Negative Home Sleep Testing in Patients with High Risk Obstructive Sleep Apnea Characteristics

Author(s):  
M.L. Stanchina ◽  
S. Prenda ◽  
J. Lincoln ◽  
M. Holt ◽  
A. Bunch ◽  
...  
2019 ◽  
Author(s):  
Xiaojun Zhan ◽  
Chandala Chitguppi ◽  
Ethan Berman ◽  
Gurston Nyquist ◽  
Tomas Garzon-Muvdi ◽  
...  

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A166-A166
Author(s):  
Nathan Guess ◽  
Henry Fischbach ◽  
Andy Ni ◽  
Allen Firestone

Abstract Introduction The STOP-Bang Questionnaire is a validated instrument to assess an individual’s risk for obstructive sleep apnea (OSA). The prevalence of OSA is estimated at 20% in the US with only 20% of those individuals properly diagnosed. Dentists are being asked to screen and refer patients at high risk for OSA for definitive diagnosis and treatment. The aim of this study was to determine whether patients in a dental school student clinic who were identified as high-risk for OSA, were referred for evaluation of OSA. Methods All new patients over the age of 18 admitted to The Ohio State University - College of Dentistry complete an “Adult Medical History Form”. Included in this study were 21,312 patients admitted between July 2017 and March 2020. Data were extracted from the history form to determine the STOP-Bang Score for all patients: age, sex, BMI, self-reported snoring-, stopped breathing/choking/gasping while sleeping-, high blood pressure-, neck size over 17” (males) or 16” (females)-, and tiredness. Each positive response is a point, for a maximum of 8 points possible. Additionally, any previous diagnosis of sleep apnea, and the patient’s history of referrals were extracted from the health record. According to clinic policy, if the patient did not have a previous diagnosis for OSA noted in the health history, and scored 5 or more on the STOP-Bang Questionnaire, they should receive a referral for an evaluation for OSA. Notes and referral forms were reviewed to determine if the appropriate referrals occurred for patients at high risk without a previous diagnosis. Results Of the 21,312 patients screened; 1098 (5.2%) screened high-risk for OSA, of which 398 had no previous diagnosis of OSA. Of these 398 patients, none (0%) had referrals for further evaluation for OSA. Conclusion The rate of appropriate referrals from a student dental clinic with an electronic health record was unacceptably low. Continued education and changes to the electronic health record are needed to ensure those at high-risk for OSA are appropriately referred and managed. Support (if any):


SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A189-A190
Author(s):  
Miguel Meira e Cruz ◽  
Luana Seixas ◽  
Augusto Santos ◽  
João Garrido ◽  
Yuri Lopes ◽  
...  

Abstract Introduction Only few studies looked for a possible association of cardiovascular disorders (CVD), in comorbid insomnia with obstructive sleep apnea (COMISA) even though this is a relevant topic in order to prevent one of the major causes of morbimortality. The present study aimed to investigate the association of insomnia symptoms in patients at risk for obstructive sleep apnea in terms of prevalence and clinical interactions and to evaluate the risk of CVD in patients with a risk for COMISA. Methods This is a cross-sectional study. All medical records with data such as age, sex, height, weight and BMI, time to sleep, time to wake up, total sleep time, the Epworth Sleepiness Scale (ESS), STOP-BANG Questionnaires were studied. Insomnia and comorbidities were also investigated, and the patientsanswered yes or no to systemic arterial hypertension, diabetes, CVD. Results 685 patients were enrolled on the present study. We observed that the mild, moderate, and high risk for COMISA presented progressively increasing levels for the frequency of hypertension, diabetes, and CVD. A binary logistic regression was performed to assess whether risk for COMISA could be a predictor for CVD, and it was found that the model containing risk for COMISA was statistically significant: [x2(1)=5.273;p<0.021, R2 Negelkerke=0.014]. Risk for COMISA presented itself as a significant predictor for CVD (OR=1.672; 95% CI=1.079–2.592). Conclusion There was an increased frequency of associated comorbidities such as CVD, systemic arterial hypertension, and diabetes, according to the mild, moderate, or high risk. These findings highlight the need for a cardiometabolic evaluation in patients with this comorbid condition which may impact prognosis and therapeutic success. Support (if any):


2011 ◽  
Vol 12 (4) ◽  
pp. P27
Author(s):  
R. Hamill-Ruth ◽  
A. Kipp ◽  
R. Rome ◽  
E. Gochenour

2017 ◽  
Vol 3 (1) ◽  
pp. 16-21
Author(s):  
Karina Woodling ◽  
Juan Fiorda-Diaz ◽  
Bradley A. Otto ◽  
Christie A. Barnes ◽  
Alberto A. Uribe ◽  
...  

Author(s):  
Suwen Kumar ◽  
Benjamin Ebner ◽  
Jeniffer Bragg-Gresham ◽  
Peter Farrehi ◽  
Sharlene Day

Background: Prevalence of obstructive sleep apnea (OSA) in hypertrophic cardiomyopathy (HCM) is estimated between 32% and 71%. Individuals with HCM and OSA have increased blood pressure, BMI, , ascending aorta size, left atrial size, left ventricular end diastolic diameter, E/e’ ratio, atrial fibrillation rates and NYHA functional class. It has been suggested that treatment of OSA can decrease the need for septal reduction. However, studies have found no effect of OSA on septal thickness or outflow gradient. It is not known how OSA affects exercise performance or cardiac remodeling assessed by MR. Genetic propensity toward OSA in HCM has not been reported. We propose that OSA predicts decrease exercise tolerance and that cardiac remodeling could be identified using MR. We sought to report on HCM genotype in OSA as well as compare our clinical and echo data with other investigators. Methods: Subjects were identified through our institution’s HCM database. They were surveyed using the STOP-BANG (SB) questionnaire, a validated questionnaire to identify individuals at high risk for OSA. We stratified patients into high risk (HR) and low risk (LR) groups, based on a cut point of greater than or equal to 3 on SB. Demographics and clinical characteristics were extracted from our database. Prevalence and means were compared between the two groups, using Chi-square and t-tests. Differences between the groups were adjusted for age, sex, and BMI using linear mixed models for continuous measures and logistic regression for dichotomous measures. Results: There were 206 respondents, of those 160 (78%) scored high risk for OSA, 60 of which had a history of polysomnogram (PSG) confirming OSA. Having a HR vs. LR SB was associated with a significantly greater likelihood of stroke, CHF hospitalization, NYHA functional class >2, reduced peak VO2, reduced anaerobic threshold and increased LA diameter. Adjusted comparisons for age, gender, and BMI showed that had significantly higher PAWP and LV mass index. Of those with a prior diagnosis of OSA we compared therapy compliant and non-compliant individuals and found they differed on LV mass index (HR=98.7 g/m2 vs. LR=62.0 g/m2, p=0.01). Conclusions: OSA occurs frequently in HCM and is associated with decreased exercise tolerance, worse hemodynamics, poor outcome as well as increased LV mass, which may be attenuated by therapy. OSA is an important and modifiable risk factor in HCM. Prospective evaluation utilizing PSG based diagnosis and positive pressure therapy is warranted.


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