Sleep Apnea Clinical Score Research Articles

Comparison between the Risk of Developing Sleep Disorders with Lung Mechanics and Thoracic Ultrasound Signals in Adults with Obesity

Abstract Objective The present study aimed to compare the risk of developing sleep disorders with abnormalities in lung mechanics, abnormal ultrasound signals, and anthropometric parameters in adults with obesity. Materials and Methods A total of 50 individuals were assessed for the risk of obstructive sleep apnea (OSA) using the Mallampati classification, the Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed Apnea, High Blood Pressure, Body Mass Index, Age, Neck Circumference, and Gender (STOP-Bang) questionnaire, and the Sleep Apnea Clinical Score (SACS). Patients also underwent respiratory oscillometry, spirometry, and thoracic ultrasound. Results The subgroup with abnormal respiratory oscillometry was more likely to have an ESS score indicating a high risk of developing OSA (87.5%) than the subgroup with normal respiratory oscillometry (42.9%) (p = 0.024). On thoracic ultrasound, the frequency of patients with a Mallampati classification of high risk of developing OSA was greater in the subgroup with > 2 B-lines (80%) than in the subgroup with ≤ 2 B-lines (25.7%) (p = 0.0003). The subgroup with subpleural consolidations was more likely to have an OSA-indicative ESS score (100%) than the subgroup without subpleural consolidations (41.9%) (p = 0.004). According to the multivariate analysis, > 2 B lines and body mass index were found to be independent variables for predicting the Mallampati classification, while subpleural consolidation was the only independent variable for predicting the ESS score. Conclusion In adults with obesity, the greater the risk of developing OSA was, the worse the resistive and reactive parameters measured by respiratory oscillometry. Abnormal respiratory oscillometry and abnormal thoracic ultrasound are factors associated with a high risk of developing OSA.

A risk-predictive model for obstructive sleep apnea in patients with chronic obstructive pulmonary disease.

Obstructive sleep apnea syndrome (OSA) is increasingly reported in patients with chronic obstructive pulmonary disease (COPD). Our research aimed to analyze the clinical characteristics of patients with overlap syndrome (OS) and develop a nomogram for predicting OSA in patients with COPD. We retroactively collected data on 330 patients with COPD treated at Wuhan Union Hospital (Wuhan, China) from March 2017 to March 2022. Multivariate logistic regression was used to select predictors applied to develop a simple nomogram. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the value of the model. A total of 330 consecutive patients with COPD were enrolled in this study, with 96 patients (29.1%) confirmed with OSA. Patients were randomly divided into the training group (70%, n = 230) and the validation group (30%, n = 100). Age [odds ratio (OR): 1.062, 1.003-1.124], type 2 diabetes (OR: 3.166, 1.263-7.939), neck circumference (NC) (OR: 1.370, 1.098-1,709), modified Medical Research Council (mMRC) dyspnea scale (OR: 0.503, 0.325-0.777), Sleep Apnea Clinical Score (SACS) (OR: 1.083, 1.004-1.168), and C-reactive protein (CRP) (OR: 0.977, 0.962-0.993) were identified as valuable predictors used for developing a nomogram. The prediction model performed good discrimination [AUC: 0.928, 95% confidence interval (CI): 0.873-0.984] and calibration in the validation group. The DCA showed excellent clinical practicability. We established a concise and practical nomogram that will benefit the advanced diagnosis of OSA in patients with COPD.

