SOS score: an optimized score to screen acute stroke patients for obstructive sleep apnea

Utility of Sleep Questionnaires for Detecting Sleep Apnea in Ischemic Stroke Patients

BACKGROUND AND OBJECTIVES

Sleep-disordered breathing is highly prevalent in stroke patients. It is associated with recurrence of stroke and poor neurologic outcomes. Polysomnography (PSG), the gold standard for diagnosing sleep apnea, may not be feasible for routine evaluation in stroke patients. There is a need for reliable screening tools to assess the likelihood of sleep apnea in these patients. This study evaluated the efficacy of sleep questionnaires to predict the likelihood of sleep apnea against PSG-determined sleep apnea.

METHODS

A hospital-based study on ischemic stroke patients used the content-validated Kannada version of Berlin Questionnaire, STOP-BANG questionnaire, and Epworth Sleepiness Scale (ESS). All patients underwent overnight PSG, scored by blinded investigators, to assess the diagnostic properties of the questionnaires for various apnea-hypopnea index cutoffs.

RESULTS

The study included 70 Kannada-speaking patients with a mean age of 50.9 years. The study revealed a high prevalence of sleep apnea (80%), with obstructive sleep apnea being the most common type (77.5%). The Berlin Questionnaire showed modest sensitivity (0.51) and specificity (0.60), while the STOP-BANG questionnaire demonstrated moderate sensitivity (0.64) and specificity (0.70). The mean ESS scores were 6.6 (standard deviation [SD] 5.9) for patients with sleep apnea and 4.3 (SD 3.1) for those without sleep apnea.

CONCLUSION

Sleep questionnaires lacked the necessary diagnostic properties to serve as standalone screening tools for sleep apnea in ischemic stroke patients. Future research should aim to develop or improve screening instruments specifically designed for stroke patients.

Performance of questionnaires to predict sleep-disordered breathing in acute stroke patients

Sleep-disordered breathing is common in stroke and may negatively affect its outcome. Screening for sleep-disordered breathing in this setting is of interest but poorly studied. We aimed to evaluate the performance of eight obstructive sleep apnea screening questionnaires to predict sleep-disordered breathing in acute stroke or transient ischaemic attack patients, and to assess the impact of stroke/transient ischaemic attack-specific factors on sleep-disordered breathing prediction. We analysed acute stroke/transient ischaemic attack patients (N = 195) from a prospective cohort ("Sleep Deficiency and Stroke Outcome study"). Assessments included anthropometrics, stroke-specific parameters, sleep history, an in-hospital respiratory polygraphy within the first week after stroke, and obstructive sleep apnea screening questionnaires (Berlin Questionnaire, Epworth Sleepiness Scale, STOP-BANG, NoSAS, Sleep Apnea Clinical Score, No-Apnea, Sleep Obstructive apnea score optimized for Stroke, SLEEP-IN). In a binary classification task for respiratory event index ≥ 15 per hr, we evaluated the performance of the above-mentioned questionnaires. We used logistic regression to identify predictors for sleep-disordered breathing in this cohort. The areas under the curve for respiratory event index ≥ 15 per hr were: Berlin Questionnaire 0.60; STOP-BANG 0.72; NoSAS 0.69; No-Apnea 0.69; Sleep Apnea Clinical Score 0.75; Epworth Sleepiness Scale 0.50; Sleep Obstructive apnea score optimized for Stroke 0.58; and SLEEP-IN 0.67. The No-Apnea had the lowest false omission rate (0.13), a sensitivity of 0.97 and a specificity of 0.12. In multiple logistic regression analysis (respiratory event index ≥ 15 per hr), age, neck circumference, National Institutes of Health Stroke Scale at admission, prior stroke, cardioembolic stroke aetiology and observed apneas were associated with sleep-disordered breathing. The logistic regression model performed similar (area under the curve 0.80) to Sleep Apnea Clinical Score (p = 0.402) and STOP-BANG (p = 0.127), but outperformed the other questionnaires. Neither existing questionnaires nor our statistical model are sufficient to accurately diagnose sleep-disordered breathing after stroke, thus requiring sleep study evaluation. The No-Apnea questionnaire may help to identify patients amenable to sleep testing.

Prevalence and Detection of Obstructive Sleep Apnea Early after Stroke

Background

Obstructive sleep apnea (OSA) negatively impacts post-stroke recovery. This study's purpose: examine the prevalence of undiagnosed OSA and describe a simple tool to identify those at-risk for OSA in the early phase of stroke recovery.

