Apnea-hypopnea Index Cutoff Research Articles

Prevalence of obstructive sleep apnea in a sample of Egyptian railway drivers

Background There are scanty international and even no Egyptian studies addressing the prevalence of obstructive sleep apnea syndrome (OSAS) in railway drivers with an expected high risk of accidents. Thus, it is worth studying and assessing the prevalence and predictors of OSAS among Egyptian railway drivers. Patients and methods This prospective cross-sectional screening study was conducted on 160 Egyptian railway drivers. They were subjected to medical history taking and examination, anthropometric measurements, oxygen saturation (SpO2) by oximetry, arterial blood gases, Friedman obstructive sleep apnea–hypopnea syndrome score measurement, and Arabic version of both Berlin and STOP BANG questionnaires. Then, limited night polysomnography (PSG) was performed in high-risk patients. Finally, full channel PSG was done for positive limited night PSG. Results The prevalence of sleep apnea among the studied cases was 4.22%. There was high statistically significant difference between the non-OSAS group and the OSAS group regarding age less than or equal to 49 years [odds ratio (OR)=11.364], witnessed apneas during sleep (OR=175), weight in kg more than 95 (OR=13.00), PaO2 less than or equal to 88 (OR=31.0), PaCO2 more than 39 (OR=31.0), and average SPO2 less than or equal to 88 (OR=34.0). Regarding parameters of limited night PSG, the apnea–hypopnea index cutoff point was more than or equal to 5 with an area under the curve (AUC) of 100%, O2 desaturation index cutoff point was more than 17.2 with an AUC of 100%; lastly, the average SPO2 cutoff point was less than or equal to 88% with an AUC of 76.4%. Conclusion This study highlights for the first time that the prevalence of OSAS was 4.2% in a sample of Egyptian railway drivers. Our results further point out that weight, neck circumference, systolic blood pressure, PaO2, and PaCO2 are the most useful predictors of suspecting OSAS. Also, parameters of limited PSG are considered a useful tool in confirming suspected patients with OSAS.

Endothelial Function and Arterial Stiffness Should Be Measured to Comprehensively Assess Obstructive Sleep Apnea in Clinical Practice.

Objective: An effective clinical tool to assess endothelial function and arterial stiffness in patients with obstructive sleep apnea (OSA) is lacking. This study evaluated the clinical significance of subclinical markers for OSA management in males without serious complications.Patients/Methods: Males without serious complications were consecutively recruited. Clinical data, biomarker tests, reactive hyperemia index (RHI), and augmentation index at 75 beats/min (AIx75) measured by peripheral arterial tonometry were collected. An apnea hypopnea index (AHI) cutoff of ≥15 events/h divided the patients into two groups.Results: Of the 75 subjects, 42 had an AHI ≥15 events/h. Patients with an AHI ≥15 events/h had higher high-sensitivity C-reactive protein, tumor necrosis factor-alpha (TNF-α), vascular endothelial growth factor, and AIx75 values than the control group but no statistical difference in RHI was observed. After controlling for confounders, TNF-α was negatively correlated with the average oxygen saturation (r = −0.258, P = 0.043). RHI was correlated with the rapid eye movement (REM) stage percentage (r = 0.306, P = 0.016) but not with AHI (P > 0.05). AIx75 was positively correlated with the arousal index (r = 0.289, P = 0.023) but not with AHI (r = 0.248, P = 0.052).Conclusions: In males with OSA without severe complications, TNF-α and AIx75 are independently related to OSA. The role of RHI in OSA management requires further elucidation. These markers combined can comprehensively evaluate OSA patients to provide more evidence for the primary prevention of coronary heart disease and treatment response assessment.

