Cognitive Impairment in Patients on Maintenance Hemodialysis and Its Influencing Factors: a Multicenter Cross-sectional Study
摘要
Background Understanding the condition and influencing factors of cognitive impairment in maintenance hemodialysis (MHD) patients could signficantly enhance their quality of life while alleviating the burden on their families and society. Objective TO investigate the status of cognitive impairment in MHD patients and explore the possible influencing factors. Methods Using convenience sampling, we selected MHD patients from three hemodialysis centers (including the Department of Nephrology at the First Affiliated Hospital of Shihezi University, the Department of Nephrology at Shihezi People's Hospital, and the Langshen Hemodialysis Center) in Shihezi City between April 2023 and April 2024. We collected data on demographic characteristics, cognitive impairment levels, sleep quality, independent living abilities, serum levels of α-Klotho, β-Klotho, FGF-23, and other common laboratory indicators. Cognitive function was assessed with the Montreal Cognitive Assessment (MoCA), sleep quality was evaluated with the Athens Insomnia Scale (AIS-8), and independent living ability was assessed using the Functional Activities Questionnaire (FAQ). Serum levels of α-Klotho, β-Klotho, and FGF-23 were measured by the ELISA method. Univariate and multivariate Logistic regression analyses were performed to identify influencing factors, which were validated for their predictive value on cognitive impairment using the receiver operating characteristic (ROC) curve. A nomogram was subsequently plotted. Results A total of 276 MHD patients were surveyed, revealing a cognitive impairment incidence rate of 76.4% (211/276). Among these, 145 patients had mild cognitive impairment and 66 patients had moderate cognitive impairment. Nearly half of the patients exhibited suspected insomnia (21.4%) or confirmed insomnia (25.4%). Among the patients studied, 14.9% (41 out of 276) lacked the ability to live independently. The multivariate Logistic regression analysis indi