Methods

This was a cross-sectional descriptive study of people ∼15 days post-stroke. Adults with stroke diagnosis admitted to inpatient rehabilitation over a 3-year period were included if they were alert/arousable, able to consent/assent to participation, and excluded if they had a pre-existing OSA diagnosis, other neurologic health conditions, recent craniectomy, global aphasia, inability to ambulate 150 feet independently pre-stroke, pregnant, or inability to understand English. OSA was deemed present if oxygen desaturation index (ODI) of >=15 resulted from overnight oximetry measures. Prevalence of OSA was determined accordingly. Four participant characteristics comprised the "BASH" tool (body mass index >=35, age>=50, sex=male, hypertension=yes). A receiver operator characteristics (ROC) curve analysis was performed with BASH as test variable and OSA presence as state variable.

Results

Participants (n=123) were 50.4% male, averaged 64.12 years old (sd 14.08), and self-identified race as 75.6% White, 20.3% Black/African American, 2.4%>1 race, and 1.6% other; 22% had OSA. ROC analysis indicated BASH score >=3 predicts presence of OSA (sensitivity=0.778, specificity=0.656, area under the curve =0.746, p<0.001).

Conclusions

Prevalence of undiagnosed OSA in the early stroke recovery phase is high. With detection of OSA post-stroke, it may be possible to offset untreated OSA's deleterious impact on post-stroke recovery of function. The BASH tool is an effective OSA screener for this application.

Clinical prediction models for the early diagnosis of obstructive sleep apnea in stroke patients: a systematic review

BACKGROUND

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by repetitive cessation or reduction in airflow during sleep. Stroke patients have a higher risk of OSA, which can worsen their cognitive and functional disabilities, prolong their hospitalization, and increase their mortality rates.

METHODS

We conducted a comprehensive literature search in the databases of PubMed, CINAHL, Embase, PsycINFO, Cochrane Library, and CNKI, using a combination of keywords and MeSH words in both English and Chinese. Studies published up to March 1, 2022, which reported the development and/or validation of clinical prediction models for OSA diagnosis in stroke patients.

RESULTS

We identified 11 studies that met our inclusion criteria. Most of the studies used logistic regression models and machine learning approaches to predict the incidence of OSA in stroke patients. The most frequently selected predictors included body mass index, sex, neck circumference, snoring, and blood pressure. However, the predictive performance of these models ranged from poor to moderate, with the area under the receiver operating characteristic curve varying from 0.55 to 0.82. All the studies have a high overall risk of bias, mainly due to the small sample size and lack of external validation.

CONCLUSION

Although clinical prediction models have shown the potential for diagnosing OSA in stroke patients, their limited accuracy and high risk of bias restrict their implications. Future studies should focus on developing advanced algorithms that incorporate more predictors from larger and representative samples and externally validating their performance to enhance their clinical applicability and accuracy.

SAS Care 1: sleep-disordered breathing in acute stroke an transient ischaemic attack - prevalence, evolution and association with functional outcome at 3 months, a prospective observational polysomnography study

Sleep-disordered breathing (SDB) is frequent in patients with acute stroke. Little is known, however about the evolution of SDB after stroke. Most of our knowledge stems from smaller cohort studies applying limited cardiopulmonary sleep recordings or from cross-sectional data collected in different populations.

This study aims to determine prevalence, type and intra-individual evolution of SDB based on full-night polysomnography (PSG) in acute stroke and 3 months thereafter. Furthermore, we aimed to identify predictors of SDB in the acute and chronic phase and to evaluate associations between SDB and functional outcome at 3 months (M3).

A total of 166 patients with acute cerebrovascular events were evaluated by full PSG at baseline and 105 again at M3. The baseline prevalence of SDB (apnoea–hypopnoea index (AHI)>5·h⁻¹) was 80.5% and 25.4% of the patients had severe SDB (AHI>30·h⁻¹). Obstructive sleep apnoea was more prevalent than central sleep apnoea (83.8% versus 13%). Mean±SD AHI was 21.4±17.6·h⁻¹and decreased significantly at M3 (18±16.4·h⁻¹; p=0.018). At M3, 91% of all patients with baseline SDB still had an AHI>5·h⁻¹ and in 68.1% the predominant type of SDB remained unchanged (78.9% in obstructive sleep apnoea and 44.4% in central sleep apnoea). The only predictors of SDB at baseline were higher age and body mass index and in the chronic phase additionally baseline AHI. Baseline AHI was associated with functional outcome (modified Rankin score >3) at M3.