Hybrid CNN-LSTM Network for Real-Time Apnea-Hypopnea Event Detection Based on IR-UWB Radar

Polysomnography (PSG) is the gold-standard for sleep apnea and hypopnea syndrome (SAHS) diagnosis. Because the PSG system is not suitable for long-term continuous use owing to the high cost and discomfort caused by attached multi-channel sensors, alternative methods using a non-contact sensor have been investigated. However, the existing methods have limitations in that the radar-person distance is fixed, and the detected apnea hypopnea (AH) event cannot be provided in real-time. In this paper, therefore, we propose a novel approach for real-time AH event detection with impulse-radio ultra-wideband (IR-UWB) radar using a deep learning model. 36 PSG recordings and simultaneously measured IR-UWB radar data were used in the experiments. After the clutter was removed, IR-UWB radar images were segmented by sliding a 20-s window at 1-s shift, and categorized into two classes: AH and N. A hybrid model combining the convolutional neural networks and long short-term memory networks was trained with the data, which consisted of class-balanced segments. Time sequenced classified outputs were then fed to an event detector to identify valid AH events. Therefore, the proposed method showed a Cohen’s kappa coefficient of 0.728, sensitivity of 0.781, specificity of 0.956, and an accuracy of 0.930. According to the apnea-hypopnea index (AHI) estimation analysis, the Pearson’s correlation coefficient between the estimated AHI and reference AHI was 0.97. In addition, the average accuracy and kappa of SAHS diagnosis was 0.98 and 0.96, respectively, for AHI cutoffs of ≥ 5, 15, and 30 events/h. The proposed method achieved the state-of-the-art performance for classifying SAHS severity without any hand-engineered feature regardless of the user’s location. Our approach can be utilized for a cost-effective and reliable SAHS monitoring system in a home environment.

Validation of home portable monitoring for the diagnosis of sleep-disordered breathing in adolescents and adults with neuromuscular disorders.

Sleep-disordered breathing (SDB) is common in patients with neuromuscular disorders (NMD), developing before chronic hypercapnia appears. Polysomnography (PSG) is the diagnostic gold standard but is often impractical and poorly accessible for individuals with NMD. We sought to determine the diagnostic accuracy, feasibility, and patient preference of home sleep apnea testing (HSAT) compared with PSG for the detection of SDB in NMD. Participants with NMD at risk for SDB aged ≥ 13 years underwent HSAT followed by overnight PSG with concomitant laboratory sleep apnea testing (same device as HSAT). Sensitivity and specificity were calculated for standard apnea-hypopnea index cutoffs for mild (≥ 5 events/h), moderate (≥ 15 events/h), and severe SDB (≥ 30 events/h) and for an oxygen desaturation index ≥ 5 events/h. Receiver operating characteristic curves were built. A questionnaire assessed patient preference. Of 38 participants, 73% had moderate to severe SDB and 79% had technically acceptable HSAT. For an apnea-hypopnea index ≥ 15 events/h, HSAT sensitivity and specificity were 50% and 88%, respectively. For an oxygen desaturation index ≥ 5 events/h, HSAT sensitivity and specificity were 95% and 78%, respectively. The area under the receiver operating characteristic curve for an apnea-hypopnea index ≥ 15 events/h was 0.88 (95% confidence interval, 0.69-1.00) for HSAT. The HSAT underestimated the apnea-hypopnea index from PSG (bias, -10.7 ± 15.9 events/h). HSAT was preferred to PSG by 61% of participants. HSAT is feasible, preferred by patients, and reliable for detecting SDB in most patients, although it cannot definitively rule out SDB. Therefore, HSAT is a viable diagnostic approach for SDB in NMD when PSG is not feasible, recognizing that it does not accurately distinguish between upper-airway obstruction and hypoventilation. Additional work is needed to further optimize home sleep testing in NMD. Westenberg JN, Petrof BJ, Noel F, et al. Validation of home portable monitoring for the diagnosis of sleep-disordered breathing in adolescents and adults with neuromuscular disorders. J Clin Sleep Med. 2021;17(8):1579-1590.

