Risk factors of sleep-disordered breathing in haemodialysis patients

Sleep apnoea syndrome prevalence in chronic kidney disease and end-stage kidney disease patients: a systematic review and meta-analysis

Background

Several studies have examined the frequency of sleep apnoea (SA) in patients with chronic kidney disease (CKD), reporting different prevalence rates. Our systematic review and meta-analysis aimed to define the clinical penetrance of SA in CKD and end-stage kidney disease (ESKD) patients.

Methods

Ovid-MEDLINE and PubMed databases were explored up to 5 June 2023 to identify studies providing SA prevalence in CKD and ESKD patients assessed by different diagnostic methods, either sleep questionnaires or respiration monitoring equipment [such as polysomnography (PSG), type III portable monitors or other diagnostic tools]. Single-study data were pooled using the random-effects model. The Chi2 and Cochrane-I2 tests were used to assess the presence of heterogeneity, which was explored performing sensitivity and/or subgroup analyses.

Results

A cumulative analysis from 32 single-study data revealed a prevalence of SA of 57% [95% confidence interval (CI) 42%-71%] in the CKD population, whereas a prevalence of 49% (95% CI 47%-52%) was found pooling data from 91 studies in ESKD individuals. The prevalence of SA using instrumental sleep monitoring devices, including classical PSG and type III portable sleep monitors, was 62% (95% CI 52%-72%) and 56% (95% CI 42%-69%) in CKD and ESKD populations, respectively. Sleep questionnaires revealed a prevalence of 33% (95% CI 16%-49%) and 39% (95% CI 30%-49%).

Conclusions

SA is commonly seen in both non-dialysis CKD and ESKD patients. Sleep-related questionnaires underestimated the presence of SA in this population. This emphasizes the need to use objective diagnostic tools to identify such a syndrome in kidney disease.

Impact of Hemodialysis on Sleep Disorders in Patients With End-Stage Renal Disease in a Tertiary Care Academic Hospital

INTRODUCTION

Although hemodialysis (HD) has prolonged the survival of patients with end-stage renal disease (ESRD), it has also adversely affected the sleep and emotional state of these patients. We evaluated the impact of HD on sleep duration, quality, and other sleep-related disorders.

METHODS

We recruited consecutive adult patients visiting our tertiary care dialysis unit. We included only ESRD patients who had an estimated glomerular filtration rate (eGFR) of <15 mL/min/1.73m2. We excluded patients with unrelated comorbidities or on medications that could affect sleep. Basic demographic information, anthropometric data, and appropriate lab investigations were obtained. Objective information related to their sleep duration and quality was asked using a predefined proforma. Subjective sleep scores were obtained by using the Pittsburgh sleep quality index (PSQI), Epworth sleepiness scale (ESS), and insomnia severity index (ISI). For comparison, the patients were divided into HD and conservative treatment (CT) groups based on their treatment modality. The baseline characteristics of the patients were noted. The Shapiro-Wilk test was used to test normality. Correlations were obtained by using Student's t-test for parameters that were normally distributed and the Mann-Whitney-Wilcoxon test for those that were not.

RESULTS

Of the 56 patients we studied, 59% were males. The average age and body mass index (BMI) were 45.7 years and 20.98 kg/m2, respectively. Overall, 41% of patients were assigned to the HD group, and the remaining to the CT group. The CT group had fewer comorbidities compared to the HD group. The average sleep duration was similar in both groups (HD: 6.64 hours, CT: 6.49 hours). There was a weak-to-moderate positive correlation between the sleep scores. Overall, one-half of the patients had excessive daytime sleepiness (EDS) (46.43%) and insomnia (48.21%), and two-thirds of them were poor sleepers (66.07%). Symptoms suggestive of sleep-disordered breathing (SDB) were seen in 25% of patients, restless legs syndrome (RLS) in 19.64% of patients, and periodic limb movement disorder (PLMD) in 44.64% of patients. Patients undergoing HD had poorer sleep quality compared to the CT group (p=0.038). The odds of developing poor sleep were 3.6 times higher in the HD group.