The high prevalence of SDB in acute stroke, its persistence after 3 months, and the association with functional outcome supports the recommendation for a rapid SDB screening in stroke patients.

The high prevalence of SDB in acute stroke, its persistence after 3 months and its association with functional outcome support the recommendation for rapid SDB screening in stroke patientshttps://bit.ly/3bFWqV7

Prediction of sleep-disordered breathing after stroke

OBJECTIVE/BACKGROUND

Sleep-disordered breathing (SDB) is highly prevalent after stroke and is associated with poor outcomes. Currently, after stroke, objective testing must be used to differentiate patients with and without SDB. Within a large, population-based study, we evaluated the usefulness of a flexible statistical model based on baseline characteristics to predict post-stroke SDB.

PATIENTS/METHODS

Within a population-based study, participants (2010-2018) underwent SDB screening, shortly after ischemic stroke, with a home sleep apnea test. The respiratory event index (REI) was calculated as the number of apneas and hypopneas per hour of recording; values ≥10 defined SDB. The distributed random forest classifier (a machine learning technique) was applied to predict SDB with the following as predictors: demographics, stroke risk factors, stroke severity (NIHSS), neck and waist circumference, palate position, and pre-stroke symptoms of snoring, apneas, and sleepiness.

RESULTS

Within the total sample (n = 1330), median age was 65 years; 47% were women; 32% non-Hispanic white, 62% Mexican American, and 6% African American. SDB was found in 891 (67%). The area under the receiver operating characteristic curve, a measure of predictive ability, applied to the validation sample was 0.75 for the random forest model. Random forest correctly classified 72.5% of validation samples.

CONCLUSIONS

In this large, ethnically diverse, population-based sample of ischemic stroke patients, prediction models based on baseline characteristics and clinical measures showed fair rather than clinically reliable performance, even with use of advanced machine learning techniques. Results suggest that objective tests are still needed to differentiate ischemic stroke patients with and without SDB.

Association Between Risk of Obstructive Sleep Apnea and Cerebrovascular Reactivity in Stroke Patients

Background Obstructive sleep apnea (OSA) is present in 60% to 70% of stroke patients. Cerebral vasoreactivity in patients with stroke and OSA has not been well studied and could identify a new pathophysiologic mechanism with potential therapeutic intervention. We aimed to determine whether risk categories for OSA are associated with cerebral vasoreactivity in stroke patients. Methods and Results In this cross-sectional study of a cohort of patients with stroke, we used clinical questionnaires (Sleep Obstructive Apnea Score Optimized for Stroke [SOS] and snoring, tiredness, observed, pressure, bmi, age, neck, gender [STOP-BANG] scores) to assess the risk of OSA and transcranial Doppler to assess cerebral vasoreactivity (breath-holding index and visual evoked flow velocity response). Of the 99 patients included, 77 (78%) had medium or high risk of OSA and 80 performed transcranial Doppler. Mean breath-holding index was 0.52±0.37, and median visual evoked flow velocity response was 10.8% (interquartile range: 8.8-14.5); 54 of 78 (69%) showed impaired anterior circulation vasoreactivity (breath-holding index <0.69) and 53 of 71 (75%) showed impaired posterior circulation vasoreactivity (visual evoked flow velocity response ≤14.0%). There was a significant negative correlation between the risk of OSA calculated by STOP-BANG and the breath-holding index (r_S=-0.284, P=0.012). The following variables were associated with low anterior circulation vasoreactivity: dyslipidemia (odds ratio: 4.7; 95% CI, 1.5-14.2) and STOP-BANG score (odds ratio: 1.7 per 1-point increase; 95% CI, 1.1-1.5). Conclusions A high risk of OSA and impaired vasoreactivity exists in the population that has had stroke. Dyslipidemia and STOP-BANG sleep apnea risk categories were independently associated with impaired anterior circulation vasoreactivity.

