High-resolution wrist-worn overnight oximetry has high positive predictive value for obstructive sleep apnea in a sleep study referral population

Background: Sleep-disordered breathing (SDB) is frequent in the acute phase of stroke. Obstructive sleep apnea (OSA) has been found in 62% of stroke patients. The impact of OSA is significant after ischemic stroke, including early neurological deterioration, poor functional outcome and increased long-term mortality. However, performing polysomnography (PSG) for all patients with acute stroke for diagnose OSA is still impracticable. Therefore clinical tools to select patients at higher risk for OSA would be essential. The aim of this study was to determine the validity of the Berlin Questionnaire (BQ) and the Epworth Sleepiness Scale (ESS) to identify stroke patients in whom the PSG would be indicated. Methods: Subjects with ischemic stroke were stratified into high and low risk groups for SDB using a BQ. The ESS ≥ 10 was used to define excessive daytime sleepiness. The BQ and ESS were administered to the relatives of stroke patients at hospital admission. All patients were submitted to a full overnight PSG at the first night after symptoms onset. OSA severity was measured by the apnea-hypopnea index (AHI). Results: We prospectively studied 40 ischemic stroke patients. The mean age was 62 ± 12.1 years and the obstructive sleep apnea (AHI ≥ 15) was present in 67.5%. On stratifying risk of OSA in these patients based on the QB, 77.5% belonged to the high-risk and 50% to the ESS ≥ 10. The sensitivity of QB was 85%, the specificity 35%, the positive predictive value 74% and the negative predictive value 55%. For ESS was respectively 63%, 85%, 89% and 52%. The diagnostic value of the BQ and ESS in combination to predict OSA had a sensitivity of 58%, a specificity of 89%, a positive predictive value of 95% and a negative predictive value of 38%. Conclusions: The QB even applied to the bed-partners of stroke patients is a useful screening tool for OSA.

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EK Sign: A Wrinkling of Uvula and the Base of Uvula in Obstructive Sleep Apnea-Hypopnea Syndrome

Sleep Disorders ◽

10.1155/2015/749068 ◽

2015 ◽

Vol 2015 ◽

pp. 1-4

Author(s):

Venkata Koka ◽

Sandrine Baron ◽

Darius Abedipour ◽

Vincent Latournerie ◽

Pierre El Chater

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Positive Predictive Value ◽

Clinical Sign ◽

Clinical Data ◽

Predictive Value ◽

Strong Predictor ◽

Obstructive Sleep ◽

Maxilla And Mandible ◽

Hypopnea Syndrome

Introduction. Diagnosis of obstructive sleep apnea-hypopnea syndrome (OSAHS) is suspected in the presence of symptoms and/or pharyngeal alterations and skeletal abnormalities of maxilla and mandible. Our aim is to find a new clinical sign that leads to suspicion of OSAHS in snorers.Methods. We reviewed the clinical data of 69 snoring patients with or without OSAHS. We defined EK sign as the presence of horizontal wrinkling of uvula and the base of uvula and tried to correlate its presence with OSAHS.Results. EK sign was present in 25 of 69 patients. The positive predictive value of EK sign is 100%. The presence of EK sign significantly correlated with OSAHS (44% if AHI ≥ 5 and 0% if AHI < 5;p= 0.01) and severity of OSAHS (7% if AHI < 15 and 58% with AHI ≥ 15;p< 0.001).Conclusions. The EK sign is a strong predictor of OSAHS with a specificity of 100%. We recommend performing sleep tests in presence of EK sign in snorers even in the absence of other abnormalities or symptoms.

