Obstructive sleep apnea and risk of aortic dissection: A meta-analysis of observational studies

Vascular ◽  
2018 ◽  
Vol 26 (5) ◽  
pp. 515-523 ◽  
Author(s):  
Xiushi Zhou ◽  
Fei Liu ◽  
Wei Zhang ◽  
Guili Wang ◽  
Daqiao Guo ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Aortic Dissection ◽  
Confidence Interval ◽  
Mean Difference ◽  
Cochrane Library ◽  
Severe Obstructive Sleep Apnea ◽  
Odds Ratios ◽  
Sleep Study ◽  
Obstructive Sleep

Objectives Obstructive sleep apnea acts as a potential risk factor for the development of cardiovascular disease. We undertook collaborative meta-analyses to clarify the risk of aortic dissection among adults suffering obstructive sleep apnea. Methods A systematic search of the databases (PubMed, Embase, and Cochrane Library) was performed. Studies reporting on the association between obstructive sleep apnea and aortic dissection were included. Information on 424 cases of aortic dissection in 56,291 patients from one cohort, four case–controls, and two cross-sectional studies were included in this study. Results The summary suggested that patients with obstructive sleep apnea are associated with an overall significant 60% increase in the risk of aortic dissection, compared to unexposed patients (odds ratios 1.60; 95% confidence interval 1.01–2.53), with a significantly higher apnea–hypopnea index (mean difference 10.71; 95% confidence interval 7.46–13.96). Moreover, a greater relation was found between moderate-to-severe obstructive sleep apnea and aortic dissection (odds ratios 4.43; 95% confidence interval 2.59–7.59). Adverse outcomes obtained by sleep study such as oxygen desaturation index (mean difference 10.51; 95% confidence interval 7.54–13.48), average SaO2 (−1.36; 95% confidence interval −2.63 to −0.09), and minimum SaO2 (−3.63; 95% confidence interval −5.27 to −1.98) were correspondingly related to patients with aortic dissection. Conclusions Obstructive sleep apnea, especially moderate-to-severe obstructive sleep apnea, may impose an additional risk of suffering from aortic dissection with a potential mechanism including intermittent hypoxia.

scholarly journals Epicardial Adipose Tissue in Patients with Obstructive Sleep Apnea: A Systematic Review and Meta-analysis

2020 ◽  
Vol 5 (2) ◽  
pp. 81-88
Author(s):  
Bin Liu ◽  
Yingrui Li ◽  
Jianlin Du ◽  
Qiang She ◽  
Songbai Deng
Keyword(s):  
Obstructive Sleep Apnea ◽  
Adipose Tissue ◽  
Sleep Apnea ◽  
Confidence Interval ◽  
Epicardial Adipose Tissue ◽  
Meta Analysis ◽  
Mean Difference ◽  
Cochrane Library ◽  
Obstructive Sleep ◽  
Standardized Mean Difference

Objective: Epicardial adipose tissue (EAT) is a potential risk factor for obstructive sleep apnea (OSA). We performed a meta-analysis to assess the association of EAT with OSA.Methods: The PubMed, EMBASE, Web of Science, Cochrane Library, and Wanfang databases were searched by two independent investigators for all observational studies assessing the association of EAT with OSA. Then we assessed the association of EAT thickness (EAT-t) and EAT volume (EAT-v) with OSA by a meta-analysis.Results: Ten studies were included in the final analysis. Compared with that in controls, EAT-t in OSA patients was significantly increased (standardized mean difference 0.88, 95% confidence interval 0.72‐1.05, P=0.000). Furthermore, EAT-t was greater in OSA patients than in controls with similar BMIs. However, we did not find significant differences in EAT-v between OSA patients and controls (standardized mean difference 2.46, 95% confidence interval −0.36 to 5.29, P=0.088). EAT-t in the mild, moderate, and severe OSA subgroups was greater than in the controls. In addition, there were significant differences in EAT-t among the mild, moderate, and severe OSA subgroups.Conclusions: EAT-t was greater in patients with OSA than in controls, and EAT-t was also associated with the severity of OSA. These findings may provide a new clue for the pathogenesis and treatment of OSA.

scholarly journals Predictive factors facilitate identification of potential aortic dissection in patients with obstructive sleep apnea syndrome

