Chinese Journal of Blood Purification ›› 2025, Vol. 24 ›› Issue (02): 172-176.doi: 10.3969/j.issn.1671-4091.2025.02.016

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Analysis of potential classes and influencing factors for sleep quality in maintenance hemodialysis patients

MA Rong-rong, DENG Si-yan, ZHAO Juan, ZHENG Jing, CHEN Chen, HU Hua-gang, CHEN Dong-ying   

  1. Emergency Intensive Care Unit, Department of Emergency Medicine, The Central Hospital Affiliated to Jiangnan University (The Second People's Hospital of Wuxi), Wuxi 214002, China; 2School of Nursing, Suzhou Medical College, Soochow University, Suzhou 215006, China; 3Blood Purification Center, Yancheng City Tinghu District People's Hospital, Yancheng 224001, China; 4School of Nursing, Guangdong Pharmaceutical University, Guangzhou 510310, China; 5Department of Nephrology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China;  6Department of Geriatrics, The First Affiliated Hospital of Soochow University, Suzhou 215000, China
  • Received:2024-05-14 Revised:2024-11-12 Online:2025-02-12 Published:2025-02-12
  • Contact: 215000 苏州,6苏州大学附属第一医院老年医学科 E-mail:dongyingchen2022@126.com

Abstract: Objective To explore the potential categories and influencing factors for sleep quality in maintenance hemodialysis (MHD) patients.  Methods  A total of 480 MHD patients were recruited from hemodialysis center of The Central Hospital Affiliated to Jiangnan University and other 3 hospitals by convenient sampling method. General information questionnaire, Pittsburgh Sleep Quality Scale (PSQI), Patient Health Questionnaire, and Generalized Anxiety Scale were used for the investigation.  Results  The prevalence of sleep disorders in MHD patients was 50.7%. By selecting the optimal model, sleep quality could be classified into four potential categories: overall better sleep group (C1, 22.8%), typical insomnia group (C2, 14.2%), daytime dysfunction with nocturnal sleep disorder group (C3, 28.4%), and overall worse sleep group (C4, 34.6%). Logistic regression analysis showed that the influencing factors for sleep disorders in C4 group included age (OR=1.028, 95% CI: 1.005~1.052, P=0.015), depression (OR=16.097, 95% CI: 6.397~40.503, P<0.001) and anxiety (OR=3.511, 95% CI: 1.038~11.873, P=0.043), when C1 group was used as the reference group; the influencing factors for sleep disorders in C4 group included depression (OR=13.683, 95% CI: 5.072~36.917, P<0.001) and dialysis age (OR=6.983, 95% CI: 1.510~32.284, P=0.013), when C2 group was used as the reference group.  Conclusion The sleep quality is heterogeneous in MHD patients. Clinical healthcare professionals should focus on the sleep status and intervene the sleep disorders in MHD patients especially in those with older age, having dialysis age more than 10 years, and complicated with  depression and anxiety.

Key words: Maintenance hemodialysis, Sleep quality, Potential category analysis, Influencing factor, Nursing

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