scholarly journals Concerns about the Validation of the Berlin Questionnaire and American Society of Anesthesiologist Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients

2009 ◽  
Vol 110 (1) ◽  
pp. 194-194 ◽  
Author(s):  
Jose Ramon Perez Valdivieso ◽  
Maira Bes-Rastrollo
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Screening Tools ◽  
Surgical Patients ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
American Society

scholarly journals Validation of the Berlin Questionnaire and American Society of Anesthesiologists Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients

2008 ◽  
Vol 108 (5) ◽  
pp. 822-830 ◽  
Author(s):  
Frances Chung ◽  
Balaji Yegneswaran ◽  
Pu Liao ◽  
Sharon A. Chung ◽  
Santhira Vairavanathan ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
High Risk ◽  
Screening Tools ◽  
Surgical Patients ◽  
Apnea Hypopnea Index ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
American Society ◽  
American Society Of Anesthesiologists ◽  
Stop Questionnaire

Background Because of the high prevalence of obstructive sleep apnea (OSA) and its adverse impact on perioperative outcome, a practical screening tool for surgical patients is required. This study was conducted to validate the Berlin questionnaire and the American Society of Anesthesiologists (ASA) checklist in surgical patients and to compare them with the STOP questionnaire. Methods After hospital ethics approval, preoperative patients aged 18 yr or older and without previously diagnosed OSA were recruited. The scores from the Berlin questionnaire, ASA checklist, and STOP questionnaire were evaluated versus the apnea-hypopnea index from in-laboratory polysomnography. The perioperative data were collected through chart review. Results Of 2,467 screened patients, 33, 27, and 28% were respectively classified as being at high risk of OSA by the Berlin questionnaire, ASA checklist, and STOP questionnaire. The performance of the screening tools was evaluated in 177 patients who underwent polysomnography. The sensitivities of the Berlin questionnaire, ASA checklist, and STOP questionnaire were 68.9-87.2, 72.1-87.2, and 65.6-79.5% at different apnea-hypopnea index cutoffs. There was no significant difference between the three screening tools in the predictive parameters. The patients with an apnea-hypopnea index greater than 5 and the patients identified as being at high risk of OSA by the STOP questionnaire or ASA checklist had a significantly increased incidence of postoperative complications. Conclusions Similar to the STOP questionnaire, the Berlin questionnaire and ASA checklist demonstrated a moderately high level of sensitivity for OSA screening. The STOP questionnaire and the ASA checklist were able to identify the patients who were likely to develop postoperative complications.

scholarly journals Usefulness of different screening questionnaires and scoring systems for obstructive sleep apnea in patients with atrial fibrillation

EP Europace ◽  
2021 ◽  
Vol 23 (Supplement_3) ◽  
Author(s):  
M Delesie ◽  
L Knaepen ◽  
A Wouters ◽  
A De Cauwer ◽  
A De Roy ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Gold Standard ◽  
Scoring Systems ◽  
Public Institution ◽  
Screening Tools ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
Screening Questionnaires

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This study is part of Limburg Clinical Research Center, supported by the foundation Limburg Sterk Merk, province of Limburg, Flemish government, Hasselt University, Ziekenhuis Oost-Limburg and Jessa Hospital. OnBehalf Research Group Cardiovascular Diseases, University of Antwerp Background Obstructive sleep apnea (OSA) influences the progression of atrial fibrillation (AF) but is underdiagnosed in this population. Studies have shown that its treatment can help to reduce AF recurrences and improve symptoms. Polysomnography (PSG) is currently the gold standard for diagnosing OSA but being expensive and requiring overnight examination it is therefore not the ideal screening method. Different OSA screening tools such as questionnaires and scoring systems already exist but their value in AF patients remains unclear. Purpose The aim of this study was to examine the performance of different screening questionnaires and scoring systems for diagnosing OSA in an AF cohort, compared with PSG as gold standard. Methods Prospective study of the predictive performance of seven screening questionnaires and scoring systems (the Epworth Sleepiness Scale (ESS), the Berlin Questionnaire (BQ), Sleep Apnea Clinical Score (SACS), OSA50, STOP-BANG, NoSAS, MOODS) in consecutive AF patients referred to two sleep clinics. Results A total of 100 AF patients presenting for PSG were included (64.0 ± 8.6 years, 73% male, 87% non-permanent AF, mean Body Mass Index 30.6 ± 5.9 kg/m2, mean CHA2DS2-VASc score 2.4 ± 1.7, mEHRA≥2 in 64%; mean AF history 5.4 ± 5.6 years).  Forty-two percent of patients were referred to the sleep clinic by cardiologists. PSG diagnosed ≥mild OSA in 90% of patients, ≥moderate in 69%, and severe OSA in 33%. In screening for mild OSA, NoSAS, STOP-BANG and MOODS screening questionnaires had a fair area under the curve (AUC) of 0.773, 0.710 and 0.709 respectively. For at least moderate OSA, only the SACS and the NoSAS questionnaires had an AUC of 0.704 and 0.712 respectively (Figure 1). None of the seven screening questionnaires/scoring systems were performant enough (i.e. a fair AUC > 0.7) to detect severe OSA. Conclusions Our analysis shows that screening questionnaires and scoring systems such as ESS, BQ, SACS, NoSAS, OSA50, STOP-BANG and MOODS are not very useful to predict clinically relevant OSA (i.e. at least moderate OSA) in AF patients. Therefore, other screening modalities for OSA in AF patients should be investigated and validated. Abstract Figure 1

