS version 23 was used for statistical analysis. P-values &lt;0.05 are considered significant. To find characteristics that predict problematic airway, researchers used logistic regression. Result: A total of 113 participants was enrolled. Based on STOP-BANG 77 patients and 36 patients were grouped in to low risk OSA and high risk OSA, respectively, the incidence of difficult intubation (DI) was significantly higher (22.2%) in high risk OSA group versus 5.2% in low risk OSA group, relative risk of 4.278 (95% confidence interval: 1.378–13.2). Mask ventilation was significantly more problematic for the high-risk group (P=0.011) (25% against 6.5%). Male sex, neck circumference &gt;40 cm, Mallampati class 3, and 12.5 cm stern mental distance were all linked to DI. Age above 50 years, snoring history, and a neck circumference of &gt;40 cm were all found to be predictors. Conclusion: Patients who scored ≥3 on the STOP-BANG had a significantly higher rate of DI and difficult mask ventilation. As a result, the STOP-BANG questionnaire should be used to screen every adult patient undergoing elective surgery for OSA.

P021 Does Obstructive Sleep Apnea (OSA) lead to impairment within the cochlea?

Abstract Introduction The cessation of breathing with OSA is linked to the continuous decrease in oxygen saturation throughout the night which could impact the inner ear as it is sensitive to hypoxic changes. Inner ear hair cells response from the cochlea is measured through Transient Otoacoustic Emission (TEOAEs). This study aimed to evaluate TEOAEs in suspected OSA patients and its correlation with oxygen saturation. Methods TEOAEs were measured before sleep and in the morning in suspected OSA patients and healthy participants. The following frequencies were measured: 1000Hz, 1500Hz, 2000Hz, 3000Hz and 4000Hz. Polysomnography with oxygen saturation was completed overnight. Preliminary analysis was completed on 11 no OSA, 22 mild OSA, 13 moderate OSA and 27 severe OSA patients. Results One-way ANOVA with Tukey post-hoc analysis revealed a difference between severe vs mild with average TEOAE only (p = 0.04). A moderate correlation was found between average TEOAE and minimum O2 saturation, rs (72) = 0.444, p&amp;lt; 0.0001) through Spearman’s rank-order correlation. As middle ear function can impact TEOAE results, regression analysis revealed an association between a decrease in TEOAE and lowered minimum O2 saturation (F (1,63) = 8.951, p = 0.004, partial n2 = 0.124) when middle ear pressure was controlled. Discussion Oxygen desaturation with OSA is associated with a decrease in inner ear hair cells response, which was independent from middle ear function. Despite this association, a difference in TEOAE was only found between severe vs mild, which could be due to the current sample size of the preliminary data.

Capacitively-Coupled ECG and Respiration for Sleep-Wake Prediction and Risk Detection in Sleep Apnea Patients.

Obstructive sleep apnea (OSA) patients would strongly benefit from comfortable home diagnosis, during which detection of wakefulness is essential. Therefore, capacitively-coupled electrocardiogram (ccECG) and bioimpedance (ccBioZ) sensors were used to record the sleep of suspected OSA patients, in parallel with polysomnography (PSG). The three objectives were quality assessment of the unobtrusive signals during sleep, prediction of sleep–wake using ccECG and ccBioZ, and detection of high-risk OSA patients. First, signal quality indicators (SQIs) determined the data coverage of ccECG and ccBioZ. Then, a multimodal convolutional neural network (CNN) for sleep–wake prediction was tested on these preprocessed ccECG and ccBioZ data. Finally, two indices derived from this prediction detected patients at risk. The data included 187 PSG recordings of suspected OSA patients, 36 (dataset “Test”) of which were recorded simultaneously with PSG, ccECG, and ccBioZ. As a result, two improvements were made compared to prior studies. First, the ccBioZ signal coverage increased significantly due to adaptation of the acquisition system. Secondly, the utility of the sleep–wake classifier increased as it became a unimodal network only requiring respiratory input. This was achieved by using data augmentation during training. Sleep–wake prediction on “Test” using PSG respiration resulted in a Cohen’s kappa () of 0.39 and using ccBioZ in = 0.23. The OSA risk model identified severe OSA patients with a of 0.61 for PSG respiration and of 0.39 using ccBioZ (accuracy of 80.6% and 69.4%, respectively). This study is one of the first to perform sleep–wake staging on capacitively-coupled respiratory signals in suspected OSA patients and to detect high risk OSA patients based on ccBioZ. The technology and the proposed framework could be applied in multi-night follow-up of OSA patients.