CONCLUSION

This cross-sectional study focuses on the quantification of objective and subjective deterioration of sleep quality in ESRD patients on HD. The prevalence of EDS (63.64%), insomnia (51.52%), and poor sleep quality (84.84%) in the HD group was more than the previously reported values. The PSQI, ESS, and ISI scores were higher in HD patients, indicating poorer sleep quality. Our study highlights the underestimation of sleep disorders in HD patients in underserved areas. The results warrant a meticulous evaluation of the same by a keen nephrologist, followed by referral to sleep providers where necessary.

The complexity of sleep disorders in dialysis patients

Background

Dialysis patients experience a high burden of physical and emotional symptoms directly affecting their sleep and quality of life. In this study, objective and subjective measurements to quantify sleep were performed, compared with those of healthy controls, and associated with burden of comorbidity and uraemic toxicity.

Methods

A total of 64 dialysis patients were included—10 peritoneal dialysis, 42 in-centre daytime haemodialysis (HD) and 12 in-centre nocturnal HD patients—as well as one-to-one age- and gender-matched healthy controls. Assumed and actual sleep time, sleep efficiency and fragmentation index were measured by actigraphy for at least two consecutive nights. Patients and controls also completed Insomnia Severity Index (ISI) and Pittsburgh Sleep Quality Index (PSQI) questionnaires. The patients’ blood was sampled to determine concentrations of a representative series of uraemic toxins and the Davies–Stoke comorbidity index was derived from medical records.

Results

Apart from the assumed sleep time, all objectively and subjectively measured sleep parameters were worse in the dialysis group compared with the healthy controls. No differences were seen in any of the measured sleep parameters among the different dialysis groups. None of the objectively measured sleep parameters were associated with ISI or PSQI scores in dialysis patients, while sleep times were related to the subjective scores in the healthy cohort. Objectively assessed sleep parameters were associated to neither the uraemic toxicity load nor the Davies–Stoke score.

Conclusions

Independent of the modality, dialysis patients have sleep quality much worse than age- and gender-matched healthy controls. The objectively measured sleep parameters could not be associated to the subjective score, uraemic toxicity or comorbidity score, highlighting the need for objective measurements of sleep and clinical guidelines to aid patient management.

Validation of Oximetry for Diagnosing Obstructive Sleep Apnea in a Clinical Setting

A large epidemiological study using oximetry to analyze obstructive sleep apnea (OSA) and metabolic comorbidities was performed in Japan; however, reliability and validity of oximetry in the Japanese population remains poorly understood. In this study, oximetry data from the epidemiological study were compared with data from clinically performed polysomnography (PSG) and out-of-center sleep testing (OCST) in epidemiological study participants who later attended our outpatient units. The oxygen desaturation index (ODI) from oximetry showed a moderate positive relationship (correlation coefficient r = 0.561, p < 0.001) with apnea/hypopnea data from PSG/OCST. The area under the receiver operating characteristic curve showed moderate accuracy of this method in the detection of moderate-to-severe or severe OSA. However, the optimal ODI thresholds to detect moderate-to-severe OSA and severe OSA were the same (ODI > 20.1). Oximetry may be a useful tool for screening moderate-to-severe or severe sleep apnea. However, it may be difficult to set an appropriate threshold to distinguish between moderate and severe sleep apnea by oximetry alone.

Sleep Apnea in Maintenance Hemodialysis: A Mixed-Methods Study

Rationale & Objective

More than 50% of hemodialysis patients experience sleep disturbance and most have coexisting sleep apnea. However, how sleep apnea affects sleep and the overall experience of patients with chronic kidney disease treated by hemodialysis has not been evaluated.

Study Design

A mixed-methods design, incorporating cross-sectional observational and descriptive qualitative methodologies.

Setting & Participants

Patients receiving maintenance hemodialysis in Newcastle, New South Wales, Australia, with newly diagnosed sleep apnea (apnea-hypopnea index ≥ 5 per hour).

Assessments

In-laboratory polysomnography to assess sleep apnea and objective sleep parameters. Epworth Sleepiness Scale to assess daytime symptoms. A semi-structured qualitative interview to explore patient experience.

Analytical Approach

Descriptive and iterative thematic analysis.