Abstract W P224: SOS Score: an Optimized Score to Screen Acute Stroke Patients for Obstructive Sleep Apnea

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Millene R Camilo ◽  
Heidi H Sander ◽  
Alan L Eckeli ◽  
Regina M Fernandes ◽  
Taiza E Santos-Pontelli ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Ischemic Stroke ◽  
Sleep Apnea ◽  
Acute Stroke ◽  
Predictive Value ◽  
Screening Tools ◽  
Berlin Questionnaire ◽  
Stroke Patients ◽  
Obstructive Sleep ◽  
The Mean

Background: Obstructive sleep apnea (OSA) is frequent in acute stroke patients and is associated with increased mortality and poor functional outcome. Polysomnography (PSG) is the gold standard diagnostic method for OSA, but it is impracticable as a routine for all acute stroke patients. We evaluated how OSA screening tools such as the Berlin Questionnaire (BQ) and the Epworth Sleepiness Scale (ESS) would perform when administered to relatives of stroke patients in the acute setting, and compared these individual tools against a combined screening score (SOS score). Methods: Ischemic stroke patients were submitted to a full PSG at the first night after symptoms onset. OSA severity was measured by apnea-hypopnea index (AHI). BQ and ESS were administered to relatives of stroke patients before the PSG. We combined elements of the BQ and ESS to create a new screening tool for OSA named Sleep Obstructive apnea score optimized for Stroke (SOS score). Results: Thirty-nine consecutives ischemic stroke patients were enrolled in our study. The mean age was 62.3 ±12.2 years. Age was significantly different between those with and without OSA (p=0.02). The mean body mass index and neck circumference were 26.7 ± 4.7 and 38.9 ± 4.0cm, respectively. OSA (AHI ≥ 10) was present in 76.9%. The area under the curve for SOS score (AUC:0.812; p=0.005) was superior to BQ (AUC:0.567; p=0.549) and also to ESS (AUC:0.646; p=0.119 vs. AUC:0.686; p=0.048) for severe OSA (IAH ≥ 30). The threshold of SOS ≤ 10 (present in 20.5% of patients) showed high sensitivity (90%) and negative predictive value (96.2%) for OSA; SOS ≥20 (17.9% of patients) showed high specificity (100%) and positive predictive value (92.5%) for severe OSA. Using SOS as a screening approach would decrease by around 40% the demand for PSG during the acute stroke setting. Conclusions: The SOS score when administered to relatives of stroke patients appears to be an appropriate tool to screen acute stroke patients for OSA, while decreasing the need for a formal sleep study during the acute stroke setting. The new derived SOS score is superior to BQ and ESS for identifying patients with OSA and Severe OSA during the acute phase of stroke.

Abstract 41: Stroke Unit Evaluation of Sleep Apnea: Validity of Screening Tools and Use of a Portable Sleep Study

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Hugo J Aparicio ◽  
Tudor Sturzoiu ◽  
Helena W Lau ◽  
Judith Clark ◽  
Julie Grimes ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Stroke Unit ◽  
Central Sleep Apnea ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Berlin Questionnaire ◽  
Validity And Reliability ◽  
Sleep Study ◽  
Obstructive Sleep

Background: Despite high prevalence in the stroke population, sleep apnea is underdiagnosed. Obstructive sleep apnea is associated with poor cardiovascular outcomes and treatment with continuous positive airway pressure has been shown to lower blood pressure. No standard exists for screening patients who present to the hospital with acute stroke. We assessed three screening tools, the Epworth Sleepiness Scale (ESS), Berlin Questionnaire (BQ), and STOP-BANG Questionnaire (STOP-BANG), along with the use of a portable sleep study device for evaluation of sleep apnea. Overnight polysomnography (PSG) was performed on a subset of patients on outpatient follow up. Methods: Patients admitted to the stroke unit at our hospital, over nine months, were screened for sleep apnea using the three instruments, ESS, BQ, and STOP-BANG. The patients were evaluated with a portable sleep study device, ApneaLink Air (ResMed, USA), prior to discharge. Respiratory effort, respiratory flow, pulse oximetry, and oxygen saturation were recorded and sleep apnea was determined by apnea-hypopnea index (AHI) ≥ 5. Predictions from the screening tools were compared to the portable sleep study and overnight PSG results. Sensitivity and specificity testing were used to assess the validity and reliability of the tools. Results: Sleep questionnaires were administered on 37 patients who underwent an overnight sleep study. Portable studies were used to evaluate 33 patients, and 13 PSGs were performed. Obstructive sleep apnea was diagnosed in 20 (69%) and central sleep apnea in 9 (31%). Cheyne-Stokes pattern breathing was observed in 2 (5%). Mean AHI was 18.3 + 21.8/hr and maximum AHI was 105.8/hr. Sensitivity for the ESS, BQ, and STOP-BANG were 0.39, 0.66, and 0.83 and specificity for these tools were 0.26, 0.33, and 0.29, respectively. In patients who underwent the portable sleep study and overnight PSG, 9/10 (90%) of the studies were concordant. Conclusions: The STOP-BANG questionnaire, administered to hospitalized stroke patients, had high sensitivity and low-moderate specificity in our study, compared to two other commonly used screening tools. Further, the feasibility of using an unattended inpatient portable sleep study on stroke inpatients is demonstrated.

