The rate of decrease in oxygen desaturation during severe obstructive sleep apnea syndrome is correlated with subjective excessive daytime sleepiness

Nocturnal oxygen resaturation parameters are associated with cardiorespiratory comorbidities

BACKGROUND

There are strong associations between oxygen desaturations and cardiovascular outcomes. Additionally, oxygen resaturation rates are linked to excessive daytime sleepiness independent of oxygen desaturation severity. No studies have yet looked at the independent effects of comorbidities or medications on resaturation parameters.

METHODS

The Sleep Heart Health Study data was utilised to derive oxygen saturation parameters from 5804 participants. Participants with a history of comorbidities or medication usage were compared against healthy participants with no comorbidity/medication history.

RESULTS

4293 participants (50.4% female, median age 64 years) were included in the analysis. Females recorded significantly faster resaturation rates (mean 0.61%/s) than males (mean 0.57%/s, p < 0.001), regardless of comorbidities. After adjusting for demographics, sleep parameters, and desaturation parameters, resaturation rate was reduced with hypertension (-0.09 (95% CI -0.16, -0.03)), myocardial infarction (-0.13 (95% CI -0.21, -0.04)) and heart failure (-0.19 (95% CI -0.33, -0.05)), or when using anti-hypertensives (-0.10 (95% CI -0.17, -0.03)), mental health medications (-0.18 (95% CI -0.27, -0.08)) or anticoagulants (-0.41 (95% CI -0.56, -0.26)). Desaturation to Resaturation ratio for duration was decreased with mental health (-0.21 (95% CI -0.34, -0.08)) or diabetic medications (-0.24 (95% CI -0.41, -0.07)), and desaturation to resaturation ratio for area decreased with heart failure (-0.25 (95% CI -0.42, -0.08)).

CONCLUSIONS

Comorbidities and medications significantly affect nocturnal resaturation parameters, independent of desaturation parameters. However, the causal relationship remains unclear. Further research can enhance our knowledge and develop more precise and safer interventions for individuals affected by certain comorbidities.

Symptom and comorbidity burden in hypertensive patients with obstructive sleep apnea

Background

Obstructive sleep apnea (OSA) is an important but frequently overlooked risk factor for hypertension (HTN). The prevalence of hypertension is high in patients with OSA, but the differences in clinical symptoms and comorbidities between patients with OSA with hypertension and those with normal blood pressure have not been fully defined.

Methods

This study retrospectively analyzed OSA patients diagnosed for the first time in Lihuili Hospital Affiliated to Ningbo University from 2016 to 2020. Patients were divided into an OSA group with hypertension and an OSA group without hypertension. The sociodemographic information, clinical symptoms, comorbidities, and polysomnography results of the two groups were compared. The independent risk factors associated with hypertension in patients with OSA were explored.

Results

A total of 1108 patients with OSA initially diagnosed were included in the study, including 387 with hypertension and 721 without. Compared with OSA patients without hypertension, OSA patients with hypertension were older; had a higher body mass index (BMI) and Epworth sleepiness score (ESS); a higher incidence of nocturia; and a higher proportion of diabetes mellitus, coronary heart disease, and cerebrovascular disease. Multivariate analysis showed age (odds ratio [OR]:1.06, 95% confidence interval [CI]:1.04-1.08), BMI (OR:1.17, 95% CI:1.11-1.23), ESS score (OR:0.97, 95%CI: 0.94-1.00) and nocturia symptoms (OR:1.64, 95% CI:1.19-2.27) was independently associated with hypertension in OSA patients, and comorbid diabetes (OR: 3.86, 95% CI: 2.31-6.45), coronary heart disease (OR: 1.90, 95% CI:1.15-3.16), and ischemic stroke (OR: 3.69,95% CI:1.31-10.40) was independently associated with hypertension in OSA patients.

Conclusion

Compared to OSA patients with normal blood pressure, OSA patients with hypertension had more significant daytime sleepiness, more frequent nocturnal urination, and a higher risk of diabetes, coronary heart disease, and cerebrovascular disease.

