Screening Tool For Obstructive Sleep Apnea Research Articles

Evaluation of an OSA Risk Screening Smartphone App in a General, Non-Symptomatic Population Sample (ESOSA).

Background: Obstructive Sleep apnea (OSA) is a prevalent sleep disorder, risk factor for cardiovascular disease and imposes a substantial global socioeconomic and health burden. OSA is insufficiently diagnosed as it often presents with unspecific or no symptoms. This study compares the effectiveness of a smartphone-based screening method to polysomnography (PSG) in a general, non-symptomatic population sample. Methods: Adult subjects were recruited from the general population. Subjects reporting OSA-related symptoms suggesting an increased OSA risk were excluded. Included subjects underwent Type-II PSG and a parallel breathing sound analysis using the Snorefox M smartphone app. The PSG scores were compared with the results of the Snorefox M app for its ability to detect moderate to severe OSA (AHI ≥ 15). Results: 150 subjects were included. All subjects completed the diagnostic night, no adverse events occurred. A valid analysis result was obtained for 142 subjects. A total of 24% of subjects had moderate to severe OSA based on the PSG results. The Snorefox M software app showed a sensitivity of 0.91 (0.76, 0.98), specificity of 0.83, PPV of 0.63 (0.48, 0.77), and NPV of 0.97 (0.91, 0.99) to detect AHI ≥ 15 compared with the reference PSG (95% CI). Conclusions: This study compares for the first time, the performance of an app-based OSA screening tool with PSG in a non-symptomatic population sample. Easily accessible screening tools can play a role in complementing existing diagnostic possibilities, helping to increase the diagnosis rate, with a positive effect on cardiovascular health in a relevant population share.

Identifying the optimal STOP-Bang screening score for obstructive sleep apnea among bariatric surgery patients

BackgroundUndiagnosed obstructive sleep apnea (OSA) increases the risk of perioperative complications in bariatric patients. Validated screening methods exist, but are not specific to patients with severe obesity. ObjectivesDetermine the ideal OSA screening tool for bariatric surgery patients balancing accuracy and cost-effectiveness. SettingUniversity Hospital. MethodsBariatric surgery patients from January 2018 to September 2023 were identified from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database. For patients with a STOP-Bang score of ≥4 referred for polysomnogram additional variables were collected from the electronic medical record. The Berlin Score was retrospectively calculated. ResultsOut of 484 patients who underwent bariatric surgery, 167 (34.5%) had a STOP-Bang score ≥4. The receiver operating characteristic (ROC) curve for STOP-Bang scores ≥4 had an area under the curve (AUC) of 78.5% for predicting OSA and 83.7% for OSA requiring treatment (Apnea Hypopnea Index [AHI] ≥ 15), compared to Berlin Scores’ AUC of 80.7% and 88.6%, respectively. A STOP-Bang score of 4 had a sensitivity of 55.6% and specificity of 36.8%, while a score of 5 had 29.3% and 66.2%, respectively. A Berlin Score of 3 had a sensitivity of 47.5% and specificity of 69.1%, with 30 patients (44.1%) starting OSA treatment. Thirty-five patients (21%) experienced a delay in insurance submission, averaging 41.5 days, related to OSA workup. ConclusionThe Berlin questionnaire outperforms STOP-Bang in predicting OSA requiring treatment. Raising the polysomnography referral score from STOP-Bang ≥4 to ≥5 or utilizing a Berlin Score of ≥3, may alleviate resource burden, reduce costs, and expedite medical optimization for bariatric surgery.

Clinical characteristics of non-sleepy obstructive sleep apnea patients: a study in a tertiary care sleep clinic in India.

