Velopharyngeal Dysfunction and Sleep Apnea-A Survey to Ascertain Surgical Practice Patterns

2017 ◽  
Vol 54 (1) ◽  
pp. 13-18 ◽  
Author(s):  
Katelyn G. Bennett ◽  
Adina B. Robinson ◽  
Steven J. Kasten ◽  
Steven R. Buchman ◽  
Christian J. Vercler
Keyword(s):  
Sleep Apnea ◽  
Practice Patterns ◽  
Response Rate ◽  
Surgical Specialty ◽  
Sleep Study ◽  
Surgical Practice ◽  
Sleep Studies ◽  
Obstructive Sleep ◽  
E Mail ◽  
Question Survey

Objective To determine if all cleft surgeons uniformly and adequately evaluate patients with cleft for obstructive sleep apnea (OSA) and consider OSA in treatment of velopharyngeal dysfunction (VPD). Design A 22-question survey was administered via e-mail to 1117 surgeons who were members of the American Cleft Palate-Craniofacial Association. Logistic regression was used to determine if management was affected by years in practice, clinical volume, field of training, and region of practice. Main Outcome Measures We sought to determine if years in practice, clinical volume, region of practice, and surgical specialty affected surgeons’ evaluation of OSA and their approaches to VPD. Results A total of 231 surgeons responded (21% response rate), and 67% stated that they had trained in plastic surgery. With increasing years of practice, surgeons were less likely to refer patients for preoperative and postoperative sleep studies ( P = .00 and P = .001, respectively), screen patients for sleep apnea ( P = .008), or change their management based on a sleep study ( P = .001). There were no significant differences in screening or testing for OSA based upon clinical volume. Among those surveyed, otolaryngologists were more likely to refer patients for postoperative sleep studies ( P = .028). Surgeons in the Southeast were more likely to change their management based upon a sleep study ( P = .038). Conclusions Statistically significant trends in screening and testing for OSA in the setting of VPD were identified by this survey. Notably, older surgeons were less likely to investigate OSA in their patients, and not all specialties equally refer for postoperative sleep studies.

scholarly journals Revisiting level II sleep studies in the era of COVID-19: a theoretical economic decision model in patients with suspected obstructive sleep apnea

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Najib T. Ayas ◽  
Rachel Jen ◽  
Brett Baumann
Keyword(s):  
British Columbia ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Decision Model ◽  
Sleep Study ◽  
Diagnostic Algorithms ◽  
Sleep Studies ◽  
Level Ii ◽  
Obstructive Sleep ◽  
Home Sleep Study

Abstract Background The recent pandemic has made it more challenging to assess patients with suspected obstructive sleep apnea (OSA) with in laboratory polysomnography (PSG) due to concerns of patient and staff safety. The purpose of this study was to assess how Level II sleep studies (LII, full PSG in the home) might be utilized in diagnostic algorithms of suspected OSA using a theoretical decision model. Methods We examined four diagnostic algorithms for suspected OSA: an initial PSG approach, an initial LII approach, an initial Level III approach (LIII, limited channel home sleep study) followed by PSG if needed, and an initial LIII approach followed by LII if needed. Costs per patient assessed was calculated as a function of pretest OSA probability and a variety of other variables (e.g. costs of tests, failure rate of LIII/LII, sensitivity/specificity of LIII). The situation in British Columbia was used as a case study. Results The variation in cost per test was calculated for each algorithm as a function of the above variables. For British Columbia, initial LII was the least costly across a broad range of pretest OSA probabilities (< 0.80) while initial LIII followed by LII as needed was least costly at very high pretest probability (> 0.8). In patients with a pretest OSA probability of 0.5, costs per patient for initial PSG, initial LII, initial LIII followed by PSG, and initial LIII followed by LII were: $588, $417, $607, and $481 respectively. Conclusions Using a theoretical decision model, we developed a preliminary cost framework to assess the potential role of LII studies in OSA assessment. Across a broad range of patient pretest probabilities, initial LII studies may provide substantial cost advantages. LII studies might be especially useful during pandemics as they combine the extensive physiologic information characteristic of PSG with the ability to avoid in-laboratory stays. More empiric studies need to be done to test these different algorithms.

CME/Answers: Obstructive Sleep Apnea: How to Deal with Night- To-Night Variability of Respiratory Events?