The value of screening questionnaires/scoring scales for obstructive sleep apnoea in patients with atrial fibrillation

Obstructive sleep apnoea (OSA) is an important modifiable risk factor for atrial fibrillation (AF) but is underdiagnosed in this population. Currently, polysomnography is the gold standard for diagnosing OSA, but is expensive and requires overnight examination. Alternatively, home sleep apnoea testing can be used as a diagnostic tool, but also requires a complete data review. Therefore, these OSA diagnostic modalities are not ideal screening methods. Several OSA screening tools exist, but their value in patients with AF remains unclear. To test the performance of existing screening questionnaires/scales for clinically relevant OSA in patients with AF referred for diagnostic polysomnography. This prospective study compared the performance of seven screening tools (Epworth Sleepiness Scale, Berlin Questionnaire, Sleep Apnea Clinical Score, NoSAS, OSA50, STOP-Bang and MOODS) with polysomnography in the detection of clinically relevant OSA in consecutive patients with AF referred to two sleep clinics. A total of 100 patients referred for polysomnography and known previous AF were included. Polysomnography indicated at least clinically relevant OSA (i.e., apnoea-hypopnoea index≥15 events/hour) in 69% of cases, and 33% had severe OSA (apnoea-hypopnoea index>30 events/hour). In screening for clinically relevant OSA, only the SACS and NoSAS scores had fair areas under the curve (0.704 and 0.712, respectively). None of the seven screening tools was performant enough (i.e., had a fair area under the curve>0.7) in the detection of severe OSA. In this AF cohort referred for polysomnography, clinically relevant OSA was prevalent. None of the selected screening tools showed sufficient performance as a good discriminative screening tool for clinically relevant OSA in patients with AF. Given these findings, other screening modalities for OSA should be considered in the work-up of patients with AF.

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

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

PRESHYON: THE PREVALENCE ON THE RISK OF OSA AMONG PATIENTS WITH UNCONTROLLED HYPERTENSION SEEN AT THE OUT-PATIENT DEPARTMENT OF THE UNIVERSITY OF THE PHILIPPINES, PHILIPPINE GENERAL HOSPITAL

SESSION TITLE: Sleep Disorders Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: To determine the prevalence of the risk of Obstructive Sleep Apnea among patients with uncontrolled Hypertension (HTN) seen at the Out-Patient Department of the University of the Philippines-Philippine General Hospital METHODS: This is a cross-sectional study that enrolled 325 adult Filipino HTN patients seen at the outpatient department (OPD) of UP-PGH from January 2019 to July 2019. Participants also answered Berlin Questionnaire (BQ), Epworth Sleepiness Scale (ESS) and the St. Lukes Medical Center-Obstructive Sleep Apnea Clinical Score (SLMC-OSACS) for their OSA risk. Descriptive statistics were used to summarize the clinical characteristics of the patients. A chi-square test was used to analyze categorical data univariately. Logistics regression analysis was used to determine the association of the different independent variables with the outcome (dependent) variable. RESULTS: The risk of OSA was significantly high among uncontrolled HTN patients: 106 (60.7%) based on BQ (p<0.0001) and 68 (69.4%) based on SLMC-OSACS (p<0.0001). OSA risk among uncontrolled HTN was 6x higher (OR=5.69; 95% CI=3.49–9.28;p<0.0001) using the BQ and 4x higher (OR=3.70; 95% CI=2.19 – 6.26;p=<0.0001) using the SLMC-OSACS than those with controlled HTN. Daytime excessive sleepiness was not significantly associated. Other variables significantly associated with high risk OSA were BMI and other comorbidities. CONCLUSIONS: Among patients with hypertension, the risk of OSA based on the Berlin Questionnaire and SLMC-OSACS was significantly high among uncontrolled hypertension patients than those with controlled hypertension. Daytime excessive sleepiness noted with the ESS was not significantly associated with uncontrolled hypertension. Other demographic and clinical profile that were significantly associated with high risk OSA were BMI and other comorbidities (such as bronchial asthma, congestive heart failure) based on the SLMC-OSACS. CLINICAL IMPLICATIONS: Utilizing these sleep questionnaires and determining the risk for OSA among patients with uncontrolled hypertension will lead to early evaluation of OSA and complications. Locally this will aid in improving detection and provide more strategic management of uncontrolled hypertension to decrease associated cardiovascular events. This will guide our clinicians to prioritize patients who would benefit referral to sleep specialists DISCLOSURES: No relevant relationships by Jamie Chua, source=Web Response No relevant relationships by Angelica cruz, source=Web Response No relevant relationships by Maria Lowella De Leon, source=Web Response no disclosure on file for Manuel Jorge; No relevant relationships by Anna Katrina Tojino, source=Web Response