Obstructive sleep apnea (OSA) encompasses a diverse population, manifesting with or without symptoms of excessive daytime sleepiness. There is contention surrounding the significance of non-sleepy OSA within clinical contexts and whether routine treatment is warranted. This study aims to evaluate epidemiological and clinical distinctions between sleepy and non-sleepy OSA patients. A retrospective analysis was conducted on consecutive patients undergoing polysomnography for OSA assessment at tertiary care hospitals between 2018 and 2023. For 176 of 250 patients, complete polysomnography records with OSA diagnoses were available. Non-sleepy OSA was defined when a patient had an Epworth sleepiness scale score <10 and polysomnography demonstrated an apnea hypopnea index ≥5/hour. Non-sleepy OSA patients were matched with sleepy OSA patients in terms of age and gender distribution (mean age 51.24±13.25 years versus 50.9±10.87 years, male 70.4% versus 73.3%). The sensitivity of STOP-BANG≥3 for the non-sleepy OSA group was 87.7%, 89.3%, and 95.2% for any OSA severity, moderate to severe OSA, and severe OSA, respectively, while the corresponding sensitivity for the sleepy OSA group was 96.5%, 98.6%, and 100% for any OSA severity, moderate to severe OSA, and severe OSA, respectively. A novel symptom scoring tool, HASSUN (hypertension, nocturnal apneas, snoring, sleep disturbance, unrefreshing sleep, and nocturia), demonstrated a sensitivity of over 90% for all severity categories of OSA in both non-sleepy and sleepy OSA groups. The prevalence of cardiovascular and metabolic comorbidities did not significantly differ between non-sleepy and sleepy OSA patients. The physiological parameters, including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1/FVC ratio, arterial partial pressure of oxygen, and bicarbonate at baseline, were comparable between the two groups. To conclude, non-sleepy OSA patients are less obese, exhibit fewer symptoms, and have less severe OSA in comparison to sleepy OSA. Non-sleepy OSA patients display a similar likelihood of cardiovascular and metabolic comorbidities compared to sleepy OSA patients. Further investigations are warranted to elucidate the mechanisms underlying cardiovascular metabolic comorbidities in non-sleepy OSA patients. The proposed HASSUN scoring tool for non-sleepy OSA screening necessitates validation in future studies.

Nocturnal Urinary Symptoms as Screening Tools for Obstructive Sleep Apnea.

Nocturnal lower urinary tract symptoms are part of obstructive sleep apnea (OSA), and urogynecology clinics may serve as OSA screening sites. This study's aim was to determine the accuracy of nocturia and nocturnal enuresis (NE) as screening tools for OSA in new patients at a urogynecology clinic. Using a retrospective study design, we gathered information regarding diagnostic OSA testing, continuous positive airflow pressure use, and lower urinary tract symptoms improvement from women in a urogynecology clinic who were previously screened for OSA using validated questionnaires. Nocturia and NE were tested for sensitivity and specificity using positive OSA diagnosis by polysomnography as the gold standard. Nocturia with a cutoff of ≥2 episodes per night had the best test characteristics-86.4% sensitivity (95% confidence interval [CI], 65.1-97.1) and 58.5% specificity (95% CI, 44.1-71.9) for an overall accuracy of 78.4% (95% CI, 67.0-89.8). Nocturnal enuresis with a cutoff of ≥1 episode per week had the best NE characteristics with 31.8% sensitivity (95% CI, 13.9-54.9) and 79.3% specificity (95% CI, 65.9-89.2) for an overall accuracy of 56.1% (95% CI, 41.2-71). Lower urinary tract symptoms such as nocturia and NE are routinely assessed in urogynecology clinics, making them useful for OSA screening and referral. The present study found nocturia symptoms with ≥2 episodes per night to retain acceptable test characteristics in screening for OSA, whereas NE was found to have less acceptable test characteristics for OSA screening. Urogynecology clinics may utilize nocturia symptoms in clinical decision making for OSA referral.

A Machine Learning Prediction Model of Adult Obstructive Sleep Apnea Based on Systematically Evaluated Common Clinical Biochemical Indicators.

Obstructive sleep apnea (OSA) is a common and potentially fatal sleep disorder. The purpose of this study was to construct an objective and easy-to-promote model based on common clinical biochemical indicators and demographic data for OSA screening. The study collected the clinical data of patients who were referred to the Sleep Medicine Center of the Second Affiliated Hospital of Fujian Medical University from December 1, 2020, to July 31, 2023, including data for demographics, polysomnography (PSG), and 30 biochemical indicators. Univariate and multivariate analyses were performed to compare the differences between groups, and the Boruta method was used to analyze the importance of the predictors. We selected and compared 10 predictors using 4 machine learning algorithms which were "Gaussian Naive Bayes (GNB)", "Support Vector Machine (SVM)", "K Neighbors Classifier (KNN)", and "Logistic Regression (LR)". Finally, the optimal algorithm was selected to construct the final prediction model. Among all the predictors of OSA, body mass index (BMI) showed the best predictive efficacy with an area under the receiver operating characteristic curve (AUC) = 0.699; among the predictors of biochemical indicators, triglyceride-glucose (TyG) index represented the best predictive performance (AUC = 0.656). The LR algorithm outperformed the 4 established machine learning (ML) algorithms, with an AUC (F1 score) of 0.794 (0.841), 0.777 (0.827), and 0.732 (0.788) in the training, validation, and testing cohorts, respectively. We have constructed an efficient OSA screening tool. The introduction of biochemical indicators in ML-based prediction models can provide a reference for clinicians in determining whether patients with suspected OSA need PSG.