Sleep Diagnostics for Home Monitoring of Sleep Apnea Patients.

Objectives: Sleep time information is essential for monitoring of obstructive sleep apnea (OSA), as the severity assessment depends on the number of breathing disturbances per hour of sleep. However, clinical procedures for sleep monitoring rely on numerous uncomfortable sensors, which could affect sleeping patterns. Therefore, an automated method to identify sleep intervals from unobtrusive data is required. However, most unobtrusive sensors suffer from data loss and sensitivity to movement artifacts. Thus, current sleep detection methods are inadequate, as these require long intervals of good quality. Moreover, sleep monitoring of OSA patients is often less reliable due to heart rate disturbances, movement and sleep fragmentation. The primary aim was to develop a sleep-wake classifier for sleep time estimation of suspected OSA patients, based on single short-term segments of their cardiac and respiratory signals. The secondary aim was to define metrics to detect OSA patients directly from their predicted sleep-wake pattern and prioritize them for clinical diagnosis.Methods: This study used a dataset of 183 suspected OSA patients, of which 36 test subjects. First, a convolutional neural network was designed for sleep-wake classification based on healthier patients (AHI < 10). It employed single 30 s epochs of electrocardiograms and respiratory inductance plethysmograms. Sleep information and Total Sleep Time (TST) was derived for all patients using the short-term segments. Next, OSA patients were detected based on the average confidence of sleep predictions and the percentage of sleep-wake transitions in the predicted sleep architecture.Results: Sleep-wake classification on healthy, mild and moderate patients resulted in moderate κ scores of 0.51, 0.49, and 0.48, respectively. However, TST estimates decreased in accuracy with increasing AHI. Nevertheless, severe patients were detected with a sensitivity of 78% and specificity of 89%, and prioritized for clinical diagnosis. As such, their inaccurate TST estimate becomes irrelevant. Excluding detected OSA patients resulted in an overall estimated TST with a mean bias error of 21.9 (± 55.7) min and Pearson correlation of 0.74 to the reference.Conclusion: The presented framework offered a realistic tool for unobtrusive sleep monitoring of suspected OSA patients. Moreover, it enabled fast prioritization of severe patients for clinical diagnosis.

Total durations of respiratory events are modulated within REM and NREM sleep by sleeping position and obesity in OSA patients

BackgroundSupine sleeping position and obesity are well-known risk factors for obstructive sleep apnea (OSA) and modulate the risk for OSA-related daytime symptoms. Although respiratory event durations are associated with OSA-related severe health consequences, it is unclear how sleeping position, obesity, and daytime sleepiness are associated with respiratory event durations during REM and NREM sleep. We hypothesize that irrespective of the apnea-hypopnea index (AHI), respiratory event durations differ significantly between various OSA subgroups during REM and NREM sleep. MethodsOne night in-lab polysomnographic recordings were retrospectively analyzed from 1910 untreated suspected OSA patients. 599 patients (AHI ≥ 5) were included in study and divided into subgroups based on positional dependency, BMI, and daytime sleepiness (Epworth Sleepiness Scale and Multiple Sleep Latency Test). Differences in total hypopnea time (THT), total apnea time (TAT), and total apnea-hypopnea time (TAHT) within REM and NREM sleep between the subgroups were evaluated. ResultsDuring REM sleep, positional OSA patients had lower THT (OR = 0.952, p < 0.001) and TAHT (OR = 0.943, p < 0.001) than their non-positional counterparts. Compared to normal-weight patients (BMI < 25 kg/m2), obese patients (BMI ≥ 30 kg/m2) had lower THT, TAT, and TAHT (ORs = 0.942–0.971, p ≤ 0.009) during NREM sleep but higher THT (OR = 1.057, p = 0.001) and TAHT (OR = 1.052, p = 0.001) during REM sleep. No significant differences were observed in THT, TAT, and TAHT between patients with and without daytime sleepiness. ConclusionRegardless of the AHI, respiratory event durations vary significantly between OSA sub-groups during REM and NREM sleep. Therefore, to personalize OSA severity estimation the diagnosis should be tailored based on patient's demographics, clinical phenotype, and PSG characteristics.

