Literature DB >> 19682272

Depressive symptoms predict the subsequent risk of bodily pain in dialysis patients: Japan Dialysis Outcomes and Practice Patterns Study.

Yosuke Yamamoto1, Yasuaki Hayashino, Takashi Akiba, Tadao Akizawa, Yasushi Asano, Akira Saito, Kiyoshi Kurokawa, Shunichi Fukuhara.   

Abstract

BACKGROUND: Bodily pain and psychiatric distress are common symptoms in patients with dialysis. However, the temporal relationships have not yet been investigated. Objective. To evaluate the longitudinal association between depressive symptoms and subsequent risk of developing severe bodily pain in dialysis patients. Design. Prospective cohort study.
METHODS: We assessed bodily pain using a self-reported questionnaire and depressive symptoms using scores from the short version of Center for Epidemiological Studies Depression Screening Index (CES-D) from 531 participants showing no/mild bodily pain at baseline, based on the Japan Dialysis Outcomes and Practice Patterns Study, a cohort study of hemodialysis patients. To evaluate the relationship between depressive symptoms and development of severe bodily pain, multivariable logistic regression analysis was performed.
RESULTS: The 531 patients had a mean age of 57.9 years, 61.4% were male, and 33.1% had depressive symptoms. Logistic regression analysis revealed that depressive symptoms at baseline were significantly associated with higher odds of developing severe bodily pain during a 0.5- to 2.5-year follow-up period (adjusted odds ratio [AOR] = 2.13, 95% confidence interval [CI]: 1.36-3.33, P = 0.001). Further, patients with higher CES-D scores were likely to develop severe bodily pain (AOR = 1.09, 95% CI: 1.04-1.15, P = 0.001).
CONCLUSIONS: Results of this study suggest that depressive symptoms measured by CES-D predict the future risk of developing severe bodily pain in dialysis patients.

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Year:  2009        PMID: 19682272     DOI: 10.1111/j.1526-4637.2009.00661.x

Source DB:  PubMed          Journal:  Pain Med        ISSN: 1526-2375            Impact factor:   3.750


  6 in total

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Journal:  Kidney Int       Date:  2015-04-29       Impact factor: 10.612

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5.  Contemporary English Pain Descriptors as Detected on Social Media Using Artificial Intelligence and Emotion Analytics Algorithms: Cross-sectional Study.

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  6 in total

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