Abstract 41: Stroke Unit Evaluation of Sleep Apnea: Validity of Screening Tools and Use of a Portable Sleep Study

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Hugo J Aparicio ◽  
Tudor Sturzoiu ◽  
Helena W Lau ◽  
Judith Clark ◽  
Julie Grimes ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Stroke Unit ◽  
Central Sleep Apnea ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Berlin Questionnaire ◽  
Validity And Reliability ◽  
Sleep Study ◽  
Obstructive Sleep

Background: Despite high prevalence in the stroke population, sleep apnea is underdiagnosed. Obstructive sleep apnea is associated with poor cardiovascular outcomes and treatment with continuous positive airway pressure has been shown to lower blood pressure. No standard exists for screening patients who present to the hospital with acute stroke. We assessed three screening tools, the Epworth Sleepiness Scale (ESS), Berlin Questionnaire (BQ), and STOP-BANG Questionnaire (STOP-BANG), along with the use of a portable sleep study device for evaluation of sleep apnea. Overnight polysomnography (PSG) was performed on a subset of patients on outpatient follow up. Methods: Patients admitted to the stroke unit at our hospital, over nine months, were screened for sleep apnea using the three instruments, ESS, BQ, and STOP-BANG. The patients were evaluated with a portable sleep study device, ApneaLink Air (ResMed, USA), prior to discharge. Respiratory effort, respiratory flow, pulse oximetry, and oxygen saturation were recorded and sleep apnea was determined by apnea-hypopnea index (AHI) ≥ 5. Predictions from the screening tools were compared to the portable sleep study and overnight PSG results. Sensitivity and specificity testing were used to assess the validity and reliability of the tools. Results: Sleep questionnaires were administered on 37 patients who underwent an overnight sleep study. Portable studies were used to evaluate 33 patients, and 13 PSGs were performed. Obstructive sleep apnea was diagnosed in 20 (69%) and central sleep apnea in 9 (31%). Cheyne-Stokes pattern breathing was observed in 2 (5%). Mean AHI was 18.3 + 21.8/hr and maximum AHI was 105.8/hr. Sensitivity for the ESS, BQ, and STOP-BANG were 0.39, 0.66, and 0.83 and specificity for these tools were 0.26, 0.33, and 0.29, respectively. In patients who underwent the portable sleep study and overnight PSG, 9/10 (90%) of the studies were concordant. Conclusions: The STOP-BANG questionnaire, administered to hospitalized stroke patients, had high sensitivity and low-moderate specificity in our study, compared to two other commonly used screening tools. Further, the feasibility of using an unattended inpatient portable sleep study on stroke inpatients is demonstrated.

0611 Screening for Obstructive Sleep Apnea in the Bariatric Surgery Population

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A234-A234
Author(s):  
K Kreitinger ◽  
M M Lui ◽  
R Owens ◽  
C Schmickl ◽  
E Grunvald ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Statistical Significance ◽  
Preoperative Evaluation ◽  
Standard Of Care ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Obstructive Sleep

Abstract Introduction Obstructive sleep apnea (OSA) is prevalent in the bariatric surgery population and has been associated with increased perioperative risk, especially if OSA is moderate-severe (apnea-hypopnea index ≥ 15/h). Consequently, screening for OSA is recommended as part of the preoperative evaluation. Several screening tools for OSA have been developed; however, some tools lack validation and their relative performance is unclear. The purpose of this study was to compare four existing screening tools (Epworth Sleepiness Scale (ESS), STOP-BANG, NO-OSAS, and No-Apnea) with regards to the ability to identify patients with moderate-severe OSA among bariatric surgery patients. Methods We retrospectively reviewed data from Jan 2015 to Mar 2019 for adult patients presenting consecutively to UC San Diego for first-time bariatric surgery who had undergone a home or in-lab sleep study (within one year of the initial encounter for bariatric surgery), which is our standard of care. We compared the accuracy of the four screening tools for detecting moderate-severe OSA based on the area under the receiver operating characteristic curves (AUC). Subgroup analyses were explored based on sex, BMI, and ethnicity (Hispanic/Latino vs non-Hispanic/Latino). Results Of the 214 patients (83.2% female, median age 39 years) included in the study, 45.4% had moderate-severe OSA. STOP-BANG (AUC 0.75 [95%CI: 0.68 to 0.81]) and NO-OSAS (AUC 0.76 [95%CI: 0.69 to 0.82]) had similar performance (p 0.62); both performed significantly better than the ESS (AUC 0.61 [95%CI: 0.54 to 0.68]; p 0.02 for both). STOP-BANG and NO-OSAS tended to perform better in the female vs male subgroup, but this finding did not reach statistical significance. Conclusion STOP-BANG and NO-OSAS are superior to the ESS when screening bariatric surgery patients for moderate-severe OSA. In future analyses we will further explore if adjustments of standard cut-offs improve test characteristics (i.e. sensitivity/specificity) when screening bariatric surgery patients (analyses ongoing). Support None.