ABOSA - Freely available automatic blood oxygen saturation signal analysis software: Structure and validation

BACKGROUND AND OBJECTIVE

Many sleep recording software used in clinical settings have some tools to automatically analyze the blood oxygen saturation (SpO₂) signal by detecting desaturations. However, these tools are often inadequate for scientific research as they do not provide SpO₂ signal-based parameters which are superior in the estimation of sleep apnea severity and related medical consequences. In addition, these software require expensive licenses and they lack batch analysis tools. Thus, we developed the first freely available automatic blood oxygen saturation analysis software (ABOSA) that provides sophisticated SpO₂ signal-based parameters and enables batch analysis of large datasets.

METHODS

ABOSA was programmed with MATLAB. ABOSA automatically detects desaturation and recovery events from the SpO₂ signals (EDF files) and calculates numerous parameters, such as oxygen desaturation index (ODI) and desaturation severity (DesSev). The accuracy of the ABOSA software was evaluated by comparing its desaturation scorings to manual scorings in Kuopio (n = 1981) and Loewenstein (n = 930) sleep apnea patient datasets. Validation was performed in a second-by-second manner by calculating Matthew's correlation coefficients (MCC) and median differences in parameter values. Finally, the performance of the ABOSA software was compared to two commercial software, Noxturnal and Profusion, in 100 patient subpopulations. As Noxturnal or Profusion does not calculate novel desaturation parameters, these were calculated with custom-made functions.

RESULTS

The agreements between ABOSA and manual scorings were great in both Kuopio (MCC = 0.801) and Loewenstein (MCC = 0.898) datasets. However, ABOSA slightly overestimated the desaturation parameter values. The median differences in ODIs were 0.8 (Kuopio) and 0.0 (Loewenstein) events/h. Similarly, the median differences in DesSevs were 0.02 (Kuopio) and 0.01 (Loewenstein) percentage points. In a second-by-second analysis, ABOSA performed very similarly to Noxturnal and Profusion software in both Kuopio (MCC_ABOSA = 0.807, MCC_Noxturnal = 0.807, MCC_Profusion = 0.811) and Loewenstein (MCC_ABOSA = 0.904, MCC_Noxturnal = 0.911, MCC_Profusion = 0.871) datasets. Based on Noxturnal and Profusion scorings, the desaturation parameter values were similarly overestimated compared to ABOSA.

CONCLUSIONS

ABOSA is an accurate and freely available software that calculates both traditional clinical parameters and novel parameters, provides a detailed characterization of desaturation and recovery events, and enables batch analysis of large datasets. These are features that no other software currently provides making ABOSA uniquely suitable for scientific research use.

Home Sleep Testing of Sleep Apnea

Measurement methods with graded complexity for use in the lab as well as for home sleep testing (HST) are available for the diagnosis of sleep apnea, and there are different classification systems in existence. Simplified HST measurements, which record fewer parameters than traditional four- to six-channel devices, can indicate sleep apnea and can be used as screening tool in high-prevalence patient groups. Peripheral arterial tonometry (PAT) is a technique which can be suitable for the diagnosis of sleep apnea in certain cases. Different measurement methods are used, which has an influence on the significance of the results. New minimal-contact and non-contact technologies of recording and analysis of surrogate parameters are under development. If they are validated by clinical studies, it will be possible to detect sleep apnea in need of treatment more effectively. In addition, this could become a solution to monitor the effectiveness of such treatment.

Current Update on Clinically Relevant Sleep Issues in Parkinson's Disease: A Narrative Review

Sleep disturbances are among the common nonmotor symptoms in patients with Parkinson’s disease (PD). Sleep can be disrupted by nocturnal motor and nonmotor symptoms and other comorbid sleep disorders. Rapid eye movement sleep behavior disorder (RBD) causes sleep-related injury, has important clinical implications as a harbinger of PD and predicts a progressive clinical phenotype. Restless legs syndrome (RLS) and its related symptoms can impair sleep initiation. Excessive daytime sleepiness (EDS) is a refractory problem affecting patients’ daytime activities. In particular, during the COVID-19 era, special attention should be paid to monitoring sleep problems, as infection-prevention procedures for COVID-19 can affect patients’ motor symptoms, psychiatric symptoms and sleep. Therefore, screening for and managing sleep problems is important in clinical practice, and the maintenance of good sleep conditions may improve the quality of life of PD patients. This narrative review focused on the literature published in the past 10 years, providing a current update of various sleep disturbances in PD patients and their management, including RBD, RLS, EDS, sleep apnea and circadian abnormalities.