Obstructive Sleep Apnea Increases the Prevalence of Hypertension in Patients with Chronic Obstructive Disease

Whether there are increased rates of chronic diseases associated with the combination of chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA) overlap syndrome (OVS) has not been determined. The purpose of this study was to assess the prevalence of five comorbidities in COPD and OVS patients. A total of 968 patients with confirmed COPD were included in this study. Participants were requested to fill out a questionnaire involving their basic information and medical history. All subjects underwent one overnight polysomnography and were then divided into an OVS group or a COPD only group according to their apnea–hypopnea index. The prevalence of hypertension, diabetes, cardiovascular disease, arrhythmia and cerebrovascular disease were compared and risk factors for comorbidities in COPD patients were identified. Compared with the COPD only group, the prevalence of hypertension was significantly higher in the OVS group, however, the prevalence rates of the other four kinds of diseases were not statistically different between the two groups. In COPD patients, the prevalence of hypertension increased with the severity of OSA and the prevalence of arrhythmia increased with airflow limitation severity. Risk factors for OSA in patients with COPD included BMI, FEV1%, Epworth Sleepiness Scale score and the Sleep Apnea Clinical Score. OSA was an independent risk factor for hypertension. The other risk factors for hypertension in COPD patients included age, BMI, CAT score and alcohol consumption. Age, lower FEV1% may be risk factors for arrhythmia. OVS patients were associated with a high prevalence rate of hypertension, while OSA was an independent risk factor for hypertension.

Hospital screening for obstructive sleep apnea in patients admitted to a rural, tertiary care academic hospital with heart failure

ABSTRACT Background Rural communities represent a vulnerable population that would significantly benefit from hospital-based OSA screening given these areas tend to have significant health-care disparities and poor health outcomes. Although inpatient screening has been studied at urban hospitals, no study to date has assessed this approach in rural populations. Methods This study utilized the Electronic Medical Record (EMR) to generate a list of potential candidates by employing inclusion/exclusion criteria as screening. Subjects identified were then approached and offered information regarding the study. Screening for OSA entailed a tiered approach utilizing the sleep apnea clinical score (SAC) and portable sleep testing. Individuals identified as high risk (SAC ≥ 15) for OSA underwent evaluation with a portable sleep testing system while hospitalized. All participants with an apnea-hypopnea index (AHI) ≥5 events/h confirmed by a sleep medicine physician were considered screen positive for OSA. If approved/available, subjects screening positive for OSA were provided with an auto-titrating continuous positive airway pressure (PAP). Patient characteristics were analyzed using descriptive statistics. Categorical data were described using contingency tables, including counts and percentages. Continuously scaled measures were summarized by median with range. This study was registered with ClinicalTrials.gov. Identifier: NCT03056443. Results Nine hundred and fifty-eight potential subjects were identified. The three most common reasons for exclusion included previous OSA diagnosis or exposure to PAP therapy (n = 357), advanced illness (n = 380), and declined participation by the individual (n = 68). The remaining 31 subjects underwent further evaluation for obstructive sleep apnea. Twenty-three subjects had a high sleep apnea clinic score. Per our study protocol, 13 subjects who screened positive for OSA were initiated on APAP therapy. Conclusion: Our study provides important insight into the burden of sleep-disordered breathing (SDB) and unique challenges of hospital-based OSA screening/treatment in a rural setting. Our study identified barriers to successful screening in a rural population that may be well addressed by adapting previous research in hospital sleep medicine.

