Prevalence and associated factors of obstructive sleep apnea in morbidly obese patients undergoing bariatric surgery

Kositanurit, Weerapat; Muntham, Dittapol; Udomsawaengsup, Suthep; Chirakalwasan, Naricha

doi:10.1007/s11325-017-1500-y

Cited by 30 publications

(20 citation statements)

References 12 publications

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“…Obesity is recognized as a major risk for OSA and its prevalence is higher than 60% in the bariatric surgery population [40,41]. However, in this study, we found a lower prevalence of OSA (27%).…”

Section: Discussioncontrasting

confidence: 68%

Development and Validation of a Predictive Model of Success in Bariatric Surgery

et al. 2020

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Purpose There are no criteria to establish priority for bariatric surgery candidates in the public health system in several countries. The aim of this study is to identify preoperative characteristics that allow predicting the success after bariatric surgery. Materials and Methods Four hundred and sixty-one patients submitted to Roux-en-Y gastric bypass were included. Success of the surgery was defined as the sum of five outcome variables, assessed at baseline and 12 months after the surgery: excess weight loss, use of continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP) as a treatment for obstructive sleep apnea (OSA), daily number of antidiabetics, daily number of antihypertensive drugs, and all-cause mortality. Partial least squares (PLS) regression and multiple linear regression were performed to identify preoperative predictors. We performed a 90/10 split of the dataset in train and test sets and ran a leave-one-out cross-validation on the train set and the best PLS model was chosen based on goodness-of-fit criteria. Results The preoperative predictors of success after bariatric surgery included lower age, presence of non-alcoholic fatty liver disease and OSA, more years of CPAP/BiPAP use, negative history of cardiovascular disease, and lower number of antihypertensive drugs. The PLS model displayed a mean absolute percent error of 0.1121 in the test portion of the dataset, leading to accurate predictions of postoperative outcomes. Conclusion This success index allows prioritizing patients with the best indication for the procedure and could be incorporated in the public health system as a support tool in the decision-making process. Supplementary Information The online version contains supplementary material available at 10.1007/s11695-020-05103-0.

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Section: Discussioncontrasting

confidence: 68%

Development and Validation of a Predictive Model of Success in Bariatric Surgery

et al. 2020

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“…About 96% of our study population had OSA and about 75% were considered to have OSA of moderate or severe degree. The prevalence of OSA in the bariatric surgery population has been previously reported in the range 71% to 91% which means that our prevalence is in the upper level [18,31–33] probably depending on differences in study population composition. Our high prevalence number of OSA highlights the importance of screening for OSA.…”

Section: Discussionmentioning

confidence: 77%

A new sensitive and accurate model to predict moderate to severe obstructive sleep apnea in patients with obesity

et al. 2019

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Obstructive sleep apnea (OSA) has a high prevalence in patients with obesity. Only patients with clinical symptoms of OSA are admitted to polysomnography; however, many patients with OSA are asymptomatic. We aimed to create and validate a population-based risk score that predicts the severity of OSA in patients with obesity. We here report the cross-sectional analysis at baseline of an ongoing study investigating the long-term effect of bariatric surgery on OSA. One-hundred sixty-one patients of the Obesity Center of the Catholic University Hospital in Rome, Italy were included in the study. The patients underwent overnight cardiorespiratory monitoring, blood chemistry analyses, hepatic ultrasound, and anthropometric measurements. The patients were divided into 2 groups according OSA severity assessed by the apnea-hypopnea index (AHI): AHI < 15 = no or mild and AHI ≥ 15 moderate to severe OSA. A statistical prediction model was created and validated. C statistics was used to evaluate the discrimination performance of the model. The prevalence of OSA was 96.3% with 74.5% of the subjects having moderate/severe OSA. Sex, body mass index, diabetes, and age were included in the final prediction model that had excellent discrimination ability (C statistics equals to 83%). An OSA risk chart score for clinical use was created. Patients with severe obesity are at a very high risk for moderate or severe OSA in particular if they are men, older, more obese, and/or with type 2 diabetes. The OSA risk chart can be useful for general practitioners and patients as well as for bariatric surgeons to select patients with high risk of moderate to severe OSA for further polysomnography.

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“…The high prevalence of OSA is also expected due to the considerable frequency of obese people in this population (62.5%). The prevalence of apnea in obese individuals is increased, reaching 85.7% in obese class III patients who are awaiting bariatric surgery 40 .…”

Section: Discussionmentioning

confidence: 99%

Is subjective sleep evaluation a good predictor for obstructive sleep apnea?

Laranjeira¹,

Barbosa²,

Rabahi³

2018

Clinics

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OBJECTIVE:To compare subjective sleep evaluation obtained using four questionnaires with polysomnography results for individuals with and without obstructive sleep apnea.METHODS:Observational and analytical study in which individuals underwent polysomnography were studied retrospectively to investigate sleep disorders. We compared subjective data from a research database used to predict obstructive sleep apnea based on the STOP-BANG questionnaire, evaluation of excessive daytime sleepiness (Epworth Sleepiness Scale), sleep quality questionnaire (Mini Sleep Questionnaire) and Post-Sleep Data Collection Instrument with the self-reported total sleep time and sleep-onset latency for subjects with and without obstructive sleep apnea.RESULTS:The STOP-BANG questionnaire was a good predictor for the diagnosis of obstructive sleep apnea. However, the other instruments did not show a significant difference between healthy and sick individuals. Patients' perceptions of their sleep onset time were significantly lower than the polysomnographic data, but this difference remained for both subjects with and without obstructive sleep apnea. No difference was found between the subjective duration of sleep and the total sleep time assessed by polysomnography in either the healthy subjects or the patients.CONCLUSION:Except for the STOP-BANG questionnaire, subjective evaluation of sleepiness, sleep quality, perception of onset, and total sleep time are not important parameters for the diagnosis of obstructive sleep apnea, which reinforces the need for an active search for better management of these patients.

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Prevalence and associated factors of obstructive sleep apnea in morbidly obese patients undergoing bariatric surgery

Cited by 30 publications

References 12 publications

Development and Validation of a Predictive Model of Success in Bariatric Surgery

Development and Validation of a Predictive Model of Success in Bariatric Surgery

A new sensitive and accurate model to predict moderate to severe obstructive sleep apnea in patients with obesity

Is subjective sleep evaluation a good predictor for obstructive sleep apnea?

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