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The risk assessment by clinical background and cephalometry for obstructive sleep apnea with CPAP indication in Japanese

Sleep and Biological Rhythms ◽

10.1007/s41105-020-00301-w ◽

2021 ◽

Author(s):

Shuhei Nozawa ◽

Kazuhisa Urushihata ◽

Ryosuke Machida ◽

Masayuki Hanaoka

Keyword(s):

Obstructive Sleep Apnea ◽

Logistic Regression ◽

Regression Analysis ◽

Sleep Apnea ◽

Positive Predictive Value ◽

Pulse Oximetry ◽

Predictive Value ◽

Obstructive Sleep ◽

Clinical Background ◽

At Home

AbstractObstructive sleep apnea (OSA) is a disease characterized by a brief period of cessation or marked decline in ventilation. The standard treatment is continuous positive airway pressure (CPAP). To determine the indication, full-night polysomnography (PSG) is required; however, it is a stressful examination. We verified the usefulness of pulse-oximetry at home as a predictor for CPAP indication before PSG. Simultaneously, the clinical background and cephalometry were also verified. Among 376 subjects who received PSG at our hospital from February 2005 to April 2020, 138 subjects received pulse-oximetry at home before PSG were enrolled retrospectively and performed logistic regression analysis on those with CPAP indication. Concurrently, 262 of 376 subjects received cephalometry were enrolled, and logistic regression analysis were performed using clinical background and cephalometry. A 3% oxygen desaturation (3% ODI) on the pulse-oximeter was a predictor for CPAP indication. The positive predictive value of 3% ODI ≥ 28.5 events/h was 73.3% and the negative predictive value was 62.5%. Older age, higher body mass index (BMI), stronger lower jaw retraction (wider ∠ANB), and longer distance from the anterior superior tip of the hyoid bone to the mandibular plane (MP-H) on cephalometry were also independent predictors. The positive predictive value when both BMI ≥ 26.0 kg/m2 and MP-H ≥ 17.5 mm were present was 88.2% and the negative predictive value when both were absent was 71.3%. The combination of clinical background and cephalometry would be a useful screening tool as well as a pulse-oximetry at home for CPAP indication.

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Comparison of Polysomnographic and Portable Home Monitoring Assessments of Obstructive Sleep Apnea in Saskatchewan Women

Canadian Respiratory Journal ◽

10.1155/2011/408091 ◽

2011 ◽

Vol 18 (5) ◽

pp. 271-274 ◽

Cited By ~ 10

Author(s):

JA Gjevre ◽

RM Taylor-Gjevre ◽

R Skomro ◽

J Reid ◽

M Fenton ◽

...

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

High Risk ◽

Positive Predictive Value ◽

Predictive Value ◽

Diagnostic Methods ◽

Apnea Hypopnea Index ◽

Exclusion Criteria ◽

Obstructive Sleep ◽

Significant Difference

OBJECTIVES: To compare a commercially available, level III in-home diagnostic sleep test (Embletta, Embletta USA) and in-laboratory polysomnography (PSG) in women with suspected obstructive sleep apnea (OSA).METHODS: Consecutive women scheduled for routine PSG testing for evaluation of clinically suspected OSA and who met inclusion/exclusion criteria, were invited to participate. An in-home Embletta portable monitor test was performed one week before or after diagnostic PSG.RESULTS: Forty-seven of 96 women who met the inclusion/exclusion criteria agreed to participate. The mean (± SD) age of the patients was 52.0±11.0 years, with a mean body mass index of 34.86±9.04 kg/m2, and 66% (31 of 47) of patients were at high risk for OSA according to the Berlin score. Paired analysis of the overall population revealed no significant difference in mean apnea/hypopnea index (AHI) between the two diagnostic methods (P=0.475). At an AHI of ≥5, the Embletta test was highly sensitive (90.6%) in determining abnormal versus normal OSA, with a positive predictive value of 82.7%. However, a higher Embletta AHI threshold of ≥10 may be more useful, with a higher level of agreement (kappa coefficient) with PSG testing and a positive predictive value of 92.3%. The in-home study was less useful at distinguishing severe from nonsevere OSA, yielding a sensitivity of 50%.CONCLUSIONS: In women believed to be at high-risk for OSA, Embletta in-home sleep testing is useful for the detection of sleep disordered breathing.