A study of glycemic variability in patients with type 2 diabetes mellitus with obstructive sleep apnea syndrome using a continuous glucose monitoring system

BackgroundObstructive sleep apnea syndrome (OSAS) in association with Type 2 Diabetes Mellitus (DM) may result in increased glycemic variability affecting the glycemic control and hence increasing the risk of complications associated with diabetes. We decided to assess the Glycemic Variability (GV) in patients with type 2 diabetes with OSAS and in controls. We also correlated the respiratory disturbance indices with glycemic variability indices.MethodsAfter fulfilling the inclusion and exclusion criteria patients from the Endocrinology and Pulmonology clinics underwent modified Sleep Apnea Clinical Score (SACS) followed by polysomnography (PSG). Patients were then divided into 4 groups: Group A (DM with OSAS, n = 20), Group B (DM without OSAS, n = 20), Group C (Non DM with OSAS, n = 10) and Group D (Non DM without OSAS, n = 10). Patients in these groups were subjected to continuous glucose monitoring using the Medtronic iPro2 and repeat PSG. Parameters of GV: i.e. mean glucose, SD (standard Deviation), CV (Coefficient of Variation), Night SD, Night CV, MAGE and NMAGE were calculated using the Easy GV software. GV parameters and the respiratory indices were correlated statistically. Quantitative data was expressed as mean, standard deviation and median. The comparison of GV indices between different groups was performed by one-way analysis of variance (ANOVA) or Kruskal Wallis (for data that failed normality). Correlation analysis of AHI with GV parameters was done by Pearson correlation.ResultsAll the four groups were adequately matched for age, sex, Body Mass Index (BMI), waist circumference (WC) and blood pressure (BP). We found that the GV parameters Night CV, MAGE and NMAGE were significantly higher in Group A as compared to Group B (p values < 0.05). Similarly Night CV, MAGE and NMAGE were also significantly higher in Group C as compared to Group D (p value < 0.05). Apnea-hypopnea index (AHI) correlated positively with Glucose SD, MAGE and NMAGE in both diabetes (Group A plus Group B) and non- diabetes groups (Group C plus Group D).ConclusionsOSAS has a significant impact on the glycemic variability irrespective of glycemic status. AHI has moderate positive correlation with the glycemic variability.

0725 PRESHYON: The Prevalence On The Risk Of Obstructive Sleep Apnea Among Patients With Uncontrolled Hypertension Seen At The Out-Patient Department Of The University Of The Philippines- Philippine General Hospital

Abstract Introduction Obstructive Sleep Apnea (OSA) is a breathing disorder linked to increased morbidity and mortality, 1 and associated with decreased quality of life and functional impairment of daily living.2 OSA has been established to be associated with hypertension wherein the prevalence of OSA is 30%, 24,25 however, local prevalence has been lacking. The gold standard for OSA is polysomnography but this is expensive and has limited availability. Questionnaires provide risk stratification to determine if the patient needs further sleep evaluation. Recognition and treatment of OSA could lead to improving long term outcomes of patients with uncontrolled hypertension. 31-33 Methods This is a cross-sectional study that enrolled 325 adult Filipino HTN patients seen at the outpatient department (OPD) of UP-PGH from January 2019 to July 2019. Participants also answered Berlin Questionnaire (BQ), Epworth Sleepiness Scale (ESS) and the St. Lukes Medical Center-Obstructive Sleep Apnea Clinical Score (SLMC-OSACS) for their OSA risk. Descriptive statistics were used to summarize the clinical characteristics of the patients. Chi-square test was used to analyze categorical data univariately. Logistics regression analysis was used to determine the association of the different independent variable with the outcome (dependent) variable. Results The risk of OSA was significantly high among uncontrolled HTN patients: 106 (60.7%) based on BQ (p&amp;lt;0.0001) and 68 (69.4%) based on SLMC-OSACS (p&amp;lt;0.0001). OSA risk among uncontrolled HTN was 6x higher (OR=5.69; 95% CI=3.49-9.28;p&amp;lt;0.0001) using the BQ and 4x higher (OR=3.70; 95% CI=2.19 - 6.26;p=&amp;lt;0.0001) using the SLMC-OSACS than those with controlled HTN. Other variables significantly associated with high risk OSA were BMI and other comorbidities. Conclusion The risk of OSA was significantly high among uncontrolled HTN patients. In utilizing these sleep questionnaires and determining the risk for OSA among patients with uncontrolled hypertension will lead for early evaluation of OSA and complications. Locally this will aid in improving detection and provide a more strategic management of uncontrolled hypertension to decrease associated cardiovascular events. This will guide our clinicians to prioritize patients who would benefit referral to sleep specialists Support