Classification of Childhood Obstructive Sleep Apnea based on X-ray images analysis by Quasi-conformal Geometry

Craniofacial profile is one of the anatomical causes of obstructive sleep apnea (OSA). By medical research, cephalometry provides information on patients’ skeletal structures and soft tissues. In this work, a novel approach to cephalometric analysis using quasi-conformal geometry based local deformation information was proposed for OSA classification. Our study was a retrospective analysis based on 60 case-control pairs with accessible lateral cephalometry and polysomnography (PSG) data (mean age: 8.9 ± 2.3 years). By using the quasi-conformal geometry to study the local deformation around 15 landmark points, and combining the results with three linear distances between landmark points, a total of 1218 information features were obtained per subject. A L2 norm based classification model was built. Under experiments, our proposed model achieves high testing accuracy. The accurate classification tool provides us with a reliable and accurate screening tool for childhood OSA.

Correlation of morning dry mouth with clinical features of OSA in a community population: a cross-sectional study

ABSTRACT Objectives Morning dry mouth, commonly seen in Obstructive Sleep Apnea (OSA) patients, is absent in current OSA screening tools. This study evaluated the link between morning dry mouth and OSA’s clinical symptoms and complications, aiming to determine its viability as a screening indicator. Methods This research analyses baseline data from a prospective cohort study (the PIFCOPD study). Demographic information, medical history, and the presence of morning dry mouth symptoms were collected. The STOP-Bang questionnaire was performed for OSA screening. Logistic regression analyses were employed to establish the correlations between morning dry mouth and the clinical symptoms and comorbidities of OSA. Result 1291 participants (62.1±7.5 years; 501 males, 790 females) were included, of which 416 reported morning dry mouth (32.2%). 42.6% in the high-risk OSA group and 22.1% in the low-risk group reported morning dry mouth. Individuals with morning dry mouth also showed higher STOP-Bang scores (3.3±1.6 vs. 2.3±1.4, P<0.01). Significant associations were found between morning dry mouth and loud snoring, observed sleep apnea, daytime fatigue, and hyperlipidemia (P<0.01), but not with alcohol consumption, tea consumption, diabetes, or hypertension. Conclusion Morning dry mouth is associated with increased OSA risk and its clinical signs, suggesting its potential as an OSA screening symptom. Clinical trial registration This study has been registered at www.ClinicalTrials.gov (registration identifier: NCT03532893) on 21 May 2018.

Efeitos tardios do uso de cafeína no sono de crianças nascidas prematuras

ABSTRACT Objective: This study aimed to evaluate whether the therapeutic use of caffeine for premature newborns is associated with changes in sleep habits and the presence of obstructive sleep apnea in childhood. Methods: This is a cross-sectional single-center study in which the caretakers of 87 children aged 5–10 years, born full-term or preterm, treated or not with caffeine in the neonatal period, answered questionnaires to screen for obstructive sleep apnea (Pediatric Obstructive Sleep Apnea Screening Tool [PosaST]) and to characterize the sleep habits (Children's Sleep Habits Questionnaire [CSHQ]) of their children. ANOVA and linear regression tests were performed to verify possible differences between the groups. Results: Children born prematurely who were treated with caffeine woke up significantly later on weekdays than those born at term (09h±00h58 and 07h43±1h15, respectively, p=0.022) and had longer total daily sleep time also compared to those born at term (10h24±1h08 and 09h29±1h08, respectively, p&lt;0.001). There was no significant difference between the three groups in overall PosaST and CSHQ scores. Conclusions: Caffeine use in the neonatal period did not impair sleep habits later in life and did not lead to increased obstructive sleep apnea scores in prematurely born children compared to those born at term.

Sleep habits and orofacial myofunctional self-assessment of children at risk for sleep breathing disorders.

