Obstructive sleep apnea syndrome and risk of renal impairment: a systematic review and meta-analysis with trial sequential analysis

The effect of PAP on UACR and metabolic indexes in patients with MS and OSAHS

PURPOSE

To investigate the effects of positive airway pressure (PAP) device on urinary albumin to creatinine ratio (UACR) and metabolic indexes in patients with metabolic syndrome (MS) and obstructive sleep apnea-hypopnea syndrome (OSAHS).

METHODS

This study is a retrospective cohort study. Grouped according to whether to use PAP treatment, there were 25 cases in the PAP group and 44 cases in the no OSAHS treatment group. The PAP group received positive airway pressure device and routine treatment of MS. The no OSAHS treatment group received routine treatment of OSAHS and MS. The treatment period is 3 months.

RESULTS

1. The PAP group demonstrated significant reductions in Body Mass Index (BMI), Waist circumference (WC), Neck circumference (NC), Visceral fat area (VFA), Fasting C peptide (FCP), high-sensitivity C-reactive protein (hs-CRP), and UACR compared to the no OSAHS treatment group, with significant differences (P all <0.05). Among them, the UACR in the PAP group decreased significantly (from 86.05(52.55,131.61)mg/g to 16.76(8.70,25.12)mg/g, P<0.001). 2. Linear regression analysis using the decrease in UACR values as the dependent variable demonstrated a positive linear relationship with the decrease in BMI, VFA, fasting insulin (FINS), and homeostasis model assessment of insulin resistance (HOMA-IR). Furthermore, multiple linear regression analysis indicated that the decrease in VFA (B=0.537 [95% confidence interval, 0.084 to 0.989]; P = 0.021) and HOMA-IR (B=1.000 [95% confidence interval, 0.082 to 1.917]; P = 0.033) values independently correlated with decrease in UACR values.

CONCLUSIONS

PAP treatment can reduce UACR in patients with MS and OSAHS, and has the effect of improving metabolic disorders. The decrease of UACR in patients may be related to the decrease of visceral fat and the improvement of insulin resistance.

Hypoxia-Induced Insulin Resistance Mediates the Elevated Cardiovascular Risk in Patients with Obstructive Sleep Apnea: A Comprehensive Review

Patients with obstructive sleep apnea (OSA) experience insulin resistance and its clinical consequences, including hypertriglyceridemia, reduced high density lipoprotein-associated cholesterol (HDL-c), visceral adiposity, hepatic steatosis, increased epicardial fat thickness, essential hypertension, glucose intolerance, increased risk for type 2 diabetes, chronic kidney disease, subclinical vascular damage, and increased risk for cardiovascular events. Obesity is a major contributor to OSA. The prevalence of OSA is almost universal among patients with severe obesity undergoing bariatric surgery. However, insulin resistance and its clinical complications occur in OSA patients irrespective of general obesity (body mass index). In OSA patients, apnea episodes during sleep induce oxyhemoglobin desaturation and tissue hypoxia. Insulin resistance is an adaptive response to tissue hypoxia and develops in conditions with limited tissue oxygen supply, including healthy subjects exposed to hypobaric hypoxia (high altitude) and OSA patients. Indicators of oxyhemoglobin desaturation have been robustly and independently linked to insulin resistance and its clinical manifestations in patients with OSA. Insulin resistance mediates the elevated rate of type 2 diabetes, chronic kidney disease, and cardiovascular disease unexplained with traditional cardiovascular risk factors present in OSA patients. Pathophysiological processes underlying hypoxia-induced insulin resistance involve hypoxia inducible factor-1 upregulation and peroxisome proliferator-activated receptor-gamma (PPAR- γ ) downregulation. In human adipose tissue, PPAR- γ activity promotes glucose transport into adipocytes, lipid droplet biogenesis, and whole-body insulin sensitivity. Silencing of PPAR- γ in the adipose tissue reduces glucose uptake and fat accumulation into adipocytes and promotes insulin resistance. In conclusion, tissue hypoxia drives insulin resistance and its clinical consequences in patients with OSA, regardless of body mass index.

The role of depression between sleep disorders and frailty among elderly patients with chronic kidney disease (CKD) in China: a cross-sectional study

OBJECTIVE

To investigate the correlation among sleep disorders, physical frailty, and depression in elderly patients with chronic kidney disease (CKD), and to explore the mediating role of depression.

METHODS

This was a cross-sectional study, simple sampling was used to investigate the elderly CKD patients from one tertiary hospital in Shanghai. Those CKD patients who were diagnosed as CKD1-5 phase and were admitted to the Renal Medicine Ward from January to June 2022 and provided formal consent were considered for inclusion in our study. They were investigated with frailty phenotype (FP), Pittsburgh sleep quality index (PSQI), Center for Epidemiological Studies Depression Scale (CES-D), and self-made general information questionnaire. Linear regression was used to assess the associations between the variables, before this, PROCESS v4.1 was used to transform PSQI, CES-D and FP score to improve its normality, and conduct intermediary analysis. A difference of p < 0.05 was statistically significant.