Bispectral analysis of overnight airflow to improve the pediatric sleep apnea diagnosis

Pediatric Obstructive Sleep Apnea (OSA) is a respiratory disease whose diagnosis is performed through overnight polysomnography (PSG). Since it is a complex, time-consuming, expensive, and labor-intensive test, simpler alternatives are being intensively sought. In this study, bispectral analysis of overnight airflow (AF) signal is proposed as a potential approach to replace PSG when indicated. Thus, our objective was to characterize AF through bispectrum, and assess its performance to diagnose pediatric OSA. This characterization was conducted using 13 bispectral features from 946 AF signals. The oxygen desaturation index ≥3% (ODI3), a common clinical measure of OSA severity, was also obtained to evaluate its complementarity to the AF bispectral analysis. The fast correlation-based filter (FCBF) and a multi-layer perceptron (MLP) were used for subsequent automatic feature selection and pattern recognition stages. FCBF selected 3 bispectral features and ODI3, which were used to train a MLP model with ability to estimate apnea-hypopnea index (AHI). The model reached 82.16%, 82.49%, and 90.15% accuracies for the common AHI cut-offs 1, 5, and 10 events/h, respectively. The different bispectral approaches used to characterize AF in children provided complementary information. Accordingly, bispectral analysis showed that the occurrence of apneic events decreases the non-gaussianity and non-linear interaction of the AF harmonic components, as well as the regularity of the respiratory patterns. Moreover, the bispectral information from AF also showed complementarity with ODI3. Our findings suggest that AF bispectral analysis may serve as a useful tool to simplify the diagnosis of pediatric OSA, particularly for children with moderate-to-severe OSA.

Effects of age and sex on the performance of the NoSAS score as a screening tool for obstructive sleep apnea: a hospital-based retrospective study in China.

The NoSAS score has been shown to be a reliable screening tool for obstructive sleep apnea (OSA) in overall populations. This study aimed to explore the effects of age and sex on the predicting performance of this score. A retrospective analysis was conducted on 1119 subjects aged ≥ 18 years and with a total sleep time of ≥ 4 h during overnight polysomnography. Discrimination was assessed by using areas under receiver operating characteristic curve (AUCs), while predictive parameters were calculated by using contingency tables. Overall, a NoSAS score of 8 points or higher resulted in sensitivity, specificity, and AUC for predicting an apnea-hypopnea index (AHI) of ≥ 20 events/h of 74%, 36%, and 0.63 (in non-elderly 73%, 46%, and 0.65; in elderly 91%, 17%, and 0.59; in men 85%, 18%, and 0.56; in women 52%, 76%, and 0.71, respectively). The AUCs at all AHI cutoffs were significantly lower in men than in women (all with p < 0.01), while the AUCs at AHI cutoff of 5, 15, and 30 events/h were significantly lower in elderly than in non-elderly (p < 0.01, 0.05, and 0.05, respectively). In non-elderly, a conventional NoSAS with cutoff of 7 or a modified NoSAS with age cutoff of 50 years provided sensitivity and specificity for predicting an AHI of ≥ 20 events/h of 87%, 37% and 80%, 36%, respectively, with comparable AUCs. In women, a conventional NoSAS with cutoff of 6 or a modified NoSAS with neck circumference cutoff of 35 cm provided sensitivity and specificity for predicting an AHI of ≥ 20 events/h of 85%, 39% and 79%, 52%, respectively, with comparable AUCs. NoSAS score has better discrimination but lower sensitivity for predicting OSA in non-elderly and women than in their counterparts. Age- and sex-specific cutoff values reverse this imbalance. Our results underline the preference of age- and sex-specific cutoff values and the need for better age- and sex-specific screening algorithms.

Clinical, polysomnographic, and cephalometric features of obstructive sleep apnea with AHI over 100.

