Comparison of sleep quality between hemodialysis and peritoneal dialysis patients

2008 ◽  
Vol 40 (3) ◽  
pp. 785-791 ◽  
Author(s):  
Nazmiye Eryavuz ◽  
Seref Yuksel ◽  
Gursel Acarturk ◽  
Ihsan Uslan ◽  
Serap Demir ◽  
...  
Renal Failure ◽  
2014 ◽  
Vol 37 (1) ◽  
pp. 61-65 ◽  
Author(s):  
Xueli Lai ◽  
Wei Chen ◽  
Xiaolu Bian ◽  
Tieyun Wang ◽  
Juan Li ◽  
...  

Sleep Science ◽  
2021 ◽  
Vol 14 (nspe2) ◽  
Author(s):  
Hamed Azarnoush ◽  
Mojgan Mortazavi ◽  
Mohammad Hossein Rouhani ◽  
Shiva Seirafian ◽  
Abdolamir Atapour ◽  
...  

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Luisa Pereira ◽  
Anabela Malho Guedes ◽  
Ana Rita Martins ◽  
Patricia Matias ◽  
Patricia Branco

Abstract Background and Aims Sleep quality is an important and determining factor in the quality of life (QoL) during dialysis. The prevalence of sleep disorders in the general population varies between 10 and 40%; this figure increases to 50% in dialysis patients. This study was conducted to determine which factors influence sleep quality in end stage renal disease patients on automated (APD) and continuous (CAPD) ambulatory peritoneal dialysis. Methods This was a cross-sectional study which included stable patients from two Peritoneal Dialysis Units. We excluded patients who weren’t able to understand the questionnaires, the language and the ones who had hospitalar admissions in the previous 3 months. Pittsburg Sleep Quality Index (PSQI) was used for assessing sleep quality (the higher the score, the lower the sleep quality), while quality of life parameters were assessed by self-administered EuroQol questionnaire (EQ-5D-5L). The presence of depressive symptoms was made with Patient Health Questionnaire (PHQ-9). In all patients, demographic variables, Charlson Comorbidity Index (CCI), clinical and laboratory parameters were recorded and analyzed. Descriptive statistics was performed. Two groups were created according to Pittsburg Sleep Quality score: G1 (n=42) - “poor” sleep quality and G2 (n=28) - “good” sleep quality. Groups were compared using independent t-test for comparison of continuous variables and Chi square test for categorical variables. In order to evaluate relationship between sleep quality and the other variables multivariate logistic regression and Pearson bivariate analysis were used. Results The study enrolled 70 patients (male/female 44/26; mean age 55.3±14.6 years; APD/CAPD 25/45; PD duration 28±24.2months). One third (31.4%) of the patients was diabetic, 12.9% presented cardiac insufficiency and 20% had cardiovascular disease. 50% of our population had a sleep disorder, although the majority of the problems were slight to moderate. We found that PD patients who sleep better (G2) had significant better life quality (p<0.001), lower CCI (p<0.001) and were less depressed (p<0.001). 77.3% of the patients with worst sleep quality (G1) were diabetic (p=0.04), regardless glycemic control and hemoglobin A1c. There were no significant differences between the two modalities of peritoneal dialysis (APD and CAPD patients), between genders or in patients who were PD first. We found no significant association between sleep quality and dialysis efficacy (weekly kt/v). Multivariate analysis (linear regression) showed a significant association between sleep quality and EuroQol (ExpB=0.000; IC 95% 0.000 to 0.054; p=0.002) and, depression (ExpB=1.274; IC 95% 1.045 to 1.552; p=0.017) in a model adjusted to age, PD duration and diabetes. Conclusion Our results show that poor sleep quality seems to be linked to life quality, comorbidity burden and depression. A better understanding of risk factors associated with poor sleep quality may help to signalize the patients who may benefit of specific treatment. The PSQI survey is a simple tool offering very complete information on sleep quality. The implementation of actions aimed at improving the hygiene of sleep may be an excellent way to improve the patients’ quality of life in an efficient and effective manner.


Renal Failure ◽  
2008 ◽  
Vol 30 (10) ◽  
pp. 1017-1022 ◽  
Author(s):  
İbrahim Güney ◽  
Murat Biyik ◽  
Mehdi Yeksan ◽  
Zeynep Biyik ◽  
Huseyin Atalay ◽  
...  

Renal Failure ◽  
2021 ◽  
Vol 43 (1) ◽  
pp. 180-187
Author(s):  
Haifen Zhang ◽  
Yan Yang ◽  
Jiaying Huang ◽  
Shuhui Lailan ◽  
Xingjuan Tao

Author(s):  
Maryanne Zilli Canedo Silva ◽  
Barbara Perez Vogt ◽  
Nayrana Soares Carmo Reis ◽  
Rogerio Carvalho Oliveira ◽  
Jacqueline Costa Teixeira Caramori

Author(s):  
Firas Ajam ◽  
Arda Akoluk ◽  
Anas Alrefaee ◽  
Natasha Campbell ◽  
Avais Masud ◽  
...  

ABSTRACT Background: The electrocardiogram (ECG) can aid in identification of chronic kidney disease (CKD) patients at high risk for cardiovascular diseases. Cohort studies describe ECG abnormalities in patients on hemodialysis (HD), but we did not find data comparing ECG abnormalities among patients with normal kidney function or peritoneal dialysis (PD) to those on hemodialysis. We hypothesized that ECG conduction abnormalities would be more common, and cardiac conduction interval times longer, among patients on hemodialysis vs. those on peritoneal dialysis and CKD 1 or 2. Methods: Retrospective review of adult inpatients’ charts, comparing those with billing codes for “Hemodialysis” vs. inpatients without those charges, and an outpatient peritoneal dialysis cohort. Patients with CKD 3 or 4 were excluded. Results: One hundred and sixty-seven charts were reviewed. ECG conduction intervals were consistently and statistically longer among hemodialysis patients (n=88) vs. peritoneal dialysis (n=22) and CKD stage 1 and 2 (n=57): PR (175±35 vs 160±44 vs 157±22 msec) (p=0.009), QRS (115±32 vs. 111±31 vs 91±18 msec) (p=0.001), QT (411±71 vs. 403±46 vs 374±55 msec) (p=0.006), QTc (487±49 vs. 464±38 vs 452±52 msec) (p=0.0001). The only significantly different conduction abnormality was prevalence of left bundle branch block: 13.6% among HD patients, 5% in PD, and 2% in CKD 1 and 2 (p=0.03). Conclusion: To our knowledge, this is the first study to report that ECG conduction intervals are significantly longer as one progresses from CKD Stage 1 and 2, to PD, to HD. These and other data support the need for future research to utilize ECG conduction times to identify dialysis patients who could potentially benefit from proactive cardiac evaluations and risk reduction.


Author(s):  
Albatool Almousa ◽  
Fai Almarshud ◽  
Razan Almasuood ◽  
Marya Alyahya ◽  
Chandra Kalevaru ◽  
...  

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