To explore the possible impact factors on daytime sleepiness among peritoneal patients from a single center in China. A cross-sectional study was conducted in 98 prevalent peritoneal dialysis (PD) patients using both the Pittsburgh Sleep Quality Index (PSQI) questionnaire of sleep quality and the Epworth Sleepiness Scale (ESS) questionnaire of excessive daytime sleepiness (EDS). Biochemical differences between daytime sleepiness and non-daytime sleepiness population were evaluated, following univariate and multivariable analysis to find the risk factors on sleep disturbance. The prevalence of "poor sleep quality" (PSQI > 5) was 74.49%, while daytime sleepiness (ESS ≥ 9) occurred in 22.45%. Mean PSQI was 9.06 ± 4.60 and EES was 6.31 ± 4.98. Compared to non-EDS cases, patients with ESS ≥ 9 had worse residual renal function (RRF), higher serum creatinine, higher serum magnesium and elevated serum ferritin. In univariate analysis, ESS correlated with serum albumin (r = 0.346, p = 0.015), phosphate (r = 0.313, p = 0.029), magnesium (r = 0.376, p = 0.008) and urinary Kt/V (r = -0.341, p = 0.029). Finally, multivariable linear regression indicated that urinary Kt/V, PSQI and magnesium were independent predictors of ESS score. EDS does exist in PD patients and is associated both with poor nighttime sleep quality and lower RRF. Hypermagnesemia may be a treatable risk factor to improve daytime tiredness.
Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambulatory peritoneal dialysis patients were assigned to the EDS group and the non-EDS group according to the Epworth Sleepiness Scale (ESS). Ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the differential metabolites. Twenty-seven (male/female, 15/12; age, 60.1 ± 16.2 years) PD patients with ESS ≥ 10 were assigned to the EDS group, while twenty-one (male/female, 13/8; age, 57.9 ± 10.1 years) PD patients with ESS < 10 were defined as the non-EDS group. With UHPLC-Q-TOF/MS, 39 metabolites with significant differences between the two groups were found, 9 of which had good correlations with disease severity and were further classified into amino acid, lipid and organic acid metabolism. A total of 103 overlapping target proteins of the differential metabolites and EDS were found. Then, the EDS–metabolite–target network and the protein–protein interaction network were constructed. The metabolomics approach integrated with network pharmacology provides new insights into the early diagnosis and mechanisms of EDS in PD patients.
Uremic toxins are chemicals, organic or inorganic, that accumulate in the body fluids of individuals with acute or chronic kidney disease and impaired renal function. More than 130 uremic solutions are included in the most comprehensive reviews to date by the European Uremic Toxins Work Group, and novel investigations are ongoing to increase this number. Although approaches to remove uremic toxins have emerged, recalcitrant toxins that injure the human body remain a difficult problem. Herein, we review the derivation and elimination of uremic toxins, outline kidney–gut axis function and relative toxin removal methods, and elucidate promising approaches to effectively remove toxins.
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