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The Utility of Epworth Sleepiness Scale to Screen Moderate and Severe Obstructive Sleep Apnea Preoperatively to Predict Difficult Airway

Journal of Health and Allied Sciences NU ◽

10.1055/s-0041-1722823 ◽

2021 ◽

Author(s):

Rashmi Soori ◽

Ivor D’Sa ◽

Giridhar Hosmane

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Difficult Airway ◽

Predictive Value ◽

Upper Airway ◽

Apnea Hypopnea Index ◽

Sleep Study ◽

Airway Collapse ◽

Upper Airway Collapse ◽

Obstructive Sleep

Abstract Introduction Obstructive sleep apnea (OSA) is sleep-disordered breathing characterized by repetitive episodes of partial or complete upper airway collapse in sleep leading to apnea and/or hypopnea, desaturations, sleep disruptions, and cardiovascular changes. OSA is a known cause for difficult airway, especially mask ventilation. Daytime sleepiness is one of the hallmark symptoms of OSA. So, we used the Epworth sleepiness score (ESS) in patients suspected of OSA undergoing a sleep study. Methods Overall, 44 subjects suspected to have OSA and undergoing polysomnography were included in the study. The socio-demographic details and the complaints were recorded and the Epworth sleepiness questionnaire was administered. The severity of OSA was graded as per the American Academy of Sleep Medicine using the apnea hypopnea index. Results A total of 44 patients were included in the study. Out of these, 19 were mild, 13 moderate, and 12 severe OSA cases, respectively. ESS of more than 10 showed a positive predictive value of 81.25% and specificity of 85% in screening patients with moderate and severe OSA. But the sensitivity and negative predictive value was only 54.16 and 60.71%, respectively. Conclusion ESS being a simple questionnaire can be easily used preoperatively. A score of more than 10 effectively diagnoses moderate and severe OSA, but less than 10 cannot rule out OSA

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Development of a pediatric obstructive sleep apnea triage algorithm

Journal of Otolaryngology - Head and Neck Surgery ◽

10.1186/s40463-021-00528-8 ◽

2021 ◽

Vol 50 (1) ◽

Author(s):

D. S. Heath ◽

H. El-Hakim ◽

Y. Al-Rahji ◽

E. Eksteen ◽

T. C. Uwiera ◽

...

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Univariate Analysis ◽

Individual Risk ◽

Obstructive Sleep ◽

High Prevalence ◽

Grade Scale ◽

Overnight Oximetry ◽

Triage Algorithm ◽

Pediatric Sleep

Abstract Introduction Diagnosis and treatment of obstructive sleep apnea (OSA) in children is often delayed due to the high prevalence and limited physician and sleep testing resources. As a result, children may be referred to multiple specialties, such as pediatric sleep medicine and pediatric otolaryngology, resulting in long waitlists. Method We used data from our pediatric OSA clinic to identify predictors of tonsillectomy and/or adenoidectomy (AT). Before being seen in the clinic, parents completed the Pediatric Sleep Questionnaire (PSQ) and screening questionnaires for restless leg syndrome (RLS), nasal rhinitis, and gastroesophageal reflux disease (GERD). Tonsil size data were obtained from patient charts and graded using the Brodsky-five grade scale. Children completed an overnight oximetry study before being seen in the clinic, and a McGill oximetry score (MOS) was assigned based on the number and depth of oxygen desaturations. Logistic regression, controlling for otolaryngology physician, was used to identify significant predictors of AT. Three triage algorithms were subsequently generated based on the univariate and multivariate results to predict AT. Results From the OSA cohort, there were 469 eligible children (47% female, mean age = 8.19 years, SD = 3.59), with 89% of children reported snoring. Significant predictors of AT in univariate analysis included tonsil size and four PSQ questions, (1) struggles to breathe at night, (2) apneas, (3) daytime mouth breathing, and (4) AM dry mouth. The first triage algorithm, only using the four PSQ questions, had an odds ratio (OR) of 4.02 for predicting AT (sensitivity = 0.28, specificity = 0.91). Using only tonsil size, the second algorithm had an OR to predict AT of 9.11 (sensitivity = 0.72, specificity = 0.78). The third algorithm, where MOS was used to stratify risk for AT among those children with 2+ tonsils, had the same OR, sensitivity, and specificity as the tonsil-only algorithm. Conclusion Tonsil size was the strongest predictor of AT, while oximetry helped stratify individual risk for AT. We recommend that referral letters for snoring children include graded tonsil size to aid in the triage based on our findings. Children with 2+ tonsil sizes should be triaged to otolaryngology, while the remainder should be referred to a pediatric sleep specialist. Graphical abstract