RESULTS

A total of 504 elderly patients with CKD completed the questionnaire survey, aged 60-91. The incidence of sleep disorders among elderly patients with CKD was 60%, and the incidence of physical frailty was 18%. The depression was positively correlated with physical frailty (r = 0.418, p < 0.01) and sleep disorders (r = 0.541, p < 0.01). Physical frailty was positively correlated with sleep disorders (r = 0.320, p < 0.01). The depression plays a significant mediating role in the model, and the effect ratio of depression is 52%.

CONCLUSION

Depression is a mediating variable between sleep disorders and frailty. Improving depression in elderly patients with CKD accompanied by sleep disorders can help delay the occurrence of frailty.

Impact of Pulmonary Hypertension on Renal Functions in Obstructive Sleep Apnea Syndrome

OBJECTIVES

Pulmonary hypertension (PH) is common in obstructive sleep apnea syndrome (OSAS). This study aimed to evaluate the effect of PH on kidney functions in patients with OSAS.

METHODS

The data of patients who were diagnosed as having OSAS after referral to the sleep center in the Gaziantep University Medical Faculty between January 2005 and June 2017 were evaluated. The estimated glomerular filtration rate was calculated with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Renal functions of the subjects who had data after 5 years were included for long-term analysis.

RESULTS

A total of 2152 patients with OSAS (n = 1540), PH (n = 49), OSAS and PH coexistence (n = 359), and the control group (n = 204) were included in the study. Pulmonary arterial pressure (PAP) was 44.51 ± 23.73 in the PH group; it was 37.1 ± 13.14 in the group with OSAS + PH (P = 0.001) Urea and uric acid were found to be higher in the association of OSAS + PH. CKD-EPI was lower in the presence of PH or OSAS + PH than in the presence of OSAS. PH was present in 16.06% of males and 25.10% of females (P = 0.000), and PAP was detected as 35.80 ± 13.23 and 40.96 ± 16.65, respectively (P = 0.001). PH was present in 15.99% of males and 25.84% of females with OSAS (P = 0.000). The PAP of males with OSAS was 36.03 ± 13.46, and the PAP of females was 38.68 ± 12.55 (P = 0062). Urea, creatinine, and uric acid were higher and CKD-EPI was lower in male subjects in the presence of OSAS and PH, whereas the same scenario also was present in the presence of PH alone in female subjects. Long-term comparisons (n = 343) revealed significant decreases in the CKD-EPI in those with OSAS and OSAS + PH and these decrease were more pronounced in the presence of OSAS and PH. The regression analysis revealed that female patients had lower CKD-EPI in the presence of PH, although the presence of PH had no effect on CKD-EPI in males.

CONCLUSIONS

PH is a risk factor for the deterioration of renal function in OSAS and more prominent in the long term.

A Review of a Recent Meta-Analysis Study on Obstructive Sleep Apnea

This paper summarizes a recent meta-analysis of various topics in obstructive sleep apnea (OSA). In addition to cardiovascular disease and neurocognitive dysfunction, a wide variety of diseases have been associated with OSA, and associations with cancer have also been reported. Although continuous positive airway pressure is a very effective treatment, the results have shown that it does not reduce the incidence of various complications. It has been reported that uvulopalatopharyngoplasty was effective, and robotic surgery for the tongue root and hypoglossal nerve stimulation were also effective. The effectiveness of various medications to reduce daytime sleepiness has also been demonstrated. Although exercise lowered the apnea-hypopnea index, it was not related to changes in body composition, and it was also reported that exercise combined with weight control were effective. Additionally, interesting and clinically meaningful meta-analysis results were summarized and presented.

Prevalence of sleep disorders in children with chronic kidney disease: a meta-analysis

BACKGROUND

The reported prevalence of sleep disorders in children with chronic kidney disease (CKD) varies greatly. A quantitative meta-analysis to estimate the prevalence of sleep disorders among pediatric CKD patients may provide further information.

OBJECTIVES

The objective of this study is to estimate the prevalence of sleep disorders in children with CKD. The study protocol was registered on PROSPERO (registration number CRD42021268378).

DATA SOURCES

Two authors independently searched the PubMed, MEDLINE, EMBASE, and Cochrane review databases up to June 2021.

STUDY ELIGIBILITY CRITERIA

Eligible studies include data of prevalence of sleep disorders in children with CKD.

STUDY APPRAISAL AND SYNTHESIS METHODS

The prevalence of restless legs syndrome, sleep-disordered breathing, pediatric obstructive sleep apnea (i.e., apnea-hypopnea index &gt; 1 event/h in polysomnography), excessive daytime sleepiness, and insomnia/insufficient sleep was estimated using a random-effects model. Subgroup analyses were conducted to compare the prevalence of sleep disorders between children on dialysis and not on dialysis. This meta-analysis included 12 studies with 595 children (mean age: 12.9 years; gender ratio: 55.6% boys; mean sample size: 49.6 patients).