SAFETY OF A NOVEL SLEEP APNEA TRIAGE TOOL FOR POST-OPERATIVE ORTHOPEDIC SURGERY PATIENTS

SESSION TITLE: Education, Research, and Quality Improvement Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: The purpose of this quality improvement project is to provide a tool for effective and safe triage of post-operative patients in the post-anesthesia care unit with known or suspected obstructive sleep apnea (OSA) at an academic orthopedic hospital in New York City. METHODS: Results are reported from a single center experience in a hospital where there was no standard of care risk assessment tool used in triaging known or suspected OSA patients during the post-operative period. Adult patients who underwent orthopedic surgery between October 2018 and February 2020 who had a known or suspected history of OSA were studied. After admission to the PACU and upon meeting their modified Aldrete criteria or after 2 hours had elapsed, whichever came first, the PACU primary provider used our novel risk-assessment tool to assess whether the patient had high risk criteria related to OSA. Patients without high-risk criteria based on the tool were discharged from the PACU to the general medical/surgical unit. For patients with high-risk criteria, the provider would request critical care consultation in the PACU to determine the patient’s appropriate hospital disposition upon PACU discharge. RESULTS: Over the course of the study period, 216 patients were evaluated using the OSA triage tool. 53.2% of the cohort was male, median BMI was 36.3 kg/m2, 80.1% had prior diagnosis of sleep apnea. Patients had undergone a wide variety of surgeries with 23.6% having undergone hip surgery, 51.4% knee surgery, 13.4% spine surgery, 9.7% shoulder surgery, and 1.9% foot or ankle surgery. Notably, with the use of this tool, only 12.5% of patients met criteria for critical care consult and 91.7% were admitted to the floor from the PACU. Rapid response for respiratory complications were not observed in any of the patients and the three patients that required critical care consult after PACU discharge were related to an acute abdominal issue, tachycardia, and a case of atelectasis. Notably, the anonymous survey was completed by PACU nurse practioners and anesthesiologists and had a 96.8% self-reported satisfaction with guideline implementation tool. CONCLUSIONS: The use of the novel risk assessment tool at NYULMC demonstrated that this tool is a safe and effective method of triaging OSA post-operative patients in the post-anesthesia care unit with known or suspected OSA. Triaging patients using this tool did not result in subsequent rapid responses or mistriage of OSA patients. It allowed for safe care of these patients, reduced critical care resource utilization, and offered a tool perceived to be useful by utilizers. CLINICAL IMPLICATIONS: Implementing the use of this tool in orthopedic patients with obstructive sleep apnea in the post-surgical setting could be an effective and safe means of triaging these patients appropriately without increasing the risk of harm to patients in the post-op period. DISCLOSURES: No relevant relationships by Eric Bondarsky, source=Web Response No relevant relationships by Ezra Dweck, source=Web Response No relevant relationships by Chase Hardwick, source=Web Response No relevant relationships by Bashar Mourad, source=Web Response No relevant relationships by Theresa Reilly, source=Web Response No relevant relationships by Sheeja Schuster, source=Web Response

Point-of-Care Ultrasound for Obstructive Sleep Apnea Screening: Are We There Yet? A Systematic Review and Meta-analysis.