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

SLEEP ◽

10.1093/sleep/zsab072.418 ◽

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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Subjective and Objective Appraisal of Activity in Adults with Obstructive Sleep Apnea

Journal of Aging Research ◽

10.4061/2011/751819 ◽

2011 ◽

Vol 2011 ◽

pp. 1-6 ◽

Cited By ~ 19

Author(s):

Eileen R. Chasens ◽

Susan M. Sereika ◽

Martin P. Houze ◽

Patrick J. Strollo

Keyword(s):

Physical Activity ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Epworth Sleepiness Scale ◽

Functional Outcomes ◽

Apnea Hypopnea Index ◽

Sleep Study ◽

Obstructive Sleep ◽

Subjective Sleepiness ◽

Aging Adults

Objective.This study examined the association between obstructive sleep apnea (OSA), daytime sleepiness, functional activity, and objective physical activity.Setting.Subjects (N=37) being evaluated for OSA were recruited from a sleep clinic.Participants. The sample was balanced by gender (53% male), middle-aged, primarily White, and overweight or obese with a mean BMI of 33.98 (SD=7.35;median BMI=32.30). Over 40% reported subjective sleepiness (Epworth Sleepiness Scale (ESS) ≥10) and had OSA (78% with apnea + hypopnea index (AHI) ≥5/hr).Measurements.Evaluation included questionnaires to evaluate subjective sleepiness (Epworth Sleepiness Scale (ESS)) and functional outcomes (Functional Outcomes of Sleep Questionnaire (FOSQ)), an activity monitor, and an overnight sleep study to determine OSA severity.Results.Increased subjective sleepiness was significantly associated with lower scores on the FOSQ but not with average number of steps walked per day. A multiple regression analysis showed that higher AHI values were significantly associated with lower average number of steps walked per day after controlling patient's age, sex, and ESS.Conclusion.Subjective sleepiness was associated with perceived difficulty in activity but not with objectively measured activity. However, OSA severity was associated with decreased objective physical activity in aging adults.

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Abstract P195: Lack of Association between Sleep Duration and ECG Arrhythmia Risk Measures: Chicago Area Sleep Study

Circulation ◽

10.1161/circ.127.suppl_12.ap195 ◽

2013 ◽

Vol 127 (suppl_12) ◽

Author(s):

Jason Ng ◽

Phyllis C Zee ◽

Jeffrey J Goldberger ◽

Kristen L Knutson ◽

Kiang Liu ◽

...

Keyword(s):

Risk Factors ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Sleep Duration ◽

Low Risk ◽

Qtc Interval ◽

Sleep Study ◽

Chicago Area ◽

Obstructive Sleep ◽

Pr Interval

Introduction Sleep duration is significantly associated with cardiovascular disease risk factors such as hypertension, diabetes, and obesity in adults at low risk for obstructive sleep apnea. Although it is known that apnea increases the risk for sudden cardiac death, it is not known whether adults with short sleep duration independent of apnea have a higher risk for cardiac arrhythmias Hypothesis We tested the hypothesis that sleep duration in adults at low risk for obstructive sleep apnea would be associated with ECG measures that are known risk factors for ventricular arrhythmias. Methods The Chicago Area Sleep Study recruited 610 participants via commercially available telephone listings. Participants were screened using in-home apnea detection equipment (ApneaLinkTM) for one night to exclude subjects with apnea/hypopnea index ≥ 15. Participants wore wrist actigraphs for 7 days to objectively determine sleep duration. A 10-minute 12-lead ECG was recorded for each subject. Standard measures of heart rate, PR interval, and QTc interval were obtained along with markers of ventricular repolarization, Tpeak to Tend interval (Tpe) and spatial QRS-T angle. Signal-averaged ECG analysis was performed to measure filtered QRS duration (fQRSd), RMS voltage of terminal 40 ms (RMS), and duration of terminal QRS signals <40μV (LAS). Participants with atrial fibrillation, >20% ectopic beats and those using antihypertensive and sleep medications were excluded from analysis. The effect of sleep duration on the ECG parameters was estimated using a multiple linear regression model adjusting for demographics (sex, age, and race) and cardiovascular risk factors (BMI, hypertension, coronary heart disease, and diabetes). Results ECGs from a total of 504 participants (200 male, 48±8 years old) were analyzed. Mean sleep duration was 7±1 hrs, heart rate was 64±9 bpm, PR interval was 165±18 ms, and QTc interval was 424±23 ms. Mean Tpe interval was 83±14 ms and spatial QRS-T angle was 29±26 deg. The signal-averaged ECG measures of fQRSd, RMS, and LAS had mean values of 78±12 ms, 58±34 μV, and 24±9 ms, respectively. In an unadjusted model, there was a borderline association between sleep duration and QTc (β=0.004 ms/hr, SE=0.0023, p=0.08). However, that association was no longer significant following adjustment with demographics and cardiovascular risk factors. No other ECG measures were associated with sleep duration. Conclusions In a population at low risk of obstructive sleep apnea, ECG-based measures of cardiovascular risks were not associated with sleep duration. Previously reported associations between short sleep and cardiovascular events may not be arrhythmic in origin.

