Prevalence and related factors of poor sleep quality in patients with pre-dialysis chronic kidney disease

Autor: Raziye Yazıcı, İbrahim Güney
Rok vydání: 2022
Předmět:
Zdroj: The International Journal of Artificial Organs. 45:905-910
ISSN: 1724-6040
0391-3988
DOI: 10.1177/03913988221118941
Popis: Background: Sleep disturbances in patients with chronic kidney disease (CKD) are related to decreased quality of life and increased health-related risks. There is insufficient data about actual prevalence and related factors of poor sleepers in this group. In this study, we aimed to investigate prevalence and related risk factors of self-reported poor sleep quality in patients with pre-dialysis CKD. Methods: In this cross-sectional study, 259 pre-dialysis CKD patients (median age 56 years; range, 19–85) were included. Demographical, clinical and laboratory correlates were recorded. Body mass index (BMI) was calculated. Estimated glomerular filtration rate (eGFR) was calculated by the Modification of Diet in Renal Disease (MDRD) formula. Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI), a self-rated questionnaire. Depression was evaluated using the Beck Depression Inventory (BDI). Results: Median eGFR was 27.6 ml/min/1.73 m2 (range, 9–56). Of the 259 patients, 110 (42.5%) were poor sleepers with global PSQI score >5. The univariate correlation analysis revealed that global PSQI score was positively correlated with age, BMI, waist circumferences (WC), hip circumferences (HC), serum phosphorus and triglyceride levels, systolic blood pressure (BP), pulse pressure and BDI score, and negatively correlated with male gender and hemoglobin level. Logistic regression analysis, showed that HC, systolic BP, and BDI scores were independently associated with poor sleep quality ( p = 0.001, p = 0.020 and p Conclusion: Prevalence of poor sleep quality in our pre-dialysis CKD patients was 42.5%. Systolic BP, depression and HC, all of these are potentially correctable factors, were associated with poor sleep quality independently.
Databáze: OpenAIRE