Is OSA risk proportional to BMI or parentally mediated? A questionnaire-based study in a cohort of Egyptian children

IntroductionThere is an increased body of evidence that Obstructive Sleep apnea (OSA) in obese patients has familial tendencies. This familial predilection might be mediated through tendencies to atopy with subsequent nasal obstruction, tendencies to adenotonsillar enlargement by fat deposition, or through differential fatty deposits in the airway. The aim of this study was to study if paternal or maternal OSA might be predictive of OSA in offspring and to determine the relationship of OSA to Body Mass Index (BMI), gender, and waist circumference (WC). Methods100 obese patients retrieved from a consortium of Egyptian Schools were screened and their parents using sleep apnea clinical score (SACS), their gender, BMI, and WC were noted. For the performance of Receiver Operating Characteristic study, obese children were divided according to their SACS into high risk (1) (SACS>75) and low risk (0) (SACS≤75). The sensitivity of each of BMI, WC, gender, paternal and maternal SACS as predictors of OSA high risk was determined. Results: Paternal OSA risk was the single significant predictor of OSA risk in obese children (Sensitivity: 89%, Specificity: 97%), WC was the second-best predictor (Sensitivity: 78%, Specificity: 89%), female offsprings were at higher risk to be involved, BMI was a weak predictor of OSA risk with a cut off>34. Finally, yet importantly, maternal OSA risk was unrelated to OSA risk in obese children. ConclusionThis study confirms that genetic factors might play a much more important role than the degree of obesity in determining OSA risk in obese patients, these findings open the door to more in-depth studies to understand the genetic mechanisms involved in such a relationship.

Translation and cultural adaptation of the Sleep Apnea Clinical Score for use in Brazil.

ABSTRACTObjective:To translate the Sleep Apnea Clinical Score (SACS) into Brazilian Portuguese and adapt it to the cultural setting, validating it for use as a screening method for polysomnography and as a tool to quantify the risk of obstructive sleep apnea syndrome in individuals in Brazil. Methods:The translation was performed by two professionals, with subsequent synthesis of the translations. From that version, a back-translation was prepared, revised, and compared with the original by a team of experts. As a pre-test, a consensus version was applied in 20 patients randomly selected from among those under treatment at outpatient clinics at the Piquet Carneiro Polyclinic of the State University of Rio de Janeiro, in the city of Rio de Janeiro, to assess their understanding of the questions. In the validation phase, the Brazilian-Portuguese version of the SACS was applied in 86 patients who subsequently underwent polysomnography, regardless of the SACS result. Results:The analyses of the pre-test phase showed that the SACS was easily understood by the patients. In the validation phase, the SACS showed a sensitivity of 45.3% (95% CI: 32.8-58.2%), a specificity of 90.9% (95% CI: 70.8-98.9%), a positive predictive value of 93.5% (95% CI: 79.0-98.2%), a negative predictive value of 36.4% (95% CI: 30.6-42.5%), and an accuracy of 57.0% (95% CI: 45.8-67.6%). Conclusions:The Brazilian-Portuguese version of the SACS can be used in order to assess the risk of obstructive sleep apnea syndrome.

The Screening Value Of ESS, SACS, BQ, And SBQ On Obstructive Sleep Apnea In Patients With Chronic Obstructive Pulmonary Disease.