Results

We analyzed 36 patients with newly diagnosed sleep apnea and interviewed 26 (mean age, 62 years, median apnea-hypopnea index, 32 per hour). Severity of sleep apnea did not affect patients’ sleep duration, sleep efficiency, or self-reported Epworth Sleepiness Scale score. From the qualitative interviews, 4 themes emerged: “broken sleep” related to short sleep duration, with waking and dozing off a common sleep cycle, caused by uncontrolled pain and dialysis. Many participants reported regularly “feeling unrefreshed” on waking. “Impact of sleep disturbance” included reduced physical, mental, and self-management capacity. Finally, interviewees described the need to use strategies to “soldier on” with symptoms.

Limitations

Participants’ views are only transferrable to hemodialysis patients with sleep apnea.

Conclusions

Our findings suggest that severity of sleep apnea does not affect sleep time or patient-reported daytime sleepiness; however, hemodialysis patients with sleep apnea report disturbed and unrefreshed sleep and the debilitating effects of sleep disturbance is profound. Broken and unrefreshed sleep were the dominant symptoms of sleep apnea and should be assessed routinely to identify patients with sleep apnea and improve quality of life in patients with chronic kidney disease treated with hemodialysis.

Sleep Apnea and the Kidney

Purpose of Review

There are some uncertainties about the interactions between obstructive sleep apnea (OSA) and chronic kidney disease (CKD). We critically reviewed recent studies on this topic with a focus on experimental and clinical evidence of bidirectional influences between OSA and CKD, as well as the effects of treatment of either disease.

Recent Findings

Experimental intermittent hypoxia endangers the kidneys, possibly through activation of inflammatory pathways and increased blood pressure. In humans, severe OSA can independently decrease kidney function. Treatment of OSA by CPAP tends to blunt kidney function decline over time, although its effect may vary. OSA may increase cardiovascular complications and mortality in patients with end-stage renal disease (ESRD), while it seems of little harm after renal transplantation. Excessive fluid removal may explain some of the improvements in OSA severity in ESRD and after transplantation.

Summary

Severe OSA and CKD do interact negatively, mainly through hypoxia and fluid retention. The moderate mutually interactive benefits that treatment of each disease exerts on the other one warrant further studies to improve patient management.

The Predictive Performance of the STOP-Bang Questionnaire in Obstructive Sleep Apnea Screening of Obese Population at Sleep Clinical Setting

Background

The prevalence of obstructive sleep apnea (OSA) is high in the obese population. In this study, it was aimed to fulfill the STOP-Bang questionnaire which is a concise and easy-to-use questionnaire for OSA screening in obese patients.

Materials & methods

This is a retrospective study where the patients, who planned polysomnography, were referred to sleep clinic. Patients were screened for OSA by the STOP-Bang questionnaire. Laboratory polysomnography was performed in 275 patients. Patients with BMI ≥ 30 were taken into study. The screening test was evaluated by three different risk analysis such as, a STOP score, a STOP-Bang score and a modified STOP-Bang score. The predictive parameters (sensitivity, specificity, and positive and negative predictive values) for alternative scoring models in obese patients were analyzed.

Results

In 217 obese patients, a STOP score cutoff of 3 and a STOP-Bang score cutoff of 4 provides a better balance of sensitivity and specificity for all OSA (apnea-hypopnea index [AHI] ≥ 5). The STOP questionnaire revealed a sensitivity of 87.9% and a positive predictive value of 99.5% for patients with all OSA (p: 0.005). The STOP-Bang scoring model revealed a sensitivity of 95.3% and a positive predictive value of 99.5% for patients with all OSA (p < 0.001). The modified STOP-Bang scoring revealed a sensitivity of 95.8% and a positive predictive value of 99.5% for patients with all OSA (p < 0.001). The area under the curve of the STOP-Bang for identifying mild, moderate and severe OSA was 0.581, 0.652 and 0.675, respectively. Whereas according to the STOP-Bang, all morbid obese patients (obesity class III, n: 47) were at high risk of OSA.

Conclusion

This study suggests that the STOP-Bang questionnaire for obstructive sleep apnea screening in obese patients is a high sensitivity and appropriate screening test.