Praxis ◽  
2021 ◽  
Vol 110 (1) ◽  
pp. 16-18
Author(s):  
Maurice Roeder ◽  
Esther I. Schwarz ◽  
Thomas Gaisl ◽  
Malcolm Kohler
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Apnea Hypopnea Index ◽  
Night Sleep ◽  
Sleep Study ◽  
Diagnostic Uncertainty ◽  
Sleep Studies ◽  
Respiratory Events ◽  
Obstructive Sleep ◽  
Single Night

Abstract.According to current recommendations, the diagnosis of obstructive sleep apnea (OSA) is established by a single-night sleep study. However, recent reports suggest a remarkable night-to-night variability of OSA severity. We report on a 76-year-old man with suspected OSA who underwent six sleep studies within 13 months. Sleep studies demonstrated a remarkable variability of respiratory events based on an apnea-hypopnea index (AHI) varying between 1.1 and 43.1/h. There were no changes in body weight, alcohol intake, medication or comorbidities during the evaluation period. Due to diagnostic uncertainty and missing subjective benefit, the initially implemented CPAP therapy was stopped after one year of therapy. Considering night-to-night variability of OSA severity, single-night sleep studies might not be accurate enough in order to reliably diagnose or exclude OSA.

569 Correlation between age and initial findings of sleep disordered breathing in children with achondroplasia

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A224-A225
Author(s):  
Fayruz Araji ◽  
Cephas Mujuruki ◽  
Brian Ku ◽  
Elisa Basora-Rovira ◽  
Anna Wani
Keyword(s):  
Sleep Apnea ◽  
Primary Care Physicians ◽  
Sleep Disordered Breathing ◽  
Upper Airway ◽  
Sleep Study ◽  
Surgical Interventions ◽  
Screening Guidelines ◽  
Obstructive Sleep ◽  
Children’S Sleep ◽  
Disordered Breathing

Abstract Introduction Achondroplasia (ACH) occurs approximately 1 in 20,000–30,000 live births. They are prone to sleep disordered breathing specifically due to the upper airway stenosis, enlarged head circumference, combined with hypotonia and limited chest wall size associated with scoliosis at times. The co-occurrence of sleep apnea is well established and can aide in the decision for surgical intervention, however it is unclear at what age children should be evaluated for sleep apnea. Screening is often delayed as during the daytime there is no obvious gas exchange abnormalities. Due to the rareness of this disease, large studies are not available, limiting the data for discussion and analysis to develop guidelines on ideal screening age for sleep disordered breathing in children with ACH. Methods The primary aim of this study is to ascertain the presence of sleep disorder breathing and demographics of children with ACH at time of first polysomnogram (PSG) completed at one of the largest pediatric sleep lab in the country. The secondary aim of the study is to identify whether subsequent polysomnograms were completed if surgical interventions occurred and how the studies differed over time with and without intervention. Retrospective review of the PSGs from patients with ACH, completed from 2017–2019 at the Children’s Sleep Disorders Center in Dallas, TX. Clinical data, demographics, PSG findings and occurrence of interventions were collected. Results Twenty-seven patients with the diagnosis of ACH met criteria. The average age at the time of their first diagnostic PSG was at 31.6 months of age (2.7 years), of those patients 85% had obstructive sleep apnea (OSA),51% had hypoxemia and 18% had hypercapnia by their first diagnostic sleep study. Of those with OSA, 50% were severe. Majority were females, 55%. Most of our patients were Hispanic (14%), Caucasian (9%), Asian (2%), Other (2%), Black (0%). Each patient had an average of 1.9 PSGs completed. Conclusion Our findings can help create a foundation for discussion of screening guidelines. These guidelines will serve to guide primary care physicians to direct these patients to an early diagnosis and treatment of sleep disordered breathing. Support (if any):

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):

scholarly journals Snoring: a source of noise pollution and sleep apnea predictor

SLEEP ◽  
2019 ◽  
Vol 43 (6) ◽  
Author(s):  
Mudiaga Sowho ◽  
Francis Sgambati ◽  
Michelle Guzman ◽  
Hartmut Schneider ◽  
Alan Schwartz
Keyword(s):  
Sleep Apnea ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Noise Pollution ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Sound Levels ◽  
Obstructive Sleep ◽  
Single Night ◽  
The Relationship