RESULTS

The prevalence of restless legs syndrome in children with CKD was 21% (95% confidence interval [CI], 14-30%). The prevalence of sleep-disordered breathing, pediatric obstructive sleep apnea, excessive daytime sleepiness, and insomnia/insufficient sleep was 22% (95% CI, 12-36%), 34% (95% CI, 19-53%), 27% (95% CI, 17-41%), and 14% (95% CI, 7-27%), respectively. Subgroup analysis revealed the pooled prevalence of excessive daytime sleepiness was significantly higher in children on dialysis than in children not on dialysis (43.3% vs. 11.2%; P = 0.018). Children on dialysis also had a high prevalence of other sleeping disorders, although the differences did not reach statistical significance. Children with CKD exhibited a 3.9-fold (95% CI, 1.37 to 10.93) increased risk of restless legs syndrome and a 9.6-fold (95% CI, 3.57 to 25.76) increased risk of excessive daytime sleepiness compared with controls.

LIMITATIONS

The selected papers are of small sample size, lack of a control group, and exhibit substantial heterogeneity.

CONCLUSIONS

Sleep disorders are common in children with CKD. Our results indicate that while the prevalence rates of various sleep disorders were higher in children on dialysis than in children not on dialysis, the prevalence of excessive daytime sleepiness was statistically significant in children on dialysis. A higher resolution version of the Graphical abstract is available as Supplementary information.

Development and assessment of a risk prediction model for moderate-to-severe obstructive sleep apnea

Background

OSA is an independent risk factor for several systemic diseases. Compared with mild OSA, patients with moderate-to-severe OSA have more severe impairment in the function of all organs of the body. Due to the current limited medical condition, not every patient can be diagnosed and treated in time. To enable timely screening of patients with moderate-to-severe OSA, we selected easily accessible variables to establish a risk prediction model.

Method

We collected 492 patients who had polysomnography (PSG), and divided them into the disease-free mild OSA group (control group), and the moderate-to-severe OSA group according to the PSG results. Variables entering the model were identified by random forest plots, univariate analysis, multicollinearity test, and binary logistic regression method. Nomogram were created based on the binary logistic results, and the area under the ROC curve was used to evaluate the discriminative properties of the nomogram model. Bootstrap method was used to internally validate the nomogram model, and calibration curves were plotted after 1,000 replicate sampling of the original data, and the accuracy of the model was evaluated using the Hosmer-Lemeshow goodness-of-fit test. Finally, we performed decision curve analysis (DCA) of nomogram model, STOP-Bang questionnaire (SBQ), and NoSAS score to assess clinical utility.

Results

There are 6 variables entering the final prediction model, namely BMI, Hypertension, Morning dry mouth, Suffocating awake at night, Witnessed apnea, and ESS total score. The AUC of this prediction model was 0.976 (95% CI: 0.962–0.990). Hosmer-Lemeshow goodness-of-fit test χ² = 3.3222 (P = 0.1899 > 0.05), and the calibration curve was in general agreement with the ideal curve. The model has good consistency in predicting the actual occurrence of moderate-to-severe risk, and has good prediction accuracy. The DCA shows that the net benefit of the nomogram model is higher than that of SBQ and NoSAS, with has good clinical utility.

Conclusion

The prediction model obtained in this study has good predictive power for moderate-to-severe OSA and is superior to other prediction models and questionnaires. It can be applied to the community population for screening and to the clinic for prioritization of treatment.

An umbrella review of systematic reviews and meta-analyses of observational investigations of obstructive sleep apnea and health outcomes

Purpose

The previous analysis of systematic reviews and meta-analyses have illustrated that obstructive sleep apnea (OSA) is correlated with multiple health outcomes. In the present research, our main aim was to execute an umbrella review to assess the available evidence for the associations between OSA and health outcomes.

Methods

Herein, a meta-analysis of previous observational investigations that have reported associations between OSA and health outcomes in all human populations and settings was performed. We used these studies to execute an umbrella review of available meta-analyses and systematic reviews.

Results

Sixty-six articles comprising 136 unique outcomes were enrolled in this analysis. Of the 136 unique outcomes, 111 unique outcomes had significant associations (p < 0.05). Only 7 outcomes (coronary revascularization after PCI, postoperative respiratory failure, steatosis, alaninetrans aminase (ALT) elevation, metabolic syndrome (MS), psoriasis, and Parkinson’s disease) had a high quality of evidence. Twenty-four outcomes had a moderate quality of evidence, and the remaining 80 outcomes had a weak quality of evidence. Sixty-nine outcomes exhibited significant heterogeneity. Twenty-five outcomes exhibited publication bias. Sixty-three (95%) studies showed critically low methodological quality.

Conclusion

Among the 66 meta-analyses exploring 136 unique outcomes, only 7 statistically significant outcomes were rated as high quality of evidence. OSA may correlate with an increased risk of coronary revascularization after PCI, postoperative respiratory failure, steatosis, ALT elevation, MS, psoriasis, and Parkinson’s disease.