Obstructive sleep apnea (OSA) is induced by a sleep-related collapse of the upper airway in association with multiple factors. The severity of OSA is determined by the apnea-hypopnea index (AHI). Although obesity and sex differences are common factors in OSA, the level of the AHI varies to the same degree according to the age and sex and degree of obesity. However, only a few studies have evaluated AHI over 100/h, those reports did not describe why they set the AHI cutoff at 100/h. The purpose of this study was to elucidate the pathogenesis of "very" severe OSA, defined as having an AHI > 100/h. AHI > 100/h was set as very severe OSA (VS-OSA) in this study. As controls, moderate to severe OSA patients, matched with VS-OSA for age, sex, and body mass index (BMI), were enrolled. The findings of polysomnography and cephalography between VS-OSA and controls were compared. Eleven patients in the VS-OSA group (mean AHI 110.2/h) and 22 patients in the control group (mean AHI 41.6/h) were compared (mean age 50.2 vs 50.6, male:female 5:6 vs 10:12, mean BMI 35.4kg/m2 vs 34.5kg/m2). There were no significant differences in the clinical characteristics. In the polysomnographic parameters, the VS-OSA group showed apnea predominance, the mean percutaneous oxygen saturation (SO2) was significantly lower in all sleep stages, and the minimum SO2 was significantly lower (49.0% vs 77.5%, p = 0.002). A similar apnea duration and rather shorter hypopnea duration were shown. The time of apnea-to-arousal was significantly earlier (- 0.1s vs 0.9s, p = 0.003). Lung-to-finger circulation time showed no differences. The cephalometric findings showed no significant differences. VS-OSA patients were more likely to have apnea predominance, desaturation when sleeping despite a similar apnea duration, and rather shorter hypopnea duration, and arousals were evoked significantly earlier.

Does the Lack of Gender-Specific Apnea-Hypopnea Index Cutoff for Obstructive Sleep Apnea Impact Surgical Selection?

The apnea-hypopnea index (AHI) is the parameter on which the severity of obstructive sleep apnea (OSA) is based and is also the determinant for both clinicians and third-party payers for surgical procedures. The purpose of this retrospective cross-sectional chart review is to examine differences in symptoms and AHI between men and women with OSA and whether this may impact timing and selection of surgical care. Retrospective cross-sectional study of patients aged 18years and older who presented at a single center for surgical evaluation of OSA from January 2017 to 2020. AHI, oxygen desaturation index, respiratory disturbance index, and lowest oxygen saturation were obtained from polysomnography. The predictor variable was gender, and the outcome variable was AHI. Unadjusted and multivariate adjusted linear regression models were used to compare differences in AHI between gender, controlling for age, body mass index (BMI), Epworth sleepiness scale, and fatigue severity scale. Poisson regression analysis with robust error was used to assess the relative risks of antidepressant and anxiolytic medication use between genders. A total of 408 consecutive new patients seen for surgical evaluation to treat OSA (248 men and 160 women) were included. Median patient age was 40years for men and 41years for women. Median AHI for men was 22.1 events per hour and 13.7 for women (P<.001). When adjusted for age and BMI, men have 33.2% higher AHI than women, with age contributing to 2% and BMI contributing to 6% of the difference. When controlling for age, BMI, Epworth sleepiness scale, and fatigue severity scale, women have a 2.2 increased relative risk of taking anxiolytic or antidepressant medications. Women with OSA seeking surgery in a dedicated sleep practice have 33% lower AHI than men when controlling for age, BMI, and symptoms. Based on our findings, non-gender-specific AHI may handicap the surgeon from offering the full range of available procedures to women with OSA.

When will we ditch the AHI?

When will we ditch the AHI?

Assessment of Airflow and Oximetry Signals to Detect Pediatric Sleep Apnea-Hypopnea Syndrome Using AdaBoost.

The reference standard to diagnose pediatric Obstructive Sleep Apnea (OSA) syndrome is an overnight polysomnographic evaluation. When polysomnography is either unavailable or has limited availability, OSA screening may comprise the automatic analysis of a minimum number of signals. The primary objective of this study was to evaluate the complementarity of airflow (AF) and oximetry (SpO2) signals to automatically detect pediatric OSA. Additionally, a secondary goal was to assess the utility of a multiclass AdaBoost classifier to predict OSA severity in children. We extracted the same features from AF and SpO2 signals from 974 pediatric subjects. We also obtained the 3% Oxygen Desaturation Index (ODI) as a common clinically used variable. Then, feature selection was conducted using the Fast Correlation-Based Filter method and AdaBoost classifiers were evaluated. Models combining ODI 3% and AF features outperformed the diagnostic performance of each signal alone, reaching 0.39 Cohens’s kappa in the four-class classification task. OSA vs. No OSA accuracies reached 81.28%, 82.05% and 90.26% in the apnea–hypopnea index cutoffs 1, 5 and 10 events/h, respectively. The most relevant information from SpO2 was redundant with ODI 3%, and AF was complementary to them. Thus, the joint analysis of AF and SpO2 enhanced the diagnostic performance of each signal alone using AdaBoost, thereby enabling a potential screening alternative for OSA in children.