Association between obstructive sleep apnea and persistent-postural perceptual dizziness

2021 ◽  
pp. 1-6
Author(s):  
Anand K. Bery ◽  
Jayson Lee Azzi ◽  
Andre Le ◽  
Naomi S. Spitale ◽  
Judith Leech ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sensitivity And Specificity ◽  
Berlin Questionnaire ◽  
Future Studies ◽  
Obstructive Sleep ◽  
Chronic Dizziness ◽  
Patients At Risk ◽  
The Mean ◽  
The Relationship

BACKGROUND: Obstructive sleep apnea (OSA) has been linked to vestibular dysfunction, but no prior studies have investigated the relationship between Persistent Postural Perceptual Dizziness (PPPD), a common cause of chronic dizziness, and OSA. OBJECTIVE AND METHODS: We determined the frequency of OSA in an uncontrolled group of PPPD patients from a tertiary dizziness clinic based on polysomnogram (PSG). We then assessed the sensitivity and specificity of common OSA questionnaires in this population. RESULTS: Twenty-five patients with PPPD underwent PSG (mean age 47, 60% female, mean BMI 29.5). A majority, or 56%, of patients were diagnosed with OSA, and in most, the OSA was severe. OSA patients were older (56 years versus 40 years, p = 0.0006) and had higher BMI (32 versus 26, p = 0.0078), but there was no clear gender bias (56% versus 64% female, p = 1.00). The mean sensitivity and specificity of the STOP BANG questionnaire for detecting OSA was 86% and 55%, respectively. Sensitivity and specificity of the Berlin Questionnaire was 79% and 45%, respectively. CONCLUSIONS: The prevalence of OSA was much higher in our small PPPD group than in the general population. Screening questionnaires appear to demonstrate good sensitivity to detect PPPD patients at risk of OSA in this small study. Future studies should confirm these findings and determine whether treatment of OSA improves symptoms in PPPD.

419 STOP-Bang Score and History of Radiation Predicts Risk of Obstructive Sleep Apnea in Cancer Patients: A Machine Learning Study

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A166-A166
Author(s):  
Ankita Paul ◽  
Karen Wong ◽  
Anup Das ◽  
Diane Lim ◽  
Miranda Tan
Keyword(s):  
Machine Learning ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Cancer Patients ◽  
Prediction Accuracy ◽  
Screening Tools ◽  
Cancer Type ◽  
Sleep Study ◽  
Obstructive Sleep ◽  
History Of

Abstract Introduction Cancer patients are at an increased risk of moderate-to-severe obstructive sleep apnea (OSA). The STOP-Bang score is a commonly used screening questionnaire to assess risk of OSA in the general population. We hypothesize that cancer-relevant features, like radiation therapy (RT), may be used to determine the risk of OSA in cancer patients. Machine learning (ML) with non-parametric regression is applied to increase the prediction accuracy of OSA risk. Methods Ten features namely STOP-Bang score, history of RT to the head/neck/thorax, cancer type, cancer stage, metastasis, hypertension, diabetes, asthma, COPD, and chronic kidney disease were extracted from a database of cancer patients with a sleep study. The ML technique, K-Nearest-Neighbor (KNN), with a range of k values (5 to 20), was chosen because, unlike Logistic Regression (LR), KNN is not presumptive of data distribution and mapping function, and supports non-linear relationships among features. A correlation heatmap was computed to identify features having high correlation with OSA. Principal Component Analysis (PCA) was performed on the correlated features and then KNN was applied on the components to predict the risk of OSA. Receiver Operating Characteristic (ROC) - Area Under Curve (AUC) and Precision-Recall curves were computed to compare and validate performance for different test sets and majority class scenarios. Results In our cohort of 174 cancer patients, the accuracy in determining OSA among cancer patients using STOP-Bang score was 82.3% (LR) and 90.69% (KNN) but reduced to 89.9% in KNN using all 10 features mentioned above. PCA + KNN application using STOP-Bang score and RT as features, increased prediction accuracy to 94.1%. We validated our ML approach using a separate cohort of 20 cancer patients; the accuracies in OSA prediction were 85.57% (LR), 91.1% (KNN), and 92.8% (PCA + KNN). Conclusion STOP-Bang score and history of RT can be useful to predict risk of OSA in cancer patients with the PCA + KNN approach. This ML technique can refine screening tools to improve prediction accuracy of OSA in cancer patients. Larger studies investigating additional features using ML may improve OSA screening accuracy in various populations Support (if any):

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