To identify orofacial myofunctional complaints and sleep-disordered breathing and correlate them with sleep habits in childhood. The study included 71 parents/guardians of public school children aged 6 to 11 years. They answered a form with semi-structured medical history questions and the Nordic Orofacial Test-Screening - interview, the Pediatric Obstructive Sleep Apnea Screening Tool Questionnaire, and the Children's Sleep Habits Questionnaire - all of them in their Portuguese/Brazilian versions in an online format. Statistical analyses used Spearman's correlation, setting the significance level at 5%. There were 29 female children (40.8%) and 42 male ones (59.2%), with a mean age of 8.52 years. The study found orofacial myofunctional complaints related to breathing functions (35.2%), chewing and swallowing (32.4%), and deleterious habits (33.8%). All children were at a low risk of sleep-disordered breathing. As for sleep habits, 23 children (32.39%) had a lower total score, whereas 48 children (67.61%) exceeded 41 points. There was a correlation between the risk of sleep-disordered breathing in children with complaints of orofacial myofunctional disorders and poor sleep quality/habits.

Apnea‐Hypopnea Index Prediction for Obstructive Sleep Apnea Using Unsegmented SpO2 Signals and Deep Learning

This paper presents an apnea‐hypopnea index (AHI) prediction model for obstructive sleep apnea (OSA) by using unsegmented peripheral oxygen saturation (SpO2) signals. This proposal, directly predicting AHI values with respect to overnight unsegmented SpO2 signals, is the first report in the literature, and simply solves the method limitation of our previous study. As well, this approach can provide more features of OSA assessment to users and doctors. Experimental results show that the presented model gives an overall accuracy up to 81.13% for four‐level OSA severity classification, which is higher than our original work and significantly outperforms most counterparts in the literature. This work can be used as an easy‐to‐use and effective screening tool for OSA before undergoing polysomnography (PSG). Moreover, doctors can arrange timely PSG tests for those who require preferential medical care according to the predicted OSA severity. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Anthropometric screening approach for obstructive sleep apnea in Japanese men: development and validation of the ABC scale

BackgroundThe existing screening tools for the detection of moderate and severe obstructive sleep apnea (OSA) are tailored to Western individuals. The aim of this study was to formulate and validate a simple anthropometric tool for OSA screening in a Japanese male population by incorporating objective indicators obtained during routine medical checkups.MethodsIn total, 443 Japanese men, who were suspected of having OSA and visited our sleep disorder clinic from 2009 to 2012, were retrospectively divided into two groups (development group [DG], n = 206; validation group [VG], n = 237). In the DG, OSA was defined as an apnea–hypopnea index of ≥ 15 events/h. Data regarding clinical and anthropometric variables (age, body mass index [BMI], neck circumference [NC], waist circumference [WC]) were obtained. For parameters that were associated with OSA on simple logistic regression analysis, cutoff values were calculated with receiver operating characteristic curves to create a new screening tool. The utility of the tool was evaluated in the VG and compared to that of the modified Berlin questionnaire (mBQ) for OSA.ResultsAge (odds ratio [OR] = 1.033, p = 0.002), BMI (OR = 1.231, p < 0.001), NC (OR = 1.327, p < 0.001), and WC (OR = 1.083, p < 0.001) were significant risk factors for OSA in the DG. Cutoff values for the prediction of OSA were age: ≥ 46.5 years, BMI: ≥ 25.45 kg/m2, NC: ≥ 38.35 cm, and WC: ≥ 90.75 cm. Our screening tool, incorporating age, BMI, and WC, yielded 70.1% sensitivity (mBQ: 85.4%) and 66.0% specificity (mBQ: 35.0%) in the VG.ConclusionsOSA screening in Japanese men has been conducted only in limited settings such as sleep clinics. The study findings support the implementation of screening in medical checkups using objective indices to enable early detection and treatment of OSA.