Perioperative diagnosis of obstructive sleep apnea (OSA) has important resource implications as screening questionnaires are overly sensitive, and sleep studies are expensive and time-consuming. Ultrasound (US) is a portable, noninvasive tool potentially useful for airway evaluation and OSA screening in the perioperative period. The objective of this systematic review was to evaluate the correlation of surface US with OSA diagnosis and to determine whether a point-of-care ultrasound (PoCUS) for OSA screening may help with improved screening in perioperative period. A search of all electronic databases including Medline, Embase, and Cochrane Database of Systematic Reviews was conducted from database inception to September 2017. Inclusion criteria were observational cohort studies and randomized controlled trials of known or suspected OSA patients undergoing surface US assessment. Article screening, data extraction, and summarization were conducted by 2 independent reviewers with ability to resolve conflict with supervising authors. Diagnostic properties and association between US parameters (index test) and OSA diagnosis using sleep study (reference standard) were evaluated. The US parameters were divided into airway and nonairway parameters. A random-effects meta-analysis was planned, wherever applicable. Of the initial 3865 screened articles, 21 studies (7 airway and 14 nonairway) evaluating 3339 patients were included. Majority of studies were conducted in the general population (49%), respirology (23%), and sleep clinics (12%). No study evaluated the use of US for OSA in perioperative setting. Majority of included studies had low risk of bias for reference standard and flow and timing. Airway US parameters having moderate-good correlation with moderate-severe OSA were distance between lingual arteries (DLAs > 30 mm; sensitivity, 0.67; specificity, 0.59; 1 study/66 patients); mean resting tongue thickness (>60 mm; sensitivity, 0.85; specificity, 0.59; 1 study/66 patients); tongue base thickness during Muller maneuver (MM; sensitivity, 0.59; specificity, 0.78; 1 study/66 patients); and a combination of neck circumference and retropalatal (RP) diameter shortening during MM (sensitivity, 1.0; specificity, 0.65; 1 study/104 patients). Nonairway US parameters having a low-moderate correlation with moderate-severe OSA were carotid intimal thickness (pooled correlation coefficient, 0.444; 95% confidence interval [CI], 0.320-0.553; P value = .000, 8 studies/727 patients) and plaque presence (sensitivity, 0.24-0.75; specificity, 0.13-1.0; 4 studies/1183 patients). We found that a number of airway and nonairway parameters were identified with moderate to good correlation with OSA diagnosis in the general population. In future studies, it remains to be seen whether PoCUS screening for a combination of these parameters can address the pitfalls of OSA screening questionnaires.

Single-use suvorexant for treating insomnia during overnight polysomnography in patients with suspected obstructive sleep apnea: a single-center experience.

PurposeAlthough patients with suspected obstructive sleep apnea (OSA) might suffer difficulty in falling asleep during overnight polysomnography (PSG), standard hypnotics to obtain sleep during PSG have not been established. The aim of this study was to investigate the safety and efficacy of a new hypnotic agent, suvorexant, a dual orexin receptor antagonist, for insomnia in suspected OSA patients during in-laboratory PSG.Patients and methodsAn observational study was conducted during PSG for 149 patients with suspected OSA who had no insomnia at home. Patients with difficulty in falling asleep during PSG were optionally permitted to take single-use suvorexant. Patients with residual severe insomnia (>1 hour) after taking suvorexant were permitted to take an add-on use zolpidem. Clinical data and sleep questionnaire results were analyzed between a no insomnia group (without hypnotics) and an insomnia group (treated with suvorexant).ResultsAmong 84 patients who experienced insomnia during PSG and required hypnotics (the insomnia group; treated with suvorexant), 44 (52.4%) achieved sufficient subjective sleep with single-use of suvorexant, while the other 40 (47.6%) required suvorexant plus zolpidem. An apnea hypopnea index (AHI) of ≥5 was observed in 144 out of 149 patients with predominantly obstructive respiratory events. Among those patients, 70.8% in the no insomnia group and 63.1% in the insomnia group had severe OSA. Regarding both subjective sleep time and morning mood, significant differences between the no insomnia group and the insomnia group were not observed. No patient taking suvorexant had an adverse event, such as delirium or falling.ConclusionSingle-use suvorexant seems to be a safe and effective (but mild) hypnotic agent for suspected OSA patients with insomnia during in-laboratory PSG.

Accurate Deep Learning-Based Sleep Staging in a Clinical Population With Suspected Obstructive Sleep Apnea.