Guidelines for the Early Management of Patients With Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association

Background and Purpose- The purpose of these guidelines is to provide an up-to-date comprehensive set of recommendations in a single document for clinicians caring for adult patients with acute arterial ischemic stroke. The intended audiences are prehospital care providers, physicians, allied health professionals, and hospital administrators. These guidelines supersede the 2013 Acute Ischemic Stroke (AIS) Guidelines and are an update of the 2018 AIS Guidelines. Methods- Members of the writing group were appointed by the American Heart Association (AHA) Stroke Council's Scientific Statements Oversight Committee, representing various areas of medical expertise. Members were not allowed to participate in discussions or to vote on topics relevant to their relations with industry. An update of the 2013 AIS Guidelines was originally published in January 2018. This guideline was approved by the AHA Science Advisory and Coordinating Committee and the AHA Executive Committee. In April 2018, a revision to these guidelines, deleting some recommendations, was published online by the AHA. The writing group was asked review the original document and revise if appropriate. In June 2018, the writing group submitted a document with minor changes and with inclusion of important newly published randomized controlled trials with >100 participants and clinical outcomes at least 90 days after AIS. The document was sent to 14 peer reviewers. The writing group evaluated the peer reviewers' comments and revised when appropriate. The current final document was approved by all members of the writing group except when relationships with industry precluded members from voting and by the governing bodies of the AHA. These guidelines use the American College of Cardiology/AHA 2015 Class of Recommendations and Level of Evidence and the new AHA guidelines format. Results- These guidelines detail prehospital care, urgent and emergency evaluation and treatment with intravenous and intra-arterial therapies, and in-hospital management, including secondary prevention measures that are appropriately instituted within the first 2 weeks. The guidelines support the overarching concept of stroke systems of care in both the prehospital and hospital settings. Conclusions- These guidelines provide general recommendations based on the currently available evidence to guide clinicians caring for adult patients with acute arterial ischemic stroke. In many instances, however, only limited data exist demonstrating the urgent need for continued research on treatment of acute ischemic stroke.

The STOP-Bang and Berlin questionnaires to identify obstructive sleep apnoea in Alzheimer's disease patients

BACKGROUND

A close relationship between obstructive sleep apnoea (OSA) and Alzheimer's disease (AD) has been described in recent years. OSA is a risk factor for AD, but the diagnosis and clinical characteristics of OSA in patients with AD is not well understood. This study evaluated the clinical utility of two screening questionnaires, the STOP-Bang questionnaire (SBQ) and the Berlin questionnaire (BQ), to identify which patients with mild AD are at higher risk of having OSA and to determine the clinical predictors of OSA in this population.

METHODS

In this study, 91 consecutive outpatients with mild AD were prospectively evaluated with the SBQ and the BQ. All patients underwent level 1 in-laboratory polysomnography. The predictive performance of the questionnaires were calculated for different apnoea-hypopnoea index (AHI) cut-offs.

RESULTS

The median age of the patients was 76.0 (73.0; 80.0) years, and 58 (63.7%) were female. Of those, 81 patients (89.02%) were found to have OSA defined by an AHI > 5 events/h. Comparing the predictive performances of the SBQ and the BQ, the SBQ was found to have a higher diagnostic sensitivity (85% vs 4%), a lower specificity (35% vs. 96%), a higher positive predictive value (PPV) (44% vs 33%) and negative predictive value (NPV) (80% vs 65%) for detecting severe OSA at an AHI cut-off of 30 events/h. None of the items alone in the two questionnaires predicted the risk of OSA. A modified version of the SBQ, with new cut-off points for several variables according to the characteristics of AD patients, showed a slightly greater AUC than the standard SBQ (AUC 0.61 vs 0.72).

CONCLUSION

There is a high prevalence of OSA among patients with mild AD. The SBQ and the BQ are not good screening tools for detecting OSA in patients with AD. A modified version of SBQ could increase the detection of these patients.

Pre-screening of sleep-disordered breathing after stroke: A systematic review

OBJECTIVES

Sleep-Disordered Breathing (SDB) is frequent in stroke patients. Polysomnography (PSG) and cardiorespiratory polygraphy are used to confirm SDB, but the need for PSG exceeds the available resources for systematic testing. Therefore, a simple and robust pre-screening instrument is necessary to identify the patients with an urgent need for a targeted PSG. The aim of this systematic review was to identify and evaluate the available methods to pre-screen stroke patients possibly suffering from SDB.