Modified STOP-bang questionnaire incorporating morning dry mouth and BMI adjustment in China: a retrospective study of 590 patients

ABSTRACT Background Morning dry mouth (MDM) is a common symptom of Obstructive Sleep Apnea (OSA) yet current OSA screening tools overlook it. Objective To enhance the specificity of the Stop-Bang questionnaire (SBQ) by adding an MDM symptom. Method A retrospective analysis on 590 patients from Peking University First Hospital (2013–2018) suspected of OSA was conducted. They underwent polysomnography. The research incorporated the MDM symptom into SBQ and adjusted the body mass index (BMI) threshold to 28 kg/m2. Predictive parameters were then calculated. Results 83.1% patients were diagnosed with OSA, with 61.4% reporting MDM. Multivariate regression confirmed MDM significantly influenced Apnea-Hypopnea Index (AHI). Adjusted SBQ with MDM showed a slight decrease in sensitivity but improved specificity, especially when using a BMI threshold of > 28 kg/m2. For AHI ≥ 5 events/h and AHI ≥ 15 events/h, adjusted SBQ with MDM (BMI >28 kg/m2) obtained the highest Youden index. Conclusion Incorporating the MDM symptom into SBQ and adjusting the BMI threshold enhances the diagnostic specificity for OSA.

Improving the screening process for obstructive sleep apnea in the primary care setting.

There is a high prevalence of obstructive sleep apnea (OSA) in the primary care setting that is underdiagnosed and underreported in 75-80% of the population. If untreated, OSA has implications for long-term cardiovascular, cerebrovascular, and metabolic health. At a primary care clinic in New Jersey, patients at high risk for OSA were not being routinely screened for the condition. This project intended to address the administration of the STOP-Bang Questionnaire among asymptomatic high-risk patient populations with hypertension and/or obesity. In addition to determining each participant's level of risk for OSA, and in turn, facilitating referrals and diagnostic testing per a provider's discretion. The STOP-Bang Questionnaire, a validated screening tool for OSA, was implemented in a primary care practice to measure levels of risk for OSA among eligible participants. A total of 32 out of the 100 patients assessed were identified as high risk for OSA. After screening, 36 participants were referred for confirmatory testing. The STOP-Bang Questionnaire, a validated screening tool for OSA, is recommended for all asymptomatic high-risk patients, specifically for those with obesity and/or hypertension, at least annually. The use of a screening tool evaluates a level of risk, promotes detection of disease in the primary stages, delays disease progression, and improves treatment initiatives.

Comorbid association of obstructive sleep apnea (OSA) and thrombotic primary antiphospholipid syndrome (tPAPS): A more severe phenotype?

ObjectiveWe aimed to evaluate the frequency of obstructive sleep apnea (OSA) in patients with thrombotic primary antiphospholipid syndrome (tPAPS), to investigate the performance of screening tools for OSA in this scenario and to compare clinical/laboratorial differences in tPAPS patients with and without OSA. MethodsWe consecutively enrolled patients with tPAPS to undergo sleep studies using a portable monitor. OSA was defined as apnea-hypopnea index ≥15 events/h. Frequency of OSA in tPAPS was evaluated and compared with age-, gender-, and BMI-matched controls (1:3 ratio) from the Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). Next, we tested the performance of three different screening tools for assessing OSA in patients with tPAPS. Finally, patients with tPAPS were stratified according to OSA status comparing their clinical and laboratory characteristics (including damage burden measured by Damage Index for Antiphospholipid Syndrome [DIAPS] and biomarkers associated with thrombosis) using standard statistical procedures. ResultsFifty-two patients were included for analysis (females: 82.7%; mean age: 48 ± 14 years; body-mass index: 31.1 ± 6.5 Kg/m2; 25% with moderate-severe OSA). When compared to matched controls from ELSA-Brasil (n = 115), there was no significant differences in the frequencies of OSA (tPAPS: 12/42 [28.6%] vs. controls: 35/115 [30.4%], p = 0.821). Among screening tools, NoSAS had the highest area under ROC curve (AUC 0.806, CI 95% 0.672–0.939, p = 0.001), followed by STOP-Bang (AUC 0.772, CI 95% 0.607–0.938, p = 0.004). Patients with comorbid tPAPS and OSA presented higher levels of von Willebrand factor (vWF) (median 38.9 vs. 32.6, p = 0.038) and DIAPS (median 5 vs. 2, p = 0.020), when compared to those without OSA. OSA remained statistically associated with higher DIAPS, even after controlling for age, disease duration and BMI. ConclusionOSA is common in patients with tPAPS, with rates comparable to a non-referred population. Both NoSAS and STOP-Bang scores seems to be useful for screening OSA in these patients. Patients with tPAPS+OSA had higher damage burden and higher levels of vWF, which might suggest a more severe phenotype of tPAPS in this scenario.