Comparison of Diagnostic Sleep Studies in Hospitalized Neurorehabilitation Patients With Moderate to Severe Traumatic Brain Injury

OSA is prevalent during a time of critical neural repair after traumatic brain injury (TBI). The diagnostic utility of existing sleep studies is needed to inform clinical management during acute recovery from TBI. This study aimed to evaluate the non-inferiority and diagnostic accuracy of a portable level 3 sleep study relative to level 1 polysomnography in hospitalized neurorehabilitation patients with TBI. This is a prospective clinical trial conducted at six TBI Model System study sites between May 2017 and February 2019. Of 896 admissions, 449 were screened and eligible for the trial, with 345 consented. Additional screening left 263 eligible for and completing simultaneous administration of both level 1 and level 3 sleep studies, with final analyses completed on 214 (median age= 42 years; ED Glasgow Coma Scale= 6; time to polysomnography [PSG]= 52days). Agreement was moderate to strong (weighted kappa= 0.78, 95%CI, 0.72-0.83) with the misclassification commonly occurring with mild sleep apnea due to underestimation of apnea hypopnea index (AHI). Most of those with moderate to severe sleep apnea were correctly classified (n= 54/72). Non-inferiority was not demonstrated: the minimum tolerable specificity of 0.5 was achieved across all AHI cutoff scores (lower confidence limits [LCL] range, 0.807-0.943), but the minimum tolerable sensitivity of 0.8 was not (LCL range, 0.665-0.764). Although the non-inferiority of level 3 portable diagnostic testing relative to level 1 was not established, strong agreement was seen across sleep apnea indexes. Most of those with moderate to severe sleep apnea were correctly identified; however, there was risk of misclassification with level 3 sleep studies underestimating disease severity for those with moderate to severe AHI and disease presence for those with mild AHI during early TBI neurorehabilitation.

Association of Sleep-Disordered Breathing With Alzheimer Disease Biomarkers in Community-Dwelling Older Adults

Increasing evidence suggests that sleep-disordered breathing (SDB) increases the risk of developing Alzheimer clinical syndrome. However, the brain mechanisms underlying the link between SDB and Alzheimer disease are still unclear. To determine which brain changes are associated with the presence of SDB in older individuals who are cognitively unimpaired, including changes in amyloid deposition, gray matter volume, perfusion, and glucose metabolism. This cross-sectional study was conducted using data from the Age-Well randomized clinical trial of the Medit-Ageing European project, acquired between 2016 and 2018 at Cyceron Center in Caen, France. Community-dwelling older adults were assessed for eligibility and were enrolled in the Age-Well clinical trial if they did not meet medical or cognitive exclusion criteria and were willing to participate. Participants who completed a detailed neuropsychological assessment, polysomnography, a magnetic resonance imaging, and florbetapir and fluorodeoxyglucose positron emission tomography scans were included in the analyses. Based on an apnea-hypopnea index cutoff of 15 events per hour, participants were classified as having SDB or not. Voxelwise between-group comparisons were performed for each neuroimaging modality, and secondary analyses aimed at identifying which SDB parameter (sleep fragmentation, hypoxia severity, or frequency of respiratory disturbances) best explained the observed brain changes and assessing whether SDB severity and/or SDB-associated brain changes are associated with cognitive and behavioral changes. Of 157 participants initially assessed, 137 were enrolled in the Age-Well clinical trial, and 127 were analyzed in this study. The mean (SD) age of the 127 participants was 69.1 (3.9) years, and 80 (63.0%) were women. Participants with SDB showed greater amyloid burden (t114 = 4.51; familywise error-corrected P = .04; Cohen d, 0.83), gray matter volume (t119 = 4.12; familywise error-corrected P = .04; Cohen d, 0.75), perfusion (t116 = 4.62; familywise error-corrected P = .001; Cohen d, 0.86), and metabolism (t79 = 4.63; familywise error-corrected P = .001; Cohen d, 1.04), overlapping mainly over the posterior cingulate cortex and precuneus. No association was found with cognition, self-reported cognitive and sleep difficulties, or excessive daytime sleepiness symptoms. The SDB-associated brain changes in older adults who are cognitively unimpaired include greater amyloid deposition and neuronal activity in Alzheimer disease-sensitive brain regions, notably the posterior cingulate cortex and precuneus. These results support the need to screen and treat for SDB, especially in asymptomatic older populations, to reduce Alzheimer disease risk. ClinicalTrials.gov Identifier: NCT02977819.