2021 ◽  
Author(s):  
dinghui wu ◽  
Dandan Jiang ◽  
Qu Chen ◽  
xiangyang yao ◽  
chunping dong ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Aortic Dissection ◽  
Obstructive Sleep Apnea Syndrome ◽  
Sleep Apnea Syndrome ◽  
Sleep Study ◽  
Hypertensive Patients ◽  
Lymphocyte Ratio ◽  
Obstructive Sleep ◽  
Apnea Syndrome

Objective: Investigating potential predictors of aortic dissection development in high-risk hypertensive patients with obstructive sleep apnea syndrome (OSAS). Methods: Hypertensive patients with aortic dissection, admitted to hospital between January 2010 and July 2020, was diagnosed with OSAS by overnight sleep study with polysomnography (PSG). Results: Male was liable to aortic dissection compared to female in both groups（84.7% and 86% respectively）.There were actually significant differences with regard to neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), mean platelet volume (MPV) / platelet count (PLT) ratio and D-dimer that we concerned about and were of great value in aortic dissection as previously reported. As multivariable regression analysis revealed, NLR (odds rate [OR], 2.258, 95% confidence interval [CI], 1.464-3.482, P<0.05), MPV/PLT (OR, 2.743, 95%CI, 1.713-4.392, P<0.05) and apnea and hypopnea index (AHI) (OR, 1.746,95% CI, 1.225-1.320, P<0.05) were all independent risk factors for aortic dissection. receiver operating characteristic curves analysis of NLR, MPV/PLT, AHI and combination of indicators for aortic dissection revealed combination of NLR, MPV/PLT ratio and AHI is of outstanding predictive value with sensitivity of 0.904 and specificity of 0.847. At the thresholds of 4.41 for NLR and 5.14 for MPV/PLT and 35.95 for AHI, 87.5% of all studied patients were expected to be correctly diagnosed with regard to aortic dissection. Conclusion: Inflammation, platelet alteration is crucial for initiation and progression of aortic dissection. Combined detection of NLR, MPV/PLT ratio and AHI could assist sleep physicians to identify silent or potential aortic dissection in patient comorbidity OSAS and hypertension.

scholarly journals 1224 Treatment of Severe OSA Using Low Flow Oxygen in a Neonate with Robin Sequence

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A467-A468
Author(s):  
Sidra Saeed ◽  
Louella Amos
Keyword(s):  
Obstructive Sleep Apnea ◽  
Weight Gain ◽  
Sleep Apnea ◽  
Supplemental Oxygen ◽  
Low Flow ◽  
Severe Obstructive Sleep Apnea ◽  
Sleep Study ◽  
Surgical Interventions ◽  
Robin Sequence ◽  
Obstructive Sleep

Abstract Introduction Robin Sequence (RS) involves the clinical triad of micrognathia, glossoptosis and cleft palate. There is a spectrum of severity, but most neonates with RS have upper airway obstruction, resulting in severe obstructive sleep apnea, sometimes requiring surgical interventions such as tongue-lip adhesion, mandibular distraction, or tracheostomy. We present an infant with RS and severe obstructive sleep apnea which was managed with supplemental oxygen. Report of Case Our patient was born at 39 weeks gestation with RS. He had a normal DNA microarray. He was discharged after a 3 week NICU hospitalization for poor feeding. Over the next 2 months, he had poor weight gain and worsening obstructive breathing and was evaluated by craniofacial surgery at that time. Room air polysomnography (PSG) was recommended and revealed an AHI of 21, REM AHI of 48, supine AHI of 25, prone AHI of 19, mean SPO2 of 98%, minimum SPO2 of 61%, and normal capnography with 0% of the time spent &gt; 50 mmHg. A repeat sleep study on 1/4LPM oxygen in the supine position revealed an AHI of 1.7, mean SPO2 of 99%, minimum SPO2 of 92%, and normal capnography. He was discharged on supplemental oxygen. At 4 months of age, he had good weight gain. At 10 months of age, room air PSG revealed persistent OSA with an AHI of 7.2, REM AHI of 21, mean SPO2 of 97%, minimum SPO2 of 81%, and normal capnography. At age 3 yrs, his PSG on room air showed resolution of his OSA with an AHI of 0.6, mean SPO2 of 97%, minimum SPO2 of 87% and normal capnography. Conclusion This case illustrates the spectrum of severity of RS and the utility of low flow oxygen to treat OSA in this patient population.