Performance Accuracy of Wrist-Worn Oximetry and Its Automated Output Parameters for Screening Obstructive Sleep Apnea in Children

Objectives: Obstructive sleep apnea (OSA) increases the risk of perioperative adverse events in children. While polysomnography (PSG) remains the reference standard for OSA diagnosis, oximetry is a valuable screening tool. The traditional practice is the manual analysis of desaturation clusters derived from a tabletop device using the McGill oximetry score. However, automated analysis of wearable oximetry data can be an alternative. This study investigated the accuracy of wrist-worn oximetry with automated analysis as a preoperative OSA screening tool. Methods: Healthy children scheduled for adenotonsillectomy underwent concurrent overnight PSG and wrist-worn oximetry. PSG determined the obstructive apnea-hypopnea index (OAHI). Oximetry data were auto-analyzed to determine 3% oxygen desaturation index (ODI3) and visually scored as per McGill criteria. The logistic regression model assessed the predictive performance of ODI3 for detecting the presence and severity of OSA after adjusting for covariates. Results: Seventy-six children (34 females), aged (mean±standard deviation) 5.7±1.6 years were classified, based on PSG-derived OAHI, as no OSA (n=31), mild (n=31), and moderate-severe OSA (n=14). Oximetric ODI3 was identified as the sole predictor of moderate-severe OSA (OAHI≥5 events/h) (odds ratio 1.38, 95% confidence interval 1.15, 1.65, &lt;i&gt;p&lt;/i&gt;=0.001). The best diagnostic performance was at ODI3=5 events/h (78.6% sensitivity, 75.8% specificity [receiver operating characteristic-area under the curve {ROC-AUC}=0.857]). ODI3 was also more sensitive than the McGill oximetry score in diagnosing moderate-severe OSA (78.6% by ODI3 vs. 33.0% by McGill). The performance was suboptimal for any level of OSA (OAHI≥1 event/h) (75.6% sensitivity, 61.3% specificity [ROC-AUC=0.709]). Conclusions: Wrist-worn oximetry-derived automated ODI3 can reliably identify moderate-severe OSA in children undergoing adenotonsillectomy, making it a potentially useful preoperative OSA screening tool.

Risk of Obstructive Sleep Apnea in Saudi Male Boys with Duchenne Muscular Dystrophy (DMD).

Duchenne muscular dystrophy (DMD) patients are at a high risk of developing sleep-related breathing disorders (SRBD) such as obstructive sleep apnea (OSA). This study aimed to determine the risk of developing OSA among DMD patients. This cross-sectional study was conducted from February 2022 to July 2022 in a tertiary healthcare facility. As a screening tool for OSA, we used the Pediatric Sleep Questionnaire (PSQ). Subjects included 60 boys with DMD, mean age 10.15 ± 3.54 years. The mean BMI for all subjects was 18.9 ± 4.08 kg/m2. Of these, 22 (36.7%) children were at high risk of OSA. Children who were overweight, and on steroids tended to be at higher risk of developing OSA (P < 0.043) and (P < 0.029) respectively. Our study shows a significant risk of OSA in DMD patients. Therefore, Sleep studies should be part of the standard of care for DMD patients.

Insights into the Use of Point-of-Care Ultrasound for Diagnosing Obstructive Sleep Apnea.

Obstructive sleep apnea (OSA) is a sleeping disorder caused by complete or partial disturbance of breathing during the night. Existing screening methods include questionnaire-based evaluations which are time-consuming, vary in specificity, and are not globally adopted. Point-of-care ultrasound (PoCUS), on the other hand, is a painless, inexpensive, portable, and useful tool that has already been introduced for the evaluation of upper airways by anesthetists. PoCUS could also serve as a potential screening tool for the diagnosis of OSA by measuring different airway parameters, including retropalatal pharynx transverse diameter, tongue base thickness, distance between lingual arteries, lateral parapharyngeal wall thickness, palatine tonsil volume, and some non-airway parameters like carotid intima-media thickness, mesenteric fat thickness, and diaphragm characteristics. This study reviewed previously reported studies to highlight the importance of PoCUS as a potential screening tool for OSA.

Revisiting the Epworth sleepiness scale : Is excessive daytime sleepiness still avalid screening tool for obstructive sleep apnea in apopulation at risk?