The identification of sleep stages is essential in the diagnostics of sleep disorders, among which obstructive sleep apnea (OSA) is one of the most prevalent. However, manual scoring of sleep stages is time-consuming, subjective, and costly. To overcome this shortcoming, we aimed to develop an accurate deep learning approach for automatic classification of sleep stages and to study the effect of OSA severity on the classification accuracy. Overnight polysomnographic recordings from a public dataset of healthy individuals (Sleep-EDF, n = 153) and from a clinical dataset (n = 891) of patients with suspected OSA were used to develop a combined convolutional and long short-term memory neural network. On the public dataset, the model achieved sleep staging accuracy of 83.7% (κ = 0.77) with a single frontal EEG channel and 83.9% (κ = 0.78) when supplemented with EOG. For the clinical dataset, the model achieved accuracies of 82.9% (κ = 0.77) and 83.8% (κ = 0.78) with a single EEG channel and two channels (EEG+EOG), respectively. The sleep staging accuracy decreased with increasing OSA severity. The single-channel accuracy ranged from 84.5% (κ = 0.79) for individuals without OSA diagnosis to 76.5% (κ = 0.68) for patients with severe OSA. In conclusion, deep learning enables automatic sleep staging for suspected OSA patients with high accuracy and expectedly, the accuracy decreased with increasing OSA severity. Furthermore, the accuracies achieved in the public dataset were superior to previously published state-of-the-art methods. Adding an EOG channel did not significantly increase the accuracy. The automatic, single-channel-based sleep staging could enable easy, accurate, and cost-efficient integration of EEG recording into diagnostic ambulatory recordings.

Validation of a photoplethysmography device for detection of obstructive sleep apnea in the perioperative setting.

Obstructive sleep apnea (OSA) is a risk factor for perioperative complications, but many OSA patients present undiagnosed. While polysomnography (PSG) is the "gold standard" for diagnosis, its application is technology-intense, time-consuming, expensive, and requires specialists, often delaying surgery. Thus, miniaturized devices were developed for OSA screening aimed at ruling out major OSA while measuring a lesser number of biological signals. We evaluated the accuracy of a photoplethysmography (PPG)-based device for OSA detection. 48 patients with established or strongly suspected (STOP-Questionnaire) OSA scheduled for surgery underwent in their preoperative nights parallel recordings by PPG and a classic polygraphy (PG) devices (SomnoLab2®). We compared the diagnostic accuracy of the PPG in diagnosing mild [Apnea-/Hypopnea-Index (AHI) 5-14 events/h] and moderate-to-severe OSA (AHI > 15). PPG and PG-derived AHI correlated significantly (r = 0.85, p < 0.0001) and high area under curve (AUC) in receiver operator characteristics (ROC) values were seen for both AHI thresholds (0.93 and 0.95, respectively). For an AHI > 5, sensitivity was 100%, specificity 44%, positive predictive value (PPV) 62%, negative predictive value (NPV) 100%, likelihood ratio (LHR) 1.79, and Cohen κ was 0.43. For an AHI > 15, sensitivity was 92%, specificity 77%, PPV 60%, NPV 96%, LHR 4.04, and Cohen κ was 0.59. In a typical perioperative cohort of confirmed and suspected OSA patients, PPG reliably detected OSA patients while showing some false-positive results. Such devices are helpful for preoperative OSA screening.