ObjectiveTo compare the performance of Epworth sleepiness scale (ESS), sleep apnea clinical score (SACS), Berlin questionnaire (BQ), and STOP-BANG questionnaire (SBQ) in screening for obstructive sleep apnea (OSA) in patients with chronic obstructive pulmonary disease (COPD).MethodsA total of 431 patients were analyzed. All subjects completed lung function test, ESS, SACS, BQ, and SBQ survey and overnight polysomnography (PSG). According to lung function and PSG results, participants were divided into COPD with OSA group (OVS, AHI ≥5) and without OSA group (AHI <5). The value of ESS, SACS, BQ, and SBQ was compared in predicting OSA in patients with COPD by receiver-operating characteristic (ROC) curve statistics.ResultsOf the 431 subjects, there were 96 cases in COPD without OSA group, and 335 cases in OVS group including 183, 96, and 56 cases of COPD combined with mild, moderate or severe OSA. In predicting different degrees of severity of OSA in patients with COPD, the value of ESS was poor with all the values of area under the curve (AUC) < 0.7. SACS and BQ had moderate predictive value in screening for severe OSA with the value of AUC of 0.750, 0.735 respectively. However, the SBQ performed best in predicting various degrees of OSA. For screening mild OSA (AHI ≥5), the ROC statistics recommended the cut-off score of SBQ >2 was considered high risk of OSA; the sensitivity, specificity, and AUC were 92.8%, 40.6%, and 0.723 respectively, the odds ratio (OR) was 2.161. When AHI ≥15, AUC for SBQ was 0.737. In predicting severe OSA (AHI ≥30), the ROC curve showed cut-off point, sensitivity, specificity, and AUC for SBQ was >4, 66.1%, 82.1%, and 0.824 respectively; the positive and negative likelihood ratio was 3.70, 0.41 separately, the OR was 2.977.ConclusionSBQ performed better than ESS, SACS, and BQ in predicting OSA in patients with COPD.

Nutrigenetic genotyping study in relation to Sleep Apnea Clinical Score.

Conflicting results regarding associations between single nucleotide polymorphisms (SNPs) in IRS1, ACE, APOE, PPARG, MTHFR, 5HT2AR, BDNF, and FTO genes and obstructive sleep apnea have been reported in previous studies. To assess pleiotropic associations between these gene polymorphisms that are commonly being studied in a nutrigenetic test and sleep apnea. One hundred and nine subjects of Caucasian origin who have performed a commercially available nutrigenetic test that includes the aforementioned polymorphisms were divided into two groups depending on the results of their Sleep Apnea Clinical Score (SACS ≤ 15 or > 15). Statistical significant differences in the prevalence of the polymorphisms under study between the groups were assessed with the Chi-squared test. Possible associations of the polymorphisms with SACS and BMI were further evaluated with logistic regression analyses. From the polymorphisms studied, only variant rs9939609 in the FTO gene was more prevalent in people with high sleep apnea clinical score (χ2 = 7.1, P = 0.029). However, this association was attenuated after adjustment for body mass index (OR = 0.653, P = 0.178). We failed to confirm previously reported associations between the majority of the studied polymorphisms and sleep apnea. Body weight seems to be an important cofounding factor that needs to be accounted for, when genetic association studies are performed for sleep apnea.

Application of three questionnaires in screening obstructive sleep apnea in patients with chronic obstructive pulmonary disease

Objective: To evaluate the clinical value of three questionnaires [Sleep Apnea Clinical Score (SACS), Berlin Questionnaire (BQ), and Epworth Sleepiness Scale (ESS)] in screening obstructive sleep apnea (OSA) in patients with chronic obstructive pulmonary disease (COPD). Methods: A total of 198 patients with COPD were assessed the likelihood of OSA by using the SACS, BQ, ESS, which was confirmed by the overnight polysomnography (PSG). The receiver operating characteristic curve (ROC) and the calculated likelihood ratios were used to compare the values of three scoring systems in predicting OSA in COPD patients. Results: The patients had an average age of (65.5±9.3) years and 92.9% (184 cases) of which were male, 14 cases (7.1%) were female; 27 cases (13.6%) had a high probability of OSA by SACS assessment, 61 cases (30.8%) had a high probability screened by BQ, and 72 (36.4%) had OSA high probability by ESS. The diagnosis of OSA in 75 patients (37.9%) were confirmed by PSG. OSA did not be accurately predicted by ESS screening in patients with COPD, with a ROC curve area under the curve of 0.592 (95% CI: 0.509-0.674, P=0.053). BQ had an area under the ROC curve of 0.706 (95% CI: 0.626-0.779, P<0.001). However, the prediction of SACS was much better, with an area under the ROC curve of 0.810 (95% CI: 0.737-0.871, P<0.001). Conclusion: SACS is superior to BQ and ESS in predicting OSA in this group of patients with COPD.