Obstructive sleep apnea (OSA) is acommon medical problem with numerous comorbidities and high costs. Since the introduction of the Epworth sleepiness scale (ESS), excessive daytime sleepiness (EDS) has been considered the most common and prominent symptom of OSA. Aim of this study was to re-evaluate the ESS for detection of OSA in apopulation at risk compared to the gold standard overnight polysomnography (PSG). A total of 266patients (mean age 57.9 ± 11.6 years; 189 men and 77women), referred to our sleep laboratory for probable OSA, were given ESS followed by an overnight PSG. The ESS values were compared to PSG apnea hypopnea index (AHI) with sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy (DA) calculated for ESS. The positive cut-off value for ESS was ≥ 10 and for AHI ≥ 5. Only 92(34.6%) subjects had a positive ESS. An OSA was diagnosed by PSG in 213 (80.1%) subjects: 46 having mild, 37 moderate and 130 severe apnea. Most subjects with positive ESS (88.0%) were found to have OSA but most subjects with a negative ESS (75.9%) were also positive for OSA (42% with AHI ≥ 30). The area under the receiver operating characteristic (ROC) curve for ESS was 0.60 (95% confidence interval, CI 0.54-0.66; p = 0.020) with SE 38.0%, SP 79.3%, PPV 88.0%, NPV 24.1% and DA 46.2%. It was found that excessive daytime sleepiness, measured by ESS, is not avaluable screening tool for OSA, especially when the test is negative. Other screening tests that involve additional parameters, beside daytime sleepiness alone, should be considered.

Alternatives to Polysomnography for the Diagnosis of Pediatric Obstructive Sleep Apnea.

Diagnosis of obstructive sleep apnea (OSA) in children with sleep-disordered breathing (SDB) requires hospital-based, overnight level I polysomnography (PSG). Obtaining a level I PSG can be challenging for children and their caregivers due to the costs, barriers to access, and associated discomfort. Less burdensome methods that approximate pediatric PSG data are needed. The goal of this review is to evaluate and discuss alternatives for evaluating pediatric SDB. To date, wearable devices, single-channel recordings, and home-based PSG have not been validated as suitable replacements for PSG. However, they may play a role in risk stratification or as screening tools for pediatric OSA. Further studies are needed to determine if the combined use of these metrics could predict OSA.

Sleep Subdomain of the Sinonasal Outcome Test as a Potential Screening Tool for Sleep Apnea in Chronic Rhinosinusitis.

Approximately 20% of patients with chronic rhinosinusitis (CRS) have comorbid obstructive sleep apnea (OSA). Patients with undiagnosed OSA are at high risk for perioperative complications. The Sinonasal Outcomes Test (SNOT-22) Questionnaire is commonly administered to CRS patients, whereas OSA screening tools are less routinely employed. This study compared SNOT-22 sleep subdomain (Sleep-SNOT) scores among non-OSA CRS versus OSA-CRS patients undergoing ESS, and assessed sensitivity, specificity, and diagnostic accuracy of the Sleep-SNOT for OSA screening. Retrospective review of patients that underwent endoscopic sinus surgery (ESS) for CRS from 2012 to 2021. Patients either carried a reported OSA diagnosis and completed the SNOT-22, or had undocumented OSA status and completed both STOP-BANG and SNOT-22. Demographics, questionnaire scores, and OSA status were collected. A receiver operating characteristic (ROC) curve assessed cutoff scores, sensitivity, and specificity of the Sleep-SNOT for OSA screening. Of 600 patients reviewed, 109 were included. 41% had comorbid OSA. OSA patients had a higher BMI (32.1 ± 7.7 vs. 28.35 ± 6.7 kg/m2 ; p = 0.02), Sleep-SNOT (21.96 ± 12.1 vs. 16.8 ± 11.2; p = 0.021) and STOP-BANG (3.1 ± 1.44 vs. 2.06 ± 1.27; p = 0.038) scores. A Sleep-SNOT score of 17.5 had a sensitivity of 68.9%, specificity of 55.7%, and diagnostic accuracy of 63% for OSA detection (p = 0.022). Sleep-SNOT scores are greater for CRS-OSA patients. The Sleep-SNOT ROC curve demonstrates a high sensitivity, specificity, and accuracy for OSA screening in CRS patients. A Sleep-SNOT score of ≥17.5 should prompt further OSA evaluation. The Sleep-SNOT may be considered as a surrogate OSA screening tool when other validated tools are not employed. Retrospective chart review, Level 3 Laryngoscope, 133:2029-2034, 2023.