scholarly journals Validation of the Berlin Questionnaire and American Society of Anesthesiologists Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients

2008 ◽  
Vol 108 (5) ◽  
pp. 822-830 ◽  
Author(s):  
Frances Chung ◽  
Balaji Yegneswaran ◽  
Pu Liao ◽  
Sharon A. Chung ◽  
Santhira Vairavanathan ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
High Risk ◽  
Screening Tools ◽  
Surgical Patients ◽  
Apnea Hypopnea Index ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
American Society ◽  
American Society Of Anesthesiologists ◽  
Stop Questionnaire

Background Because of the high prevalence of obstructive sleep apnea (OSA) and its adverse impact on perioperative outcome, a practical screening tool for surgical patients is required. This study was conducted to validate the Berlin questionnaire and the American Society of Anesthesiologists (ASA) checklist in surgical patients and to compare them with the STOP questionnaire. Methods After hospital ethics approval, preoperative patients aged 18 yr or older and without previously diagnosed OSA were recruited. The scores from the Berlin questionnaire, ASA checklist, and STOP questionnaire were evaluated versus the apnea-hypopnea index from in-laboratory polysomnography. The perioperative data were collected through chart review. Results Of 2,467 screened patients, 33, 27, and 28% were respectively classified as being at high risk of OSA by the Berlin questionnaire, ASA checklist, and STOP questionnaire. The performance of the screening tools was evaluated in 177 patients who underwent polysomnography. The sensitivities of the Berlin questionnaire, ASA checklist, and STOP questionnaire were 68.9-87.2, 72.1-87.2, and 65.6-79.5% at different apnea-hypopnea index cutoffs. There was no significant difference between the three screening tools in the predictive parameters. The patients with an apnea-hypopnea index greater than 5 and the patients identified as being at high risk of OSA by the STOP questionnaire or ASA checklist had a significantly increased incidence of postoperative complications. Conclusions Similar to the STOP questionnaire, the Berlin questionnaire and ASA checklist demonstrated a moderately high level of sensitivity for OSA screening. The STOP questionnaire and the ASA checklist were able to identify the patients who were likely to develop postoperative complications.

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 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.

393 Comparison of Oxygenation Abnormalities Between Obstructive Sleep Apnea and Central Sleep Apnea

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A156-A157
Author(s):  
Sikawat Thanaviratananich ◽  
Hao Cheng ◽  
Maria Pino ◽  
Krishna Sundar
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Demographic Data ◽  
Central Sleep Apnea ◽  
Nrem Sleep ◽  
Rate Of Change ◽  
Apnea Hypopnea Index ◽  
P Value ◽  
Obstructive Sleep ◽  
Cheyne Stokes Breathing

