scholarly journals Associations of Obstructive Sleep Apnea, Obestatin, Leptin, and Ghrelin with Gastroesophageal Reflux

2021 ◽  
Vol 10 (21) ◽  
pp. 5195
Author(s):  
Piotr Pardak ◽  
Rafał Filip ◽  
Jarosław Woliński ◽  
Maciej Krzaczek
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Gastroesophageal Reflux ◽  
Ph Monitoring ◽  
Sleep Study ◽  
Esophageal Ph ◽  
Obstructive Sleep ◽  
The Relationship ◽  
Gerd Symptoms ◽  
Severe Sleep Apnea

Gastroesophageal reflux disease (GERD) is commonly observed in patients with obstructive sleep apnea (OSA). Hormonal disorders observed in OSA may be relevant in the development of GERD. The aim of the study was to assess the correlations between ghrelin, obestatin, leptin, and the intensity of GERD in patients with OSA. The study included 58 patients hospitalized due to clinical suspicion of sleep disorders during sleep. All patients underwent a sleep study, and blood samples were collected overnight for hormonal tests. Survey data concerning symptoms of GERD, gastroscopy, and esophageal pH monitoring results were included in the study. In patients with OSA, GERD was twice as common when compared to the group without OSA. Among subjects with severe sleep apnea (AHI > 30; n = 31; 53%), we observed lower ghrelin levels, especially in the second half of the night and in the morning (p5.00 = 0.0207; p7.00 = 0.0344); the presence of OSA had no effect on obestatin and leptin levels. No significant differences in hormonal levels were observed between the groups depending on the diagnosis of GERD. However, correlations of ghrelin levels with the severity of esophagitis, leptin and ghrelin levels with the severity of GERD symptoms, and leptin levels with lower esophageal pH were found. GERD is more frequent among patients with OSA. In both GERD and OSA, deviations were observed in the levels of ghrelin and leptin. However, our analysis demonstrates that the relationship between OSA and GERD does not result from these disorders.

1060 Screening For Obstructive Sleep Apnea In Severe Gastroesophageal Reflux Disease Patients: A Forgotten Association?

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A403-A403
Author(s):  
A De ◽  
H Gharib ◽  
D Frenia ◽  
S Velpari
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Gastroesophageal Reflux Disease ◽  
Gastroesophageal Reflux ◽  
Reflux Disease ◽  
Ph Monitoring ◽  
Intermediate Risk ◽  
Inconclusive Result ◽  
Obstructive Sleep ◽  
History Of

Abstract Introduction Obstructive sleep apnea (OSA) is an emerging epidemic in the USA and remains underdiagnosed. Investigations of Gastroesophageal reflux disease (GERD) poses a substantial burden on patient-welfare and costs to the health system. Current literature has highlighted the association between severe GERD and OSA, and other sleep disorders. We conducted a retrospective analysis of patient records undergoing Bravo pH monitoring for refractory GERD to measure the prevalence of OSA and screening. Methods Records of patients who underwent outpatient Bravo pH monitoring at a teaching hospital were reviewed from August 2018 to May 2019. 72 records were reviewed in our analysis. Analysis variables included age, gender, body mass index, history of hypertension and OSA. Outpatient records were reviewed for documentation for OSA or screening and demographics were obtained for calculation of a partial STOP-BANG score (a validated OSA screening tool). Results 8 out of 72 (11%) were excluded due to incomplete documentation regarding their history. Of the remaining 64, 2 had a known diagnosis of OSA (3%) and 1 was due a sleep study for maintenance insomnia. Of the remaining 61 patients, none had documentation of a history pertaining to sleep complaints or full screening for OSA. 4 of the 8 components to the STOP-BANG criteria were documented and used to measure risk of OSA in these patients. 23 (39%) patients had a score of 3 or above characterizing them as intermediate risk. The other 4 components were not used due to a lack of clinical information. 13 of these patients had a positive Bravo test, 2 had an inconclusive result and 8 had a negative result. Of the 61 patients in total, 31 had a positive Bravo result and 9 had an inconclusive result. Conclusion In our study, we found that 39% of patients based on demographic data were of intermediate risk of OSA. Over half of these patients had a positive result for GERD. Despite the increased awareness of sleep disorders it is still neglected despite prevalent associated comorbid conditions. This study highlights the failure to screen for this modifiable risk factor within a teaching environment. Support None

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.

The relationship between opioid use and obstructive sleep apnea: A systematic review and meta-analysis

2021 ◽  
Vol 58 ◽  
pp. 101441
Author(s):  
Aseel Ahmad ◽  
Randa Ahmad ◽  
Moussa Meteb ◽  
Clodagh M. Ryan ◽  
Richard S. Leung ◽  
...  
Keyword(s):  
Systematic Review ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Meta Analysis ◽  
Opioid Use ◽  
Obstructive Sleep ◽  
The Relationship

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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