MATERIALS AND METHODS

Eleven studies out of 3,561 studies met the inclusion criteria. The selected studies assessed the efficiency of seven instruments based on the data acquired clinically or by inquiries (Berlin Questionnaire, Epworth Sleepiness Scale, SOS, Modified Sleep Apnea Scale of the Sleep Disorders Questionnaire, STOP-BANG, Four-variable Screening Tool and Multivariate Apnea Index) and three physiological measures (capnography, nocturia, nocturnal oximetry). The instruments were used to predict SDB in patients after acute or subacute stroke. Either PSG or cardiorespiratory polygraphy was used as a standard to measure SDB.

RESULTS

No independent studies using the same questionnaires, methods or criteria were published reducing generalizability. Overall, the questionnaires were quite sensitive in finding SDB but not highly specific in identifying the non-affected. The physiological measures (capnography) indicated promising results in predicting SDB, but capnography is not an ideal pre-screening instrument as it requires a specialist to interpret the results.

CONCLUSIONS

The results of pre-screening of SDB in acute and subacute stroke patients are promising but inconsistent. The current pre-screening methods cannot readily be referred to clinicians in neurologic departments. Thus, it is necessary to conduct more research on developing novel pre-screening methods for detecting SDB after stroke.

Prolonged sleep increases the risk of intracerebral haemorrhage: a nationwide case-control study

BACKGROUND AND PURPOSE

Although abnormal sleep duration is positively associated with increased risk for cardiovascular disease and mortality, the specific impact on intracerebral haemorrhage (ICH) risk remains unclear. The relationship between sleep duration and the risk of ICH was investigated in our study.

METHODS

A nationwide, multicentre matched case-control study was performed to investigate the risk factors for haemorrhagic stroke, using patients from 33 hospitals in Korea. In all, 490 patients with ICH and 980 age- and sex-matched controls were enrolled. Detailed information regarding sleep, sociodemographic factors, lifestyle and medical history before ICH onset was obtained using qualified structured questionnaires. Sleep duration was categorized and the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using a conditional logistic regression with 7 h as the reference duration.

RESULTS

The number of subjects with long sleep duration, more than 8 h, was significantly greater in the ICH group than in the control group (≥8 h, 30.4% vs. 22.6%, P = 0.002). After controlling for relevant confounding factors, longer sleep duration was found to be independently associated with the risk of ICH in a dose-response manner (8 h, OR 1.57, 95% CI 1.00-2.47; ≥9 h, OR 5.00, 95% CI 2.18-11.47).

CONCLUSIONS

Our study suggested that long sleep duration is positively associated with an increased ICH risk in a dose-dependent manner. Further studies on the relationship linking long sleep duration with increased risk of ICH are required.

A screening tool for obstructive sleep apnea in cerebrovascular patients

BACKGROUND

A majority of stroke patients suffer from obstructive sleep apnea (OSA), which can go unrecognized as the current OSA screens do not perform well in stroke patients. The objective of this study is to modify the existing OSA screening tools for use in stroke patients.

METHODS

The cohort study consisted of patients who completed the validated OSA STOP screen and underwent polysomnography within one year. Six prediction models were created and sensitivity and specificity of various cut points were calculated.

RESULTS

There were 208 patients with mean age of 55.4 years; 61.0% had sleep apnea. Models with the highest c-statistics included the STOP items plus BMI, age, and sex (STOP-BAG). Addition of neck circumference and other variables did not significantly improve the models. The STOP-BAG2 model, using continuous variables, had a greater sensitivity of 0.94 (95% CI 0.89-0.98) and specificity 0.60 (95% CI 0.49-0.71) compared to the STOP-BAG model, which used dichotomous variables, and had a sensitivity of 0.91 (95% CI 0.85-0.96) and specificity of 0.48 (95% CI 0.37-0.60).

CONCLUSIONS

The STOP-BAG screen can be used to identify cerebrovascular patients at an increased risk of OSA. The use of continuous variables (STOP-BAG2) is preferable if automated score calculation is available. It can improve the efficiency of evaluation for OSA and lead to improved outcomes of patients with cerebrovascular disease.

Identifying obstructive sleep apnea after stroke/TIA: evaluating four simple screening tools

OBJECTIVE

Despite its high prevalence and unfavorable clinical consequences, obstructive sleep apnea (OSA) often remains underappreciated after cerebrovascular events. The purpose of our study was to evaluate the clinical utility of four simple paper-based screening tools for excluding OSA after stroke or transient ischemic attack (TIA).