Abstract Introduction The apnea-hypopnea index (AHI) is used as a generic index to quantify both central sleep apnea (CSA) and obstructive sleep apnea (OSA) syndromes. Patterns of oxygenation abnormalities seen in CSA and OSA may be key to understanding differing clinical impacts of these disorders. Oxygen desaturation and resaturation slopes and durations in OSA and CSA were compared between OSA and CSA patients. Methods Polysomnographic data of patients aged 18 years or older with diagnosis of OSA and CSA, at University of Iowa Hospitals and Clinics, were analyzed and demographic data were collected. Oximetric changes during hypopneas and apneas were studied for desaturation/resaturation durations and desaturation/resaturation slopes. Desaturation and resaturation slopes were calculated as rate of change in oxygen saturation (ΔSpO2/Δtime). Comparison of hypoxemia-based parameters between patients with OSA and CSA was performed using unpaired t-test. Results 32 patients with OSA with median AHI of 15.4 (IQR 5.1 to 30.55) and median ODI of 15.47 (IQR 9.50 to 29.33) were compared to 15 patients with CSA with a median AHI of 20.4 (IQR 12.6 to 47.8) and median ODI of 27.56 (IQR 17.99 to 29.57). The mean number of desaturation and resaturation events was not significantly different between patients with OSA and CSA (OSA - 106.81±87.93; CSA - 130.67±76.88 with a p-value 0.1472). 4/15 CSA patients had Cheyne-Stokes breathing, 2/15 had treatment emergent central sleep apnea, 1/15 had methadone-associated CSA and for 8/15, no etiologies for CSA were found. Mean desaturation durations was significantly longer in OSA (20.84 s ± 5.67) compared to CSA (15.94 s ± 4.54) (p=0.0053) and consequently the desaturation slopes were steeper in CSA than OSA (-0.35%/sec ±0.180 vs. -0.243 ± 0.073; p=0.0064). The resaturation duration was not significantly longer in OSA (9.76 s ± 2.02) than CSA (9.057 s ± 2.17) (p=0.2857). Differences between desaturation duration and slopes between CSA and OSA persisted during REM and NREM sleep, and in supine sleep. Conclusion As compared to OSA, patients with CSA have different patterns of desaturations and resaturations with lesser hypoxic burden with CSA. This may have implications on the clinical outcomes seen between these two disorders. Support (if any):

scholarly journals Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258040
Author(s):  
Eric Yeh ◽  
Eileen Wong ◽  
Chih-Wei Tsai ◽  
Wenbo Gu ◽  
Pai-Lien Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Physiological Data ◽  
Apnea Hypopnea Index ◽  
Clinical Practices ◽  
Sleep Study ◽  
Link Type ◽  
Obstructive Sleep ◽  
Sensitivity Specificity

Many wearables allow physiological data acquisition in sleep and enable clinicians to assess sleep outside of sleep labs. Belun Sleep Platform (BSP) is a novel neural network-based home sleep apnea testing system utilizing a wearable ring device to detect obstructive sleep apnea (OSA). The objective of the study is to assess the performance of BSP for the evaluation of OSA. Subjects who take heart rate-affecting medications and those with non-arrhythmic comorbidities were included in this cohort. Polysomnography (PSG) studies were performed simultaneously with the Belun Ring in individuals who were referred to the sleep lab for an overnight sleep study. The sleep studies were manually scored using the American Academy of Sleep Medicine Scoring Manual (version 2.4) with 4% desaturation hypopnea criteria. A total of 78 subjects were recruited. Of these, 45% had AHI < 5; 18% had AHI 5–15; 19% had AHI 15–30; 18% had AHI ≥ 30. The Belun apnea-hypopnea index (bAHI) correlated well with the PSG-AHI (r = 0.888, P < 0.001). The Belun total sleep time (bTST) and PSG-TST had a high correlation coefficient (r = 0.967, P < 0.001). The accuracy, sensitivity, specificity in categorizing AHI ≥ 15 were 0.808 [95% CI, 0.703–0.888], 0.931 [95% CI, 0.772–0.992], and 0.735 [95% CI, 0.589–0.850], respectively. The use of beta-blocker/calcium-receptor antagonist and the presence of comorbidities did not negatively affect the sensitivity and specificity of BSP in predicting OSA. A diagnostic algorithm combining STOP-Bang cutoff of 5 and bAHI cutoff of 15 events/h demonstrated an accuracy, sensitivity, specificity of 0.938 [95% CI, 0.828–0.987], 0.944 [95% CI, 0.727–0.999], and 0.933 [95% CI, 0.779–0.992], respectively, for the diagnosis of moderate to severe OSA. BSP is a promising testing tool for OSA assessment and can potentially be incorporated into clinical practices for the identification of OSA. Trial registration: ClinicalTrial.org NCT03997916 https://clinicaltrials.gov/ct2/show/NCT03997916?term=belun+ring&draw=2&rank=1

scholarly journals Cardiorespiratory Polygraphy for Detection of Obstructive Sleep Apnea in Patients With Atrial Fibrillation