Screening for Sleep Apnea: When and How?

Several models aimed at screening for obstructive sleep apnea (OSA) have been published, and most of these are based on questions containing clinical, demographic, and anthropometric features previously identified as OSA risk factors. Here, our main objective was to review the usefulness of some of these screening tools and delineate their performance when attempting to identify subjects at risk for OSA. We evaluated some of the most cited screening tools including Sleep Apnea Clinical Score, Berlin and STOP-Bang questionnaires, Four-Variable Screening Tool, NoSAS score, and the Epworth Sleepiness Scale. Analysis of the predictive performance of the different tools is influenced by the sleep test used, the type of population studied, and the threshold of the apnea/hypopnea index used for OSA diagnosis. Nowadays, it would appear that the most employed screening instrument is the STOP-Bang questionnaire. It is a mnemonic method with eight questions dichotomized into yes-or-no responses and exhibits high sensitivity at all levels of OSA severity while also having been widely validated in several different populations.

Evaluación del riesgo de síndrome de apnea obstructiva del sueño y somnolencia diurna utilizando el cuestionario de Berlín y las escalas Sleep Apnea Clinical Score y Epworth en pacientes con ronquido habitual atendidos en la consulta ambulatoria

Objectives: To determine the frequency of risk for the obstructive sleep apnea syndrome (OSA) through clinical predictors: Berlin Questionnaire, Sleep Apnea Clinical Score (SACS) and the degree of daytime sleepiness measured by Epworth scale. Material and Methods: A cross-sectional study was conducted among patients who reported snoring seen by pulmonology in the outpatient clinic between January and March 2014. Frequency of OSA was calculated according to the three clinical prediction rules. We also determine the characteristic associated with a high risk of OSA according to each prediction rule. Results: We recruited 230 participants, 56.5% were male, with a mean age of 50 ± 12 years. The risk of moderate or high risk for OSA was 61.8%, 66.9% and 62.6% according to Epworth somnolence scale, SACS and Berlin questionnaire, respectively. Neck circumference, abdominal circumference and body mass index were the characteristics more consistently associated with OSA risk. Correlation between SACS and Berlin prediction rules was 0.55, between SACS and Epworth scale was 0.22 and between Berlin and Epworth scale was 0.35 (p < 0.001 for all comparisons). Conclusions: There is a high risk for OSA among snoring patients attending respiratory outpatient clinic. The correlation between prediction rules evaluated was lower than expected. Larger studies in general populations using polysomnography as a reference standard are needed to clarify the diagnostic and prognostic value of OSA prediction rules.

Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea

Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA). Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score. The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments. Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG.

Validating the Diagnostic Accuracy of the Sleep Apnea Clinical Score for Use in Primary Care Populations