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Abstract 14771: Obstructive Sleep Apnea is Associated With Cardiac Dysfunction in Children With Congenital Heart Disease

Circulation ◽

10.1161/circ.142.suppl_3.14771 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Daniel Combs ◽

Vanessa Fernandez ◽

brent j barber ◽

Wayne J Morgan ◽

Chiu-Hsieh Hsu ◽

...

Keyword(s):

Congenital Heart Disease ◽

Obstructive Sleep Apnea ◽

Heart Disease ◽

Sleep Apnea ◽

Right Ventricular ◽

Cardiac Dysfunction ◽

Congenital Heart ◽

Left Ventricular ◽

Sleep Study ◽

Obstructive Sleep

Introduction: Obstructive sleep apnea (OSA) is associated with cardiac dysfunction in children without congenital heart disease (CHD). Children with CHD are at increased risk for OSA and may be susceptible to further cardiovascular consequences due to OSA but the extent and nature of such cardiovascular effects of OSA are unknown. Methods: Children (6-17 years old) with corrected CHD without current cyanosis or Down syndrome were recruited from pediatric cardiology clinic. Home sleep tests were done to determine the presence and severity of OSA. OSA was defined as an obstructive apnea hypopnea index (oAHI) ≥1. Mild OSA was defined as an oAHI of ≥1 to <5 and moderate OSA was defined as an oAHI of ≥5 to <10. Standard clinically indicated echocardiograms were performed in clinic. Echocardiographic findings were compared between children with CHD with and without comorbid OSA using t-tests, Wilcoxon-sign rank tests as well as linear or logistic regression as appropriate. Results: Thirty-two children had sleep study and echocardiographic data available. OSA was present in 18 children (56%). OSA was mild in 89% and moderate in 11% of cases. There were no significant differences in age, body mass index, CHD severity, gender or ethnicity between children with and without OSA. Children with OSA had larger height-indexed right ventricular end-diastolic diameter (RVDi) compared to those without OSA (median 1.35, 95% CI 1.09, 1.56 vs. 1.21, 95% CI 1.01, 1.57; p=0.04). Children with moderate OSA had a reduced left ventricular shortening fraction compared to both those with mild OSA and no OSA (30.0 ± 6.1% vs. 38.7 ± 4.4%; p=0.009 and 39.2 ± 3.6%; p=0.007, respectively). Children with moderate OSA had increased left ventricular end-systolic diameter compared to those with mild OSA and no OSA (3.4 ± 0.4 cm vs. 2.5 ± 0.4; p=0.007 and 2.4 ± 0.5; p=0.001, respectively). Children with an RVDi above the median were seven times more likely to have OSA than those with an RVDi below the median (odds ratio 6.9.; 95% CI 1.3, 35; p=0.02). Conclusions: OSA is associated with changes in cardiac morphology and reduced contractility in children with CHD. Additionally, the presence of right ventricular dilation may suggest the need for OSA evaluation in children with CHD.

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