Alcohol as an independent risk factor for obstructive sleep apnea

Yang, Shanshan; Guo, Xiaotong; Liu, Wei; Lǐ, Yànhuá; Liu, Yunxi

doi:10.1007/s11845-021-02671-7

Cited by 19 publications

(14 citation statements)

References 18 publications

(11 reference statements)

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“…The AASM recommends initiating PAP therapy for these patients before considering surgery because of the low risk of PAP therapy compared with surgery 21. Avoiding alcohol—which affects muscle tone and can contribute to a compromised upper airway—also can reduce the AHI 22…”

Section: Managementmentioning

confidence: 99%

“…21 Avoiding alcoholwhich affects muscle tone and can contribute to a compromised upper airway-also can reduce the AHI. 22 Oral appliances are recommended for patients who are intolerant of PAP. 23 These devices require dentist evaluation for custom fitting and are designed to keep the airway open during sleep by protruding the tongue and mandible to facilitate increased diameter of the upper airway.…”

Section: Managementmentioning

confidence: 99%

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A clinical review of obstructive sleep apnea

Sisson

2023

Jaapa

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Section: Managementmentioning

confidence: 99%

Section: Managementmentioning

confidence: 99%

A clinical review of obstructive sleep apnea

Sisson

2023

Jaapa

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“…Furthermore, increased caffeine usage has been found to be linked with difficulty falling asleep, decreased time falling asleep, and decreased quality of sleep [63]. Additionally, increased alcohol is associated with sleep disorders, leading to decreased sleep latency and potential physiologic need for alcohol as a depressant to allow for sleep in multiple patients [64][65][66].…”

Section: Plos Onementioning

confidence: 99%

Use of machine learning to identify risk factors for insomnia

Huang

2023

PLoS ONE

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Importance Sleep is critical to a person’s physical and mental health, but there are few studies systematically assessing risk factors for sleep disorders. Objective The objective of this study was to identify risk factors for a sleep disorder through machine-learning and assess this methodology. Design, setting, and participants A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES) was conducted in patients who completed the demographic, dietary, exercise, and mental health questionnaire and had laboratory and physical exam data. Methods A physician diagnosis of insomnia was the outcome of this study. Univariate logistic models, with insomnia as the outcome, were used to identify covariates that were associated with insomnia. Covariates that had a p<0.0001 on univariate analysis were included within the final machine-learning model. The machine learning model XGBoost was used due to its prevalence within the literature as well as its increased predictive accuracy in healthcare prediction. Model covariates were ranked according to the cover statistic to identify risk factors for insomnia. Shapely Additive Explanations (SHAP) were utilized to visualize the relationship between these potential risk factors and insomnia. Results Of the 7,929 patients that met the inclusion criteria in this study, 4,055 (51% were female, 3,874 (49%) were male. The mean age was 49.2 (SD = 18.4), with 2,885 (36%) White patients, 2,144 (27%) Black patients, 1,639 (21%) Hispanic patients, and 1,261 (16%) patients of another race. The machine learning model had 64 out of a total of 684 features that were found to be significant on univariate analysis (P<0.0001 used). These were fitted into the XGBoost model and an AUROC = 0.87, Sensitivity = 0.77, Specificity = 0.77 were observed. The top four highest ranked features by cover, a measure of the percentage contribution of the covariate to the overall model prediction, were the Patient Health Questionnaire depression survey (PHQ-9) (Cover = 31.1%), age (Cover = 7.54%), physician recommendation of exercise (Cover = 3.86%), weight (Cover = 2.99%), and waist circumference (Cover = 2.70%). Conclusion Machine learning models can effectively predict risk for a sleep disorder using demographic, laboratory, physical exam, and lifestyle covariates and identify key risk factors.

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“…Alcohol also prolongs respiratory event duration by delaying arousal and is an important source of calories. Active treatment of OSA can be significantly affected by the amount of alcohol intake [5,6]. Sedatives, like benzodiazepines and Z-drugs can have adverse effects in some OSA patients, but do not necessarily increase the apnoea-hypopnoea index (AHI), while improving sleep efficiency and inducing no adverse consequences on alertness the day after [7].…”

Section: Lifestyle Modification (Behavioural Therapy)mentioning

confidence: 99%

Non-CPAP therapy for obstructive sleep apnoea

Verbraecken

Dieltjens

Beeck

et al. 2022

Breathe

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Treatment of obstructive sleep apnoea in adults is evolving, from a “one treatment fits all” to a more individualised approach. The spectrum of treatment options is broad and heterogeneous, including conservative, technological and pharmaceutical modalities. This raises the questions of which patients these modalities might be useful for, and if there are specific criteria for single or combined treatment. The most commonly used non-CPAP treatment is a mandibular advancement device. Furthermore, it appears from the available evidence that upper airway surgery, bariatric surgery, and maxillomandibular advancement can be effective in particular patient groups and should be indicated more readily in clinical practice. Technically, a tracheotomy is the most effective surgical treatment, but is not socially acceptable and is associated with major side-effects. Other treatment options are emerging, like positional therapy, hypoglossal nerve stimulation, and myofunctional exercises. Drug therapy is also promising when pathophysiological traits are considered.The range of currently available treatment options will be discussed in this review, with emphasis on the selection of appropriate patients, therapeutic efficacy and compliance, and reference to recent guidelines. In the selection process, routine application of drug-induced sleep endoscopy to assess the site(s) of collapse during sleep can increase the success rate of both surgical interventions and oral appliance therapy.Educational aimsTo outline recommendations concerning the proper management of obstructive sleep apnoea (OSA) patients that cannot be treated adequately with continuous positive airway pressure (CPAP) due to intolerance, poor adherence or compliance, or CPAP refusal.To provide information about the selection of appropriate patients for alternative non-CPAP treatment options.To better understand the different aspects of OSA treatment with noninvasive approaches, such as oral appliances, positional therapy, drug treatment and myofunctional therapy, including indications, contraindications, and expected short- and long-term results.To discuss the different surgical options for the treatment of OSA and to provide information on the important issue of proper patient selection for surgery, as most OSA surgical outcomes are associated with the pre-operative assessment of the level(s) of upper airway collapse.

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Alcohol as an independent risk factor for obstructive sleep apnea

Cited by 19 publications

References 18 publications

A clinical review of obstructive sleep apnea

A clinical review of obstructive sleep apnea

Use of machine learning to identify risk factors for insomnia

Non-CPAP therapy for obstructive sleep apnoea

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