Are Sleep Questionnaires Valid in All Adult Age Groups as Screening Tools for Obstructive Sleep Apnea?

Background and Objectives: Evaluation of Epworth Sleepiness Scale (ESS), Berlin, STOP, and STOP-Bang questionnaire validities for obstructive sleep apnea (OSA) screening among various adult age groups.Materials and Method: Results for each of those questionnaires were compared with diagnostic overnight polysomnography (PSG) data obtained for 396 patients suffering either insomnia, sleep apnea, excessive daytime sleepiness, or chronic snoring who had been divided into three age groups (20-39, 40-59, or ≥60 years). For each questionnaire, the sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated.Results: Among the OSA group [apnea hypopnea index (AHI) cutoff ＞5], Berlin and STOP questionnaire sensitivity and specificity were significantly different among the age groups. Among the moderate-to-severe OSA sub-group (AHI cutoff ＞15), the specificity of Berlin, STOP, and STOP-Bang questionnaire was significantly different among age groups.Conclusion: The Berlin and STOP questionnaires differed with patient age in OSA screening. The ESS questionnaire, by contrast, did not show any age-related differences of sensitivity and specificity in OSA screening or moderate-to-severe OSA screening.

Exploring the STOP-BANG questionnaire for obstructive sleep apnea screening in seniors.

The accuracy of obstructive sleep apnea (OSA) screening instruments in seniors may change as the predictive role of sex, age, and body mass index (BMI) changes with aging. We investigated the diagnostic performance of the STOP-BANG questionnaire in older individuals with aging-adapted scores and thresholds. Independent community-dwelling adults aged 65 years or older were screened for OSA. The STOP-BANG questionnaire was tested with different configurations and compared to the apnea-hypopnea index (AHI) obtained from home sleep apnea testing (HSAT). Epworth Sleepiness Scale (ESS) and Athens Insomnia Scale (AIS) were tested as possible supplementary screening criteria. We recruited 458 individuals with a mean age of 71 ± 5 years, 41% men, BMI of 28.5 ± 4.6 kg/m². Mild, moderate, and severe OSA were present in, respectively, 34%, 30%, and 19% of the sample. The STOP questions had an area under the curve (AUC) of the receiver operating characteristic curve significantly lower than the STOP-BANG and the STOP+BMI > 28 kg/m² (STOP-B28). Both STOP-BANG and STOP-B28 had high sensitivity and low specificity in all OSA levels with similar AUC to predict AHI ≥ 5 events/h, 0.64. ESS and AIS were nonsignificant as adjunctive instruments. Novel modifications of a standard instrument created the STOP-B28, a simpler-to-obtain and similarly performing variation of the STOP-BANG using fewer inputs, and useful to exclude OSA. Screening seniors via questionnaires to detect OSA is problematic. Considering the 83% OSA prevalence in this age group, it may be a sensible option to indicate objective tests, oximetry, HSAT, or even polysomnography, as a first step in OSA investigation.

Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample.