F25. Intranight variability of AHI can affect the efficiency of CPAP treatment

Introduction Obstructive sleep apnea (OSA) is a common disease with severe health consequences most commonly treated with continuous positive airway pressure (CPAP) device. However, the adherence to CPAP treatment is often limited and the usage of the CPAP device can be only around 4 h per night after 1 month usage ( Chai-Coetzer et al., 2013 ). Possibly for this reason the benefits of the CPAP usage in terms of cardiovascular outcomes are not always obvious ( McEvoy et al., 2016 ). The severity of OSA is estimated with apnea-hypopnea-index (AHI) together with daytime symptoms. AHI may vary hour by hour during the night. In the current study, the aim was to investigate whether there is a difference in AHI during the first 4 h of sleep (possible CPAP adherence) and during the worst 4 h during the night. Methods 2002 ambulatory polygraphic recordings of suspected OSA patients were evaluated. The patients were divided into normal, mild, moderate and severe OSA categories based on their total AHI. Total AHI, AHI during the first 4 h and AHI during the worst 4 h during the recording were analyzed. AHI during the first and the worst 4 h were then compared. Wilcoxon signed ranks test was used to estimate the statistical significance of the differences. p Results There were 972, 508, 260 and 262 patients in normal, mild, moderate and severe OSA categories, respectively. We found a trend of increasing AHI towards the end of the night. The median total AHI in these categories were 1.5, 8.7, 20.7 and 47.6 events/h, respectively. The median differences between the AHI during the worst 4 h and the first 4 h of the recording were 0.8, 4.8, 10.4 and 9.8 events/h ( p Conclusion There were statistically and clinically significant differences between the median AHI values of the worst 4 h and the first 4 h of the night in all OSA severity categories. CPAP adherence has been reported to be around 4 h per night ( Chai-Coetzer et al., 2013 ) and the CPAP usage is probably typically focused on the first hours from the beginning of the night. For these reasons the benefits of the CPAP usage are probably not as linear as the simple time of adherence indicates. With limited adherence time, CPAP treatment is not always able to prevent severe cardiovascular outcomes ( McEvoy et al., 2016 ). If the CPAP usage could be directed to the worst hours of the night at the same adherence level it might provide better treatment results. The total AHI would decrease more when CPAP would be used during the worst hours instead the first hours of the night.

Abstract WP153: Severe Obstructive Sleep Apnea is Associated With Presence of Intracranial Cerebral Atherosclerosis

Background and significance: Intracranial cerebral atherosclerosis (ICAS) is closely associated with risk of cerebrovascular diseases, especially in Asian populations. Obstructive sleep apnea (OSA) is associated with systemic atherosclerosis, but it is not clear whether OSA is an independent risk factor of ICAS. We aimed to investigate the association between ICAS and apnea-hypopnea index (AHI), representing severity of OSA, in suspected OSA patients. Methods: We included 142 patients who suspected OSA from Ewha Sleep Center who underwent brain MR angiography (MRA) and polysomnography (PSG). We also investigated the presence and burden of ICAS on MRA and AHI on PSG. Results: The mean patient age was 59.7 ± 13.1 years, and 54.2% (77/142) were male. The mean AHI was 19.8 ± 20.9, and 17 patients (12.0%) had ICAS. Higher AHI was noted in patients with ICAS compared to those without ICAS (38.2 ± 27.1 vs. 17.3 ± 18.7, p = 0.023). The burden of ICAS was positively correlated with severity of OSA (p for trend = 0.013)(Figure 1). In multivariable binary logistic analyses, after adjusting for age, sex, hypertension, hyperlipidemia, smoking, arousal index and minimum SaO 2 , severe OSA was independently related with presence of ICAS (odds ratio (OR): 14.05, 95% confidence interval (CI): 1.28 - 153.64, p = 0.030). Likewise, in multivariable ordinal logistic regression analyses, severe OSA was marginally associated with burden of ICAS (OR: 8.47, 95% CI: 0.74 - 95.77, p = 0.084). Conclusion: Our findings suggest that severe OSA is associated with presence of ICAS in patients with suspected OSA.

The quality of life of suspected obstructive sleep apnea patients is related to their subjective sleep quality rather than the apnea-hypopnea index.

The relationship between the severity of the apnea-hypopnea index (AHI) and the quality of life (QOL) in patients with obstructive sleep apnea (OSA) has been inconsistent in previous studies. This study aimed to identify the core factor associated with the QOL of suspected OSA patients and to compare the QOL of subjects with OSA and simple snoring (SS). Two hundred eighty-five subjects who were clinically suspected to have OSA underwent nocturnal polysomnography (PSG) and completed self-report questionnaires including the World Health Organization Quality of Life Short Form (WHOQOL-BREF) and the Pittsburgh Sleep Quality Index (PSQI). The effects of the clinical and PSG variables on the QOL score were analyzed using multiple stepwise regression analyses, and the QOL of OSA and SS groups was compared. In correlation analyses, the most significant factor that correlated with the QOL of the subjects was the PSQI total score (p<0.001), while the AHI was not related to the WHOQOL-BREF total score. In multiple linear regression analysis, the PSQI total score was the most significant factor associated with the QOL of participants (p<0.001). The mean score of the WHOQOL-BREF did not differ significantly between the OSA group and the SS group. This study suggests that the main factor affecting the QOL of suspected OSA subjects is their subjective sleep quality. We therefore conclude that patients with OSA symptoms estimate their QOL based on their subjective sleep perception rather than AHI.