Postoperative monitoring of children with obstructive sleep apnea syndrome

2014 ◽  
Vol 155 (18) ◽  
pp. 703-707 ◽  
Author(s):  
Pálma Benedek ◽  
Gabriella Kiss ◽  
Eszter Csábi ◽  
Gábor Katona
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Obstructive Sleep Apnea Syndrome ◽  
Preoperative Evaluation ◽  
Sleep Apnea Syndrome ◽  
Study Patient ◽  
Severe Obstructive Sleep Apnea ◽  
Obstructive Sleep ◽  
Significant Difference ◽  
Apnea Syndrome

Introduction: Treatment of pediatric obstructive sleep apnea syndrome is surgical. The incidence of postoperative respiratory complications in this population is 5–25%. Aim: The aim of the authors was to present the preoperative evaluation and monitoring procedure elaborated in Heim Pál Children Hospital, Budapest. Method: 142 patients were involved in the study. Patient history was obtained and physical examination was performed in all cases. Thereafter, polysomnography was carried out, the severity of the obstructive sleep apnea syndrome was determined, and the patients underwent tonsilloadenotomy. Results: 45 patients with mild, 50 patients with moderate and 47 patients with severe obstructive sleep apnea syndrome were diagnosed. There was no complication in patients with mild disease, while complications were observed in 6 patients in the moderate group and 24 patients in the severe group (desaturation, apnea, stridor, stop breathing) (p<0.000). In patients with severe obstructive sleep apnea syndrome, no significant difference was noted in preoperative apnoea-hypapnea index (p = 0.23) and in nadir oxygen saturation values (p = 0.73) between patients with and without complication. Conclusions: Patients with severe obstructive sleep apnea syndrome should be treated in hospital where pediatric intensive care unit is available. Orv. Hetil., 2014, 155(18), 703–707.

Predictive Factors for Efficacious Oral Appliance Therapy in Moderate to Severe Obstructive Sleep Apnea Patients

2021 ◽  
Author(s):  
Guillaume Buiret ◽  
Maroun Bechara ◽  
Isabelle Plouin‐Gaudon ◽  
Frederique Bavozet ◽  
Olivia Dancea ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Predictive Factors ◽  
Oral Appliance ◽  
Severe Obstructive Sleep Apnea ◽  
Oral Appliance Therapy ◽  
Obstructive Sleep

scholarly journals Continuous Positive Airway Pressure-Mandibular Advancement Device Combination Therapy for Moderate-to-Severe Obstructive Sleep Apnea: A Preliminary Study

2021 ◽  
Author(s):  
Thyagaseely Sheela Premaraj ◽  
Jacob Stadiem ◽  
Shyamaly Arya Premaraj ◽  
Charles R. Davies ◽  
Matthew Dennis ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Daytime Sleepiness ◽  
Airway Pressure ◽  
Positive Airway Pressure ◽  
Mandibular Advancement Device ◽  
Mandibular Advancement ◽  
Severe Obstructive Sleep Apnea ◽  
Obstructive Sleep ◽  
The Mean

Abstract Objectives The purpose of this pilot study was to determine whether compliance to auto-adjusting positive airway pressure (APAP) improves with the addition of a mandibular advancement device (MAD). Secondary outcome measures included were APAP pressure, subjective daytime sleepiness, apnea–hypopnea index (AHI), and mask leaks. Setting and Sample Population Participants included were diagnosed with moderate-to-severe obstructive sleep apnea (OSA) and became noncompliant to prescribed APAP. Thirteen participants with a mean age of 61.6 years were recruited for this study. Materials and Methods All participants were given a MAD to use with their APAP. Parameters measured included APAP pressure, AHI, mask leak reported via ResMed AirViewTM software, and self-reported daytime sleepiness (Epworth Sleepiness Scale [ESS]). A paired two-sample for mean t-test was performed to determine significance. Results The mean difference of pre- and postintervention APAP compliance was 23.1%, which was statistically significant (p = 0.015). The mean APAP air pressures were unchanged. The difference between pre- and postintervention mean ESS scores was 1.4 and was statistically significant (p = 0.027). The mean difference between pre- and postintervention AHI values and mask leak showed no significant difference. Conclusion This study showed that combination of APAP-MAD therapy, for patients with moderate-to-severe OSA who were noncompliant to APAP use, significantly increased compliance with APAP therapy, and significantly decreased the daytime sleepiness of participants.

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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