Study ObjectivesPolysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to develop a clinically useful support vector machine (SVM)-based prediction model to identify patients with high probability of OSA for nonsleep specialist physician in clinical practice.MethodsThe SVM model was developed using the features routinely collected at the clinical evaluation from 6,875 Chinese patients referred to sleep clinics for suspected OSA. Three apnea-hypopnea index (AHI) cutoffs, ≥5/h, ≥15/h, and ≥30/h were used to define the severity of OSA. The continuous and categorized features were selected separately and were further selected through stepwise forward feature selection. The modeling was achieved through fivefold cross-validation. The model discriminative ability was evaluated for the whole data set and four subgroups categorized with gender and age (<65 versus ≥65 years old [y/o]).ResultsTwo features were selected to predict AHI cutoff ≥5/h with six features selected for ≥15/h, and six features selected for ≥30/h, respectively, to reach Area under the Receiver Operating Characteristic (AUROC) 0.82, 0.80, and 0.78, respectively. The sensitivity was 74.14%, 75.18%, and 70.26%, while the specificity was 74.71%, 68.73%, and 70.30%, respectively. Compared to logistic regression, Berlin questionnaire, NoSAS Score, and Supersparse Linear Integer Model (SLIM) scoring system, the SVM model performs better with a more balanced sensitivity and specificity. The discriminative ability was best for male <65 y/o and modest for female ≥65 y/o.ConclusionOur model provides a simple and accurate modality for early identification of patients with OSA and may potentially help prioritize them for sleep study.

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic.

Background There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

Accuracy of WatchPAT for the Diagnosis of Obstructive Sleep Apnea in Patients with Chronic Obstructive Pulmonary Disease

The co-existence of chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA), termed the overlap syndrome (OVS), is associated with adverse outcomes that may be reversed with treatment. However, diagnosis is limited by the apparent need for in-laboratory polysomnography (PSG). WatchPAT is a portable diagnostic device that is validated for the diagnosis of OSA that might represent an attractive tool for the diagnosis of OVS.Subjects with established COPD were recruited from a general population. Subjects underwent PSG and simultaneous recording with WatchPAT. Pulmonary function testing and questionnaires were also performed.A total of 36 subjects were recruited and valid data was obtained on 33 (age 63 ± 7, BMI 28 ± 7, 61% male, FEV1 56 ± 20% predicted). There was no significant difference in the apnea–hypopnea index (AHI) between PSG and WatchPAT (19 ± 20 versus 20 ± 15 events/h; mean difference 2(–2, 5) events/h; p = 0.381). The AHI was not significantly different in rapid eye movement (REM) and non-rapid eye movement (NREM) determined by PSG versus REM and NREM determined by WatchPAT. WatchPAT slightly overestimated total and REM sleep time, and sleep efficiency. The sensitivity of WatchPAT at an AHI cut-off of ≥5, ≥15, and ≥30 events/h for corresponding PSG AHI cut-offs was 95.8, 92.3, and 88.9, respectively; specificity was 55, 65.0, and 95.8, respectively.WatchPAT is able to determine OSA reliably in patients with COPD. The availability of this additional diagnostic modality may lead to improved detection of OVS, which may in turn lead to improved outcomes for a group of COPD patients at high risk of poor outcomes.

Current Practice Patterns in the Diagnosis and Management of Sleep-Disordered Breathing in Infants.

Currently, there are no universally accepted guidelines for diagnosis and management of sleep-disordered breathing (SDB) in infants. The purpose of this study was to survey pediatric sleep medicine providers regarding their current practice patterns for diagnosis and management of SDB in infants. An anonymous, web-based survey with 71 questions was distributed via the PEDSLEEP and Ped-Lung listserv, which serve as a hub of communication for pediatric sleep and pulmonary medicine providers worldwide. Fifty-four providers from eight countries completed the survey. Ninety-six percent of providers reported performing sleep studies in infants with 53% performing more than 30 studies per year. There was no consensus on the definition of obstructive sleep apnea (OSA) in infants when using an obstructive apnea-hypopnea index (AHIo) cutoff: AHIo > 1 (30%), AHIo > 2 (35%), AHIo > 5 (24%), AHIo > 10 (2%) and other (9.3%). Thirty-six percent did not use pediatric criteria to define severity of OSA in infants. Opinions regarding management of five typical SDB cases were solicited and the results varied among respondents. Most of the providers (89%) thought that more research is needed to gather normative sleep data in infants and that their practice would benefit from evidence- based guidelines for diagnosis and management of SDB in infants (98%). These results demonstrate substantial variability in practice patterns for diagnosis and management of SDB in infants. Further research and consensus guidelines are needed to ensure optimal care for infants with SDB.