Abstract Snoring is a highly prevalent condition associated with obstructive sleep apnea (OSA) and sleep disturbance in bed partners. Objective measurements of snoring in the community, however, are limited. The present study was designed to measure sound levels produced by self-reported habitual snorers in a single night. Snorers were excluded if they reported nocturnal gasping or had severe obesity (BMI &gt; 35 kg/m2). Sound was measured by a monitor mounted 65 cm over the head of the bed on an overnight sleep study. Snoring was defined as sound ≥40 dB(A) during flow limited inspirations. The apnea hypopnea index (AHI) and breath-by-breath peak decibel levels were measured. Snore breaths were tallied to determine the frequency and intensity of snoring. Regression models were used to determine the relationship between objective measures of snoring and OSA (AHI ≥ 5 events/h). The area under the curve (AUC) for the receiver operating characteristic (ROC) was used to predict OSA. Snoring intensity exceeded 45 dB(A) in 66% of the 162 participants studied, with 14% surpassing the 53 dB(A) threshold for noise pollution. Snoring intensity and frequency were independent predictors of OSA. AUCs for snoring intensity and frequency were 77% and 81%, respectively, and increased to 87% and 89%, respectively, with the addition of age and sex as predictors. Snoring represents a source of noise pollution in the bedroom and constitutes an important target for mitigating sound and its adverse effects on bed partners. Precise breath-by-breath identification and quantification of snoring also offers a way to risk stratify otherwise healthy snorers for OSA.

Prognostic relevance of sleep apnea syndrome in patients with pulmonary arterial hypertension

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J Precek ◽  
K Vykoupil ◽  
F Kovacik ◽  
M Hutyra
Keyword(s):  
Pulmonary Hypertension ◽  
Sleep Apnea ◽  
Pulmonary Arterial Hypertension ◽  
General Population ◽  
Arterial Hypertension ◽  
Left Ventricular ◽  
Sleep Study ◽  
Prognostic Relevance ◽  
Obstructive Sleep ◽  
Pulmonary Arterial

Abstract Introduction Sleep disordered breathing (SDB) is a group of ventilatory disorders during sleep which includes obstructive sleep apnea (OSA), central sleep apnea (CSA), and sleep related hypoventilation. In patients with SDB, the prevalence of pulmonary hypertension (PH) ranges from 17% to 52%. While SDB is prevalent in the general population with recent estimates of 20% to 30%, in those with cardiovascular disease, particularly left ventricular failure, there is a higher reported prevalence of 47%. Aims The aims of this study were to determine the prevalence and prognostic relevance of sleep apnea in a cohort of patients with newly diagnosed pulmonary arterial hypertension (ESC/WHO Group 1 pulmonary hypertension). Methods We evaluated prospectively 76 patients with the pulmonary arterial hypertension (mean age 54±16 years; 45% male). All patients underwent right heart catheterisation, clinical assessments, sleep study, standard laboratory testing and evaluation of subjective sleepiness by the Epworth Sleepiness Scale. Sleep test was provided with an ApneaLink Plus, consisting of nasal pressure sensor, respiratory effort band, and pulse oximeter worn on the finger. Subjects previously treated for or diagnosed with SDB were excluded from the study. Results Sleep apnea (SA) – defined as apnea-hypopnea index (AHI) ≥5/h – was found in 59 (77.6%) of the pulmonary arterial hypertension (PAH) patients. Mean AHI in the cohort of PAH patients with SA was 26.1±16.6/h. Mean follow-up was 24 months, during which 15 (19.7%) patients died. Characteristics of parameters related to SA in groups of survivors and deceased are in table 1. From the sleep apnea-related parameters, only time with O2Sat &lt;90% – T90 was significantly associated with mortality (AUC 0.856; 95% CI 0.693 – 1.019; p&lt;0.001). Conclusions The presence of sleep apnea in pulmonary arterial hypertension patients is high. The prevalence of sleep apnea is higher in PAH patients than in the general population. The presence of sleep apnea in patients with PAH was not associated with worse prognosis, but noctural hypoxemia (time with O2Sat &lt;90%) was related to poor prognosis. Sleep apnea in patients with PAH should be screened for systematically. Funding Acknowledgement Type of funding source: None

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

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
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.

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

Circulation ◽  
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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