ObjectiveTo provide external validation of the diagnostic accuracy of the Sleep Apnea Clinical Score (SACS) tool in a new setting and patient population. Patients and MethodsWe conducted a prospective cohort study. Potential participants were adult family medicine patients. We excluded patients with a SACS of 0, known obstructive sleep apnea (OSA), negative results of previous testing, or life-limiting conditions. After SACS determination, participants completed overnight oximetry, sleep medicine consultation, and polysomnography. Those interpreting tests were blind to the participant's SACS. We determined likelihood ratios (LRs) for OSA diagnosis and posttest probabilities (PTPs). We calculated OSA prevalence (pretest probability), sensitivity, specificity, and positive and negative predictive values. ResultsOne hundred ninety-one of 312 participants (61%) completed all steps. The prevalence of OSA was similar to that found in the derivation cohort (40% vs 45%; P=.31). With OSA defined as Apnea Hypopnea Index greater than 10, a SACS greater than 15 was 40% sensitive and 90% specific, with a positive predictive value of 73% and a negative predictive value of 69%. A SACS greater than 15 in our cohort produced an LR of 4.03 (95% CI, 3.12-5.22) with 73% PTP for OSA as compared with an LR of 5.17 (95% CI, 2.54-10.51) with 78% PTP found in the derivation cohort. ConclusionThe present study provides external validation of the SACS tool. It reliably predicted OSA for patients in our family medicine practice. Broader implementation in primary care practice is recommended. Further study will examine SACS uptake by clinicians and the resulting impact on utilization and clinical efficiency in primary care practices.

Sleep Apnea Clinical Score, Berlin Questionnaire, or Epworth Sleepiness Scale: which is the best obstructive sleep apnea predictor in patients with COPD?

IntroductionThe Sleep Apnea Clinical Score (SACS) and the Berlin Questionnaire (BQ) are used to predict the likelihood of obstructive sleep apnea (OSA). The Epworth Sleepiness Scale (ESS) is used to assess daytime sleepiness, a common OSA symptom. These clinical tools help prioritize individuals with the most severe illness regarding on whom polysomnography (PSG) should be performed. It is necessary to check the applicability of these tools in patients with chronic obstructive pulmonary disease (COPD). The aim of this study is to compare SACS, BQ, and ESS performance in patients with COPD.MethodsThe SACS, BQ, and ESS were applied to 91 patients with COPD. From this group, 24 underwent PSG. In this transversal study, these three tests were compared regarding their likelihood to predict OSA in patients with COPD using receiver-operating characteristic curve statistics.ResultsIn this sample, 58 (63.7%) patients were men, and their mean age was 69.4±9.6 years. Fourteen patients (15.4%) had a high probability of OSA by SACS, 32 (32.5%) had a high probability by BQ, and 37 (40.7%) had excessive diurnal somnolence according to the ESS. From the 24 patients who underwent PSG, OSA diagnosis was confirmed in five (20.8%), according to the American Academy of Sleep Medicine criteria. BQ and ESS did not accurately predict OSA in this group of patients with COPD, with a receiver-operating characteristic curve area under the curves of 0.54 (95% CI: 0.329–0.745, P=0.75) and 0.69 (95% CI: 0.47–0.860, P=0.10), respectively. SACS performance was significantly better, with an area under the curve of 0.82 (95% CI: 0.606–0.943, P=0.02).ConclusionSACS was better than BQ and ESS in predicting OSA in this group of patients with COPD.

The role of Sleep Apnea Clinical Score (SACS) as a pretest probability in obstructive sleep apnea

A retrospective study was conducted in 198 patients suspected to have OSA at a tertiary centre in Mumbai . The pretest probability for the presence of OSAS was performed using Sleep Apnea Clinical Score (SACS).SACS score was calculated as: Snoring 3 points, Apnea 3 points, Neck Circumference in centimeters, Systemic Hypertension 4 points. Risk stratification of SACS score was done as 48 high risk. A diagnosis of OSAS was done by using the criteria laid down by American Academy of Sleep Medicine (AASM). Polysomnography (PSG) showing AHI of 5 or more was considered as diagnostic of OSA. A correlation was established between SACS and OSA using Chi square test. 29/51(56.8%) did not have OSA when their SACS score was low. 53/81(65.43%) had OSA when their SACS score was moderate. With high SACS score 56/66 (84.84%) showed presence of OSA. Overall moderate to high SACS score was able to predict OSA in 109/147 (74.15%). The correlation between SACS score and presence of OSA was highly significant (p value = 0.0000137).