The Accuracy of an Ambulatory Level III Sleep Study Compared to a Level I Sleep Study for the Diagnosis of Sleep-Disordered Breathing in Children With Neuromuscular Disease.

Polysomnography (PSG) surveillance recommendations are not being met for children with neuromuscular disease (NMD) because of limited diagnostic facilities. We evaluated the diagnostic accuracy of an ambulatory level III device as compared to a level I PSG. A cross-sectional study was conducted at a tertiary pediatric institution. Eligibility criteria included: (1) children with NMD; (2) age 6 to 18 years; (3) booked for a clinically indicated overnight level I PSG. Participants were randomized to an overnight level I PSG followed by an ambulatory level III study with end tidal carbon dioxide (etCO2) or vice versa. Sensitivity and specificity of the ambulatory level III device to diagnose sleep-disordered breathing (SDB) at an apnea-hypopnea index (AHI) cutoff of > 1.0 events/h was the primary outcome. Moderate to severe SDB was found in 46% of participants (13/28). The device's sensitivity and specificity to detect SDB was 61.5% and 86.7%, respectively. The positive predictive value of the level III study was 80.0% and the negative predictive value was 72.0%. Fifty percent of the cohort were either missing or had incomplete or falsely low ambulatory etCO2 data. A level III device with etCO2 is not yet able to be implemented in clinical practice as a diagnostic tool for SDB in pediatric patients with NMD. A commentary on this article appears in this issue on page 1973.

Wavelet analysis of oximetry recordings to assist in the automated detection of moderate-to-severe pediatric sleep apnea-hypopnea syndrome.

BackgroundThe gold standard for pediatric sleep apnea hypopnea syndrome (SAHS) is overnight polysomnography, which has several limitations. Thus, simplified diagnosis techniques become necessary.ObjectiveThe aim of this study is twofold: (i) to analyze the blood oxygen saturation (SpO2) signal from nocturnal oximetry by means of features from the wavelet transform in order to characterize pediatric SAHS; (ii) to evaluate the usefulness of the extracted features to assist in the detection of pediatric SAHS.Methods981 SpO2 signals from children ranging 2–13 years of age were used. Discrete wavelet transform (DWT) was employed due to its suitability to deal with non-stationary signals as well as the ability to analyze the SAHS-related low frequency components of the SpO2 signal with high resolution. In addition, 3% oxygen desaturation index (ODI3), statistical moments and power spectral density (PSD) features were computed. Fast correlation-based filter was applied to select a feature subset. This subset fed three classifiers (logistic regression, support vector machines (SVM), and multilayer perceptron) trained to determine the presence of moderate-to-severe pediatric SAHS (apnea-hypopnea index cutoff ≥ 5 events per hour).ResultsThe wavelet entropy and features computed in the D9 detail level of the DWT reached significant differences associated with the presence of SAHS. All the proposed classifiers fed with a selected feature subset composed of ODI3, statistical moments, PSD, and DWT features outperformed every single feature. SVM reached the highest performance. It achieved 84.0% accuracy (71.9% sensitivity, 91.1% specificity), outperforming state-of-the-art studies in the detection of moderate-to-severe SAHS using the SpO2 signal alone.ConclusionWavelet analysis could be a reliable tool to analyze the oximetry signal in order to assist in the automated detection of moderate-to-severe pediatric SAHS. Hence, pediatric subjects suffering from moderate-to-severe SAHS could benefit from an accurate simplified screening test only using the SpO2 signal.