Background: Even though depression is one of the most common psychiatric disorders, it is under-recognized in hemodialysis (HD) patients. Existing literature does not provide enough information on evaluation of predictors of depression among HD patients. The objective of the current study was to determine the prevalence and predictors of depression among HD patients.
Methods: A multicenter prospective follow-up study. All eligible confirmed hypertensive HD patients who were consecutively enrolled for treatment at the study sites were included in the current study. HADS questionnaire was used to assess the depression level among study participants. Patients with physical and/or cognitive limitations that prevent them from being able to answer questions were excluded.
Results: Two hundred twenty patients were judged eligible and completed questionnaire at the baseline visit. Subsequently, 216 and 213 patients completed questionnaire on second and final follow up respectively. The prevalence of depression among patients at baseline, 2nd visit and final visit was 71.3, 78.2 and 84.9% respectively. The results of regression analysis showed that treatment given to patients at non-governmental organizations (NGO's) running HD centers (OR = 0.347, p-value = 0.039) had statistically significant association with prevalence of depression at final visit.
Conclusions: Depression was prevalent in the current study participants. Negative association observed between depression and hemodialysis therapy at NGO's running centers signifies patients' satisfaction and better depression management practices at these centers.
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http://dx.doi.org/10.1186/s12889-019-6796-z | DOI Listing |
Front Aging Neurosci
January 2025
School of Nursing, Capital Medical University, Beijing, China.
Background: Hypocretin-1 is a vital neurotransmitter in regulating the sleep-wake cycle and provides neuroprotection against cerebral ischemia. We aims to develop a poor sleep quality predictive model for elderly population with acute ischemic stroke.
Methods: A total of 183 consecutively elderly patients were included in the prospective cohort study.
JMIR Form Res
January 2025
1, Department of Health Administration, College of Software and Digital Healthcare Convergence, Yonsei University, Changjogwan, Yonseidae-gil 1, Wonju, 26493, Republic of Korea, +82 (0) 33-760-2257.
Background: Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.
Objective: This study determined diabetes risk factors among older adults aged ≥60 years using machine learning algorithms and selected an optimized prediction model.
Methods: This cross-sectional study was conducted on 3084 older adults aged ≥60 years in Seoul from January to November 2023.
J Affect Disord
January 2025
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No.38, Xueyuan Road, Haidian District, Beijing 100191, China; Institute for Global Health and Development, Peking University, No.5 Yiheyuan Road, Haidian District, Beijing 100871, China; Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China. Electronic address:
Aims: To estimate the burden of major depressive disorder (MDD) among older adults and project its prevalence through 2050.
Methods: Using data from the Global Burden of Disease Study 2021, we calculated age-standardized rates (ASRs) for the incidence, prevalence, and years lived with disability (YLDs) of MDD among people aged ≥60 years from 1990 to 2021. Trends were analyzed using average annual percentage changes (AAPCs).
Agri
January 2025
Department of Physical Medicine and Rehabilitation, Bilkent City Hospital, Ankara, Türkiye.
Objectives: The present study aimed to compare the pressure-pain threshold (PPT) values in patients with rheumatoid arthritis (RA) and age-gender matched controls with chronic nonspecific low back pain and to determine whether PPT values could be beneficial as a disease activity predictor after secondary fibromyalgia had been ruled out.
Methods: This study contained a cross-sectional observational study of participants with RA and chronic nonspecific low back pain controls without fibromyalgia. Visual analog scale (VAS), fatigue severity scale (FSS), pain catastrophizing scale (PCS), health assessment questionnaire (HAQ), hospital anxiety and depression scale (HADS), and disease activity score (DAS28) were administered.
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