PATIENTS/METHODS

Sixty-nine inpatients and outpatients with stroke or TIA during the past 180 days completed the 4-Variable screening tool (4V), STOP-BAG questionnaire (ie, STOP-BANG questionnaire without the neck circumference measurement), Berlin questionnaire, and the Sleep Obstructive apnea score optimized for Stroke (SOS). They subsequently underwent objective testing using a portable sleep monitoring device. Cutoffs were selected to maximize sensitivity and exclude OSA (AHI ≥ 10) in ≥10% of the cohort.

RESULTS

The mean age was 68.3 ± 14.2 years and 47.8% were male. Thirty-two patients (46.4%) were found to have OSA. Male sex, body mass index (BMI), and atrial fibrillation were independent predictors of OSA. Among the screening tools, the 4V had the greatest area under the curve (AUC) of 0.688 (p = 0.007); the sensitivity was 96.9% for a cutoff of <6. The STOP-BAG also significantly detected OSA with an AUC of 0.677 (p = 0.012); the sensitivity was 93.8% for a cutoff of <2. Scores on the 4V and STOP-BAG were significantly correlated with the AHI.

CONCLUSIONS

The 4V and STOP-BAG questionnaire may aid clinicians with ruling out OSA within 180 days of stroke/TIA. Due to the atypical presentation of poststroke/TIA OSA, these tools are only moderately predictive; objective testing should still be used for OSA diagnosis in this population.

Excessive Daytime Sleepiness in Stroke Survivors: An Integrative Review

Excessive daytime sleepiness (EDS) is a prevalent symptom among stroke survivors. This symptom is an independent risk factor for stroke and may reduce stroke survivors' quality of life, cognitive functioning, and daytime functional performance. The lack of a universally accepted definition of EDS makes it difficult to measure EDS and synthesize research. The purpose of this integrative review is to describe poststroke EDS, ascertain conceptual and operational definitions of EDS, identify factors that contribute to EDS in stroke survivors, and explore outcomes associated with EDS in stroke survivors. We searched the following databases: PubMed and MEDLINE (OvidSP 1946-April; Week 2, 2015), Embase (OvidSP 1974-March; Week 1, 2015), and PsycINFO (OvidSP 1967-April; Week 2, 2015). Our search yielded 340 articles, 27 of which met inclusion criteria. The literature reveals EDS to be a multidimensional construct that is operationalized with both subjective and objective measures. Choosing measures that can quantify both the objective and subjective components is useful for gaining a comprehensive understanding of EDS. The antecedents of EDS are stroke, sleep-disordered breathing, reversed Robin Hood syndrome, and depression. The outcomes associated with EDS in stroke patients are serious and negative. Via synthesis of this research, we propose a possible framework for poststroke EDS, which may be of use in clinical practice and in research to identify valid quantifying methods for EDS as well as to prevent harmful outcomes in stroke survivors.

Diagnostic Accuracy of Obstructive Airway Adult Test for Diagnosis of Obstructive Sleep Apnea

Rationale. The gold standard for the diagnosis of Obstructive Sleep Apnea (OSA) is polysomnography, whose access is however reduced by costs and limited availability, so that additional diagnostic tests are needed. Objectives. To analyze the diagnostic accuracy of the Obstructive Airway Adult Test (OAAT) compared to polysomnography for the diagnosis of OSA in adult patients. Methods. Ninety patients affected by OSA verified with polysomnography (AHI ≥ 5) and ten healthy patients, randomly selected, were included and all were interviewed by one blind examiner with OAAT questions. Measurements and Main Results. The Spearman rho, evaluated to measure the correlation between OAAT and polysomnography, was 0.72 (p < 0.01). The area under the ROC curve (95% CI) was the parameter to evaluate the accuracy of the OAAT: it was 0.91 (0.81–1.00) for the diagnosis of OSA (AHI ≥ 5), 0.90 (0.82–0.98) for moderate OSA (AHI ≥ 15), and 0.84 (0.76–0.92) for severe OSA (AHI ≥ 30). Conclusions. The OAAT has shown a high correlation with polysomnography and also a high diagnostic accuracy for the diagnosis of OSA. It has also been shown to be able to discriminate among the different degrees of severity of OSA. Additional large studies aiming to validate this questionnaire as a screening or diagnostic test are needed.