Obstructive sleep apnea: an experience

Background: Obstructive sleep apnea (OSA) is a common disorder of repetitive pharyngeal collapse during sleep. It is more common among middle-aged adults. Obesity leads to and intensifies OSA. Epidemiologic studies have recorded relations of OSA with hypertension. The Berlin Questionnaire may find persons at high possibility for OSA and hence can evade costly polysomnography (PSG) studies, especially in resource-limited settings. This study is about our experience of Berlin Questionnaire and clinical characteristics of patients with OSA. Objective: To reveal our experience of OSA in terms of (i) age/sex distribution; (ii) Berlin Questionnaire utility; (iii) clinical features; (iv) polysomnograhic findings; and (v) association with obesity and hypertension. Materials and Methods: This prospective observational study was done in the Department of Chest Medicine and Department of ENT, Head and Neck Surgery of Government Medical College, Srinagar, Jammu and Kashmir. Outpatient department/inpatient department patients who showed positive scoring on Berlin Questionnaire were enrolled in the study. PSG was done in all of these patients. Clinical features, blood pressure, and body mass index (BMI) were noted in patients who showed positive PSG. Result: This study included a total of 120 Berlin Questionnaire positive patients, of which 96 were positive on PSG. Positive predictability value of Berlin Questionnaire was 80% for both low- and high-risk cases. Majority of PSG positive cases were female subjects (68.75%) while males comprised 31.25% of PSG positive cases. Most common age group was 51–65 years. Of PSG positive OSA patients, 41 (42.7%) showed mild disease, 30 (31.2%) moderate disease, and 25 (26%) severe disease. Most patients were grouped as per BMI into obese class II, and majorities were subjects with hypertension. In addition to snoring, other clinical features were dry mouth, excessive daytime sleepiness, and irritability. Conclusion: Berlin Questionnaire is an important screening tool to detect suspected OSA patients. Although male subjects are more commonly seen to be affected in literature, we found female predominance. Most of these patients are middle-aged. Obesity is an important risk factor, and most of these patients show BMI > 30 kg/m2. Most of these patients present hypertension as a comorbidity.

Neck circumference and body mass index as independent predictors of hypertension misclassification in patients suspected of having obstructive sleep apnea.

Twenty-four-hour ambulatory blood pressure monitoring (ABPM) seems to be the most accurate way of diagnosing hypertension in patients with obstructive sleep apnea (OSA). However, this diagnostic tool is expensive and time-consuming and is therefore not used routinely. We aimed to find baseline predictors that enable the identification of patients who misclassify themselves as nonhypertensive to optimize the use of ABPM. Clinically suspected OSA patients (n=369) were enrolled and underwent overnight polysomnography and 24-h ABPM, and completed a data collection form. Anthropometric measurements were assessed. Generalized additive models, the minimum P-value approach, and logistic regression models were used for data analysis. Results were considered significant when α is equal to 0.05. One hundred and twenty-two patients who were not on antihypertensive medication did not report hypertension, but according to ABPM data, 43.4% (n=53) of them had misclassified themselves as nonhypertensive. These patients had a significantly higher apnea-hypopnea index (P<0.001), ABPM variables (P<0.001), BMI (P=0.002), and neck circumference (NC) (P=0.002) than nonhypertensive patients (n=69). BMI and NC emerged as independent predictors of hypertension misclassification. The cut-off points that best discriminated the two groups of patients were 27 kg/m and 39 cm for BMI and NC, respectively. The resulting binary BMI and NC remained independent predictors of hypertension misclassification in the final model (odds ratio: 3.2, P=0.010; odds ratio: 2.4, P=0.038). Our findings emphasize the importance of ABPM for the diagnosis of hypertension in patients suspected of having OSA with a BMI and NC above 27 kg/m and 39 cm, respectively.