2021 ◽  
Vol 8 ◽  
Author(s):  
Michiel Delesie ◽  
Lieselotte Knaepen ◽  
Johan Verbraecken ◽  
Karolien Weytjens ◽  
Paul Dendale ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Screening Tool ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Apnea Hypopnea Index ◽  
Automated Algorithm ◽  
Obstructive Sleep ◽  
At Home

Background: Obstructive sleep apnea (OSA) is a modifiable risk factor of atrial fibrillation (AF) but is underdiagnosed in these patients due to absence of good OSA screening pathways. Polysomnography (PSG) is the gold standard for diagnosing OSA but too resource-intensive as a screening tool. We explored whether cardiorespiratory polygraphy (PG) devices using an automated algorithm for Apnea-Hypopnea Index (AHI) determination can meet the requirements of a good screening tool in AF patients.Methods: This prospective study validated the performance of three PGs [ApneaLink Air (ALA), SOMNOtouch RESP (STR) and SpiderSAS (SpS)] in consecutive AF patients who were referred for PSG evaluation. Patients wore one of the three PGs simultaneously with PSG, and a different PG during each of three consecutive nights at home. Severity of OSA was classified according to the AHI during PSG (&lt;5 = no OSA, 5–14 = mild, 15–30 = moderate, &gt;30 = severe).Results: Of the 100 included AF patients, PSG diagnosed at least moderate in 69% and severe OSA in 33%. Successful PG execution at home was obtained in 79.1, 80.2 and 86.8% of patients with the ALA, STR and SpS, respectively. For the detection of clinically relevant OSA (AHI ≥ 15), an area under the curve of 0.802, 0.772 and 0.803 was calculated for the ALA, STR and SpS, respectively.Conclusions: This study indicates that home-worn PGs with an automated AHI algorithm can be used as OSA screening tools in AF patients. Based on an appropriate AHI cut-off value for each PG, the device can guide referral for definite PSG diagnosis.

scholarly journals 0936 Sleep Disturbances in Wolfram Syndrome

SLEEP ◽  
2019 ◽  
Vol 42 (Supplement_1) ◽  
pp. A376-A377
Author(s):  
Amy K Licis ◽  
Gabriel Davis ◽  
Sarah Eisenstein ◽  
Heather Lugar ◽  
Tamara Hershey
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Quality ◽  
Rating Scale ◽  
Wolfram Syndrome ◽  
High Rate ◽  
Apnea Hypopnea Index ◽  
Diabetes Research ◽  
Sleep Study ◽  
Obstructive Sleep

Abstract Introduction Wolfram syndrome is a rare disorder associated with diabetes mellitus, diabetes insipidus, optic nerve atrophy, hearing and vision loss, and neurodegeneration. Sleep complaints are common but have not been studied with objective measures. Our goal was to assess rates of sleep apnea and objective and self-reported measures of sleep quality, and to determine the relationship of sleep pathology to other clinical variables in Wolfram syndrome patients. Methods Genetically confirmed Wolfram syndrome patients were evaluated at the 2015 and 2016 Washington University Wolfram Syndrome Research Clinics. Patients wore an actigraphy device and a type III ambulatory sleep study device and completed the Epworth Sleepiness Scale (ESS), the Pittsburgh Sleep Quality Index (PSQI) and/or the Pediatric Sleep Questionnaire (PSQ). PSQI and PSQ questionnaire data were compared to a previously collected group of controls. Patients were characterized clinically with the Wolfram Unified Rating Scale (WURS) and a subset underwent magnetic resonance imaging (MRI) for brain volume measurements. Results Twenty-one patients were evaluated ranging from age 8.9 - 29.7 years. Five of 17 (29%) adult patients fit the criteria for obstructive sleep apnea (OSA; apnea-hypopnea index [AHI] ≥ 5) and all 4 of 4 (100%) children aged 12 years or younger fit the criteria for obstructive sleep apnea (AHI’s ≥1). Higher AHI was related to greater disease severity (higher WURS Physical scores). Higher mixed apnea scores were related to lower brainstem and cerebellar volumes. Patients’ scores on the PSQ were higher than those of controls, indicating greater severity of childhood obstructive sleep-related breathing disorders. Conclusion Wolfram syndrome patients had a high rate of OSA. Further study would be needed to assess how these symptoms change over time. Addressing sleep disorders in Wolfram syndrome patients would likely improve their overall health and quality of life. Support (If Any) This work was supported by the NICHD (HD070855; Hershey, PI) and supported by CTSA (UL1 RR024992) and Diabetes Research Center (DK 020579).

