Excessive Daytime Sleepiness in Depression and Obstructive Sleep Apnea: More Than Just an Overlapping Symptom

Zhang, Dan‐Wei; Zhang, Zhen; Li, Huihua; Ding, Kaimo

doi:10.3389/fpsyt.2021.710435

Cited by 18 publications

(15 citation statements)

References 60 publications

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“…OSA cases include the repeated occurrence of hypoxemia, hypercapnia, and sleep structure disorders at night, along with well-accepted related damages, such as cardiovascular, cerebrovascular, and metabolic dysfunctions ( 1 ). Understanding the potential pathological contributions of OSA to cancers, depression, and asthma can also update our knowledge of its biological effects ( 2 , 3 ). In addition, a previous cross-sectional study involving 3,303 subjects showed that OSA was an independent risk factor for dry eye disease (DED) ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

Association between poor sleep quality and an increased risk of dry eye disease in patients with obstructive sleep apnea syndrome

Wu²,

Li³

et al. 2022

Front. Med.

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PurposeObstructive sleep apnea (OSA) is related to an increased incidence of dry eye disease (DED). However, their exact relationship is unknown and requires further well-designed studies with advanced mechanisms detection.Patients and methodsThis case–control study included 125 OSA cases and 125 age–gender-matched controls enrolled in the hospital between 1 January and 1 October 2021. OSA diagnosis and classification were performed using a polysomnography (PSG) assay. Detailed ophthalmological examinations, including the Schirmer I test, corneal staining, and ocular surface disease index (OSDI), were used to detect DED-related parameters. A comprehensive ocular surface assay was performed to measure a series of parameters, including first non-invasive first tear film break-up time (f-NIBUT), average non-invasive first tear film break-up time (av-NIBUT), tear meniscus height (TMH), and loss of meibomian gland. In addition, the Pittsburgh Sleep Quality Index (PSQI) scale was used to assess sleep quality.ResultsCompared to the control, the OSA group showed an increased DED risk (P = 0.016) along with an increased PSQI score and a higher rate of poor quality sleep (P < 0.001 and P = 0.007, respectively). Stratification of OSA cases indicated that DED-related parameters were impaired in patients with severe OSA (P < 0.05). The analysis of DED-parameters-related factors showed significant correlations between OSA-related indexes and PSQI (P < 0.05). Moreover, the poor sleep quality group in the OSA cases showed worse DED-related parameters (P < 0.05), which was not observed in the control group.ConclusionOSA, especially the severe stage OSA, was related to an increased risk of DED. Also, sleep quality was correlated with the onset of both OSA and DED, where poor sleep quality revealed a relationship between OSA and the risk of DED. Overall, our findings provided evidence for advanced management of DED and OSA in future.

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Section: Introductionmentioning

confidence: 99%

Association between poor sleep quality and an increased risk of dry eye disease in patients with obstructive sleep apnea syndrome

Wu²,

Li³

et al. 2022

Front. Med.

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“…Given the known protective effects of smoking for PD [24] and increased PD risk due to physical inactivity and depression [25,26], these often co-occurring factors may have opposing effects for individual PD risk estimates. Excessive daytime somnolence has been shown to be both a risk factor for depression as well as a frequent comorbid factor in depressed individuals, supporting their interdependency observed in the BN [27]. Diabetes received interesting edges from several nodes including SN hyperechogenicity, global cognitive deficits, sex and PD family history, and while their confidences were low, this finding might provide new hypotheses regarding biological prodromal mechanisms to be tested in future studies.…”

Section: Plos Onementioning

confidence: 72%

Bayesian network modeling of risk and prodromal markers of Parkinson’s disease

Sood

Suenkel²,

Thaler³

et al. 2023

PLoS ONE

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Parkinson’s disease (PD) is characterized by a long prodromal phase with a multitude of markers indicating an increased PD risk prior to clinical diagnosis based on motor symptoms. Current PD prediction models do not consider interdependencies of single predictors, lack differentiation by subtypes of prodromal PD, and may be limited and potentially biased by confounding factors, unspecific assessment methods and restricted access to comprehensive marker data of prospective cohorts. We used prospective data of 18 established risk and prodromal markers of PD in 1178 healthy, PD-free individuals and 24 incident PD cases collected longitudinally in the Tübingen evaluation of Risk factors for Early detection of NeuroDegeneration (TREND) study at 4 visits over up to 10 years. We employed artificial intelligence (AI) to learn and quantify PD marker interdependencies via a Bayesian network (BN) with probabilistic confidence estimation using bootstrapping. The BN was employed to generate a synthetic cohort and individual marker profiles. Robust interdependencies were observed for BN edges from age to subthreshold parkinsonism and urinary dysfunction, sex to substantia nigra hyperechogenicity, depression, non-smoking and to constipation; depression to symptomatic hypotension and excessive daytime somnolence; solvent exposure to cognitive deficits and to physical inactivity; and non-smoking to physical inactivity. Conversion to PD was interdependent with prior subthreshold parkinsonism, sex and substantia nigra hyperechogenicity. Several additional interdependencies with lower probabilistic confidence were identified. Synthetic subjects generated via the BN based representation of the TREND study were realistic as assessed through multiple comparison approaches of real and synthetic data. Altogether our work demonstrates the potential of modern AI approaches (specifically BNs) both for modelling and understanding interdependencies between PD risk and prodromal markers, which are so far not accounted for in PD prediction models, as well as for generating realistic synthetic data.

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“…People with depression may find it difficult to fall asleep and stay asleep at night [ 30 ]. They may also have excessive daytime sleepiness or may even sleep too much [ 31 ]. At the same time, SDs can exacerbate depression, leading to a negative cycle between depression and sleep that can be difficult to break [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

Persistent Depressive Disorder-Related Effect of Sleep Disorder on the Highest Risk of Suicide in Taiwan, 2000–2015

Hsiao

Cheng

Lin

et al. 2022

IJERPH

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Objective: to investigate whether persistent depressive disorder (PDD) affects sleep disorders (SDs) and increased suicide risk. Methods: in this study, we used the National Health Insurance Research Database (NHIRD) to select 117,033 SD patients, of whom 137 died by suicide, and 468,132 non-SD patients, of whom 118 died by suicide, and analyzed gender, age, and co-existing diseases. Hazard ratios (HRs) and 95% confidence intervals (CI) were calculated using a multivariate Cox proportional hazards model. Results: the hazard ratio of suicide in SD patients was 1.429 times that of non-SD patients. The hazard ratio of suicide in female patients was 1.297 times higher than in males. Compared with people without PDD, people with PDD had a 7.195 times higher hazard ratio for suicide than those without PDD. PDD patients with SDs had a 2.05 times higher hazard ratio for suicide than those with no SDs. Conclusions: suicide risk was increased in SD patients, and the maximum suicide risk was greater in SD patients with PDD than in non-PDD patients. PDD affected SDs and increased suicide risk. Clinicians should be aware of the possibility that PDD affects patients with SDs and contributes to suicide risk.

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Excessive Daytime Sleepiness in Depression and Obstructive Sleep Apnea: More Than Just an Overlapping Symptom

Cited by 18 publications

References 60 publications

Association between poor sleep quality and an increased risk of dry eye disease in patients with obstructive sleep apnea syndrome

Association between poor sleep quality and an increased risk of dry eye disease in patients with obstructive sleep apnea syndrome

Bayesian network modeling of risk and prodromal markers of Parkinson’s disease

Persistent Depressive Disorder-Related Effect of Sleep Disorder on the Highest Risk of Suicide in Taiwan, 2000–2015

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