The Prioritization of Clinical Risk Factors of Obstructive Sleep Apnea Severity Using Fuzzy Analytic Hierarchy Process.

Recently, there has been a problem of shortage of sleep laboratories that can accommodate the patients in a timely manner. Delayed diagnosis and treatment may lead to worse outcomes particularly in patients with severe obstructive sleep apnea (OSA). For this reason, the prioritization in polysomnography (PSG) queueing should be endorsed based on disease severity. To date, there have been conflicting data whether clinical information can predict OSA severity. The 1,042 suspected OSA patients underwent diagnostic PSG study at Siriraj Sleep Center during 2010-2011. A total of 113 variables were obtained from sleep questionnaires and anthropometric measurements. The 19 groups of clinical risk factors consisting of 42 variables were categorized into each OSA severity. This study aimed to array these factors by employing Fuzzy Analytic Hierarchy Process approach based on normalized weight vector. The results revealed that the first rank of clinical risk factors in Severe, Moderate, Mild, and No OSA was nighttime symptoms. The overall sensitivity/specificity of the approach to these groups was 92.32%/91.76%, 89.52%/88.18%, 91.08%/84.58%, and 96.49%/81.23%, respectively. We propose that the urgent PSG appointment should include clinical risk factors of Severe OSA group. In addition, the screening for Mild from No OSA patients in sleep center setting using symptoms during sleep is also recommended (sensitivity = 87.12% and specificity = 72.22%).

Effectiveness of home single-channel nasal pressure for sleep apnea diagnosis.

Home single-channel nasal pressure (HNP) may be an alternative to polysomnography (PSG) for obstructive sleep apnea (OSA) diagnosis, but no cost studies have yet been carried out. Automatic scoring is simpler but generally less effective than manual scoring. To determine the diagnostic efficacy and cost of both scorings (automatic and manual) compared with PSG, taking as a polysomnographic OSA diagnosis several apnea-hypopnea index (AHI) cutoff points. We included suspected OSA patients in a multicenter study. They were randomized to home and hospital protocols. We constructed receiver operating characteristic (ROC) curves for both scorings. Diagnostic efficacy was explored for several HNP AHI cutoff points, and costs were calculated for equally effective alternatives. Of 787 randomized patients, 752 underwent HNP. Manual scoring produced better ROC curves than automatic for AHI < 15; similar curves were obtained for AHI ≥ 15. A valid HNP with manual scoring would determine the presence of OSA (or otherwise) in 90% of patients with a polysomnographic AHI ≥ 5 cutoff point, in 74% of patients with a polysomnographic AHI ≥ 10 cutoff point, and in 61% of patients with a polysomnographic AHI ≥ 15 cutoff point. In the same way, a valid HNP with automatic scoring would determine the presence of OSA (or otherwise) in 73% of patients with a polysomnographic AHI ≥ 5 cutoff point, in 64% of patients with a polysomnographic AHI ≥ 10 cutoff point, and in 57% of patients with a polysomnographic AHI ≥ 15 cutoff point. The costs of either HNP approaches were 40% to 70% lower than those of PSG at the same level of diagnostic efficacy. Manual HNP had the lowest cost for low polysomnographic AHI levels (≥ 5 and ≥ 10), and manual and automatic scorings had similar costs for higher polysomnographic cutoff points (AHI ≥ 15) of diagnosis. Home single-channel nasal pressure (HNP) is a cheaper alternative than polysomnography for obstructive sleep apnea diagnosis. HNP with manual scoring seems to have better diagnostic accuracy and a lower cost than automatic scoring for patients with low apnea-hypopnea index (AHI) levels, although automatic scoring has similar diagnostic accuracy and cost as manual scoring for intermediate and high AHI levels. Therefore, automatic scoring can be appropriately used, although diagnostic efficacy could improve if we carried out manual scoring on patients with AHI < 15. Clinicaltrials.gov identifier: NCT01347398.