scholarly journals Obstructive Sleep Apnea, Sleep Duration, and Associated Mediators With Carotid Intima-Media Thickness

2021 ◽  
Author(s):  
Silvana P. Souza ◽  
Ronaldo B. Santos ◽  
Itamar S. Santos ◽  
Barbara K. Parise ◽  
Soraya Giatti ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Intima Media Thickness ◽  
Carotid Intima Media Thickness ◽  
R Package ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Media Thickness ◽  
Obstructive Sleep

Objective: To elucidate the independent associations of obstructive sleep apnea (OSA) and sleep duration (SD) as well as the potential inflammatory and metabolic mediators on carotid intima-media thickness (CIMT) in a large cohort of adults. Approach and Results: Consecutive participants from the ELSA-Brasil performed a clinical evaluation, sleep study, 1-week actigraphy for defining SD and CIMT using standard techniques. Gamma regression models were used to explore the association between OSA and SD with CIMT. Mediation analysis was performed using the mediation R package. A total of 2009 participants were included in the main analysis. As compared with no OSA (apnea-hypopnea index [AHI] <5 events/hour; n=613), patients with mild (AHI, 5–14.9; n=741), moderate (AHI, 15–29.9; n=389), and severe OSA (AHI ≥30 events/hour; n=266) presented a progressive CIMT increase (0.690 [0.610–0.790], 0.760 [0.650–0.890], 0.810 [0.700–0.940], and 0.820 [0.720–0.958] mm; P <0.001). In contrast, CIMTs were similar for those with SD <6 hours (0.760 [0.650–0.888]), 6 to 8 hours (0.750 [0.640–0.880]) and >8 hours (0.740 [0.670–0.900]). All forms of OSA were independently associated with CIMT (mild: β: 0.019, SE 0.008; P =0.022; moderate: β: 0.025, SE 0.011; P =0.022; severe OSA: β: 0.040, SE 0.013; P =0.002). Moreover, the association of AHI with CIMT was mediated by increased C-reactive protein and triglycerides ( P <0.01). SD did not interact with OSA in the association with CIMT. Conclusions: OSA is independently associated with increased CIMT in a dose-response relationship. This association is partially mediated by inflammation and dyslipidemia. In contrast, SD is not associated nor interacted with OSA to increase CIMT.

scholarly journals Prospective Screening for Primary Aldosteronism in Patients With Suspected Obstructive Sleep Apnea

Hypertension ◽  
2021 ◽  
Author(s):  
Min Ru Chee ◽  
Jesse Hoo ◽  
Renata Libianto ◽  
Stella M. Gwini ◽  
Garun Hamilton ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Primary Aldosteronism ◽  
Blood Pressure Monitoring ◽  
Apnea Hypopnea Index ◽  
Hypertension Status ◽  
Antihypertensive Medications ◽  
Sleep Study ◽  
Obstructive Sleep

Several studies have demonstrated a bidirectional relationship between obstructive sleep apnea and primary aldosteronism (PA); however, many of these studies are limited to patients with known obstructive sleep apnea, hypertension, or PA. We evaluated the role of screening for PA in all patients referred for a diagnostic sleep study without selecting for prior diagnoses with these conditions. Plasma aldosterone and renin concentration were measured after an overnight polysomnography. Blood pressure was measured at the sleep center for all patients, while a proportion underwent 24-hour blood pressure monitoring. Of the 85 participating patients, 2 (2.4%) were identified to have likely PA based on an elevated aldosterone:renin ratio and/or clinical characteristics. Another 10 (11.8%) were identified to have possible PA based on their low or normal plasma renin concentration despite taking antihypertensive medications that are known to elevate renin. In participants with both obstructive sleep apnea and hypertension (n=40), the prevalence of likely or possible PA was 30%. However, there was no correlation between aldosterone, rennin, or aldosterone:renin ratio and the apnea-hypopnea index using multiple regression analysis adjusted for interfering medications and hypertension status. The observed high prevalence of possible PA among those with both hypertension and obstructive sleep apnea suggests that they should be routinely screened for PA.

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