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      The impact of neuropathic pain and other comorbidities on the quality of life in patients with diabetes

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          Abstract

          Background

          Diabetic polyneuropathy (DPN) is one of the most common complications of diabetes and can exist with or without neuropathic pain. We were interested in how neuropathic pain impairs the quality of life in diabetic patients and what is the role of comorbidities in this condition.

          Methods

          The study included 80 patients with painful DPN (group “P”) and 80 patients with DPN, but without neuropathic pain (group “D”). Visual analogue scale (VAS) and Leeds assessment of neuropathic symptoms and signs (LANSS) pain scale were used for assessment of neuropathic pain, SF-36 standardized questionnaire for assessment of the quality of life and BDI questionnaire for assessment of depression.

          Results

          Subjects in group P had statistically significantly lower values compared to group D in all 8 dimensions and both summary values of the SF-36 scale. We ascribe the extremely low results of all parameters of SF-36 scale in group P to painful diabetic polyneuropathy with its complications. The patients in group D showed higher average values in all dimension compared to group P, but also somewhat higher quality of life compared to general population of Croatia in 4 of 8 dimensions, namely vitality (VT), social functioning (SF), role-emotional (RE) and mental health (MH), which was unexpected result.

          Clinically, the most pronounced differences between two groups were noted in sleeping disorders and problems regarding micturition and defecation , which were significantly more expressed in group P. The similar situation was with walking distance and color-doppler sonography of carotid arteries, which were significantly worse in group P. Consequently, subjects in group P were more medicated than the patients in group D, particularly with tramadol, antiepileptics and antidepressants.

          Conclusion

          Painful DPN is a major factor that influences various aspects of quality of life in diabetic patients. Additionally, this study gives an overview of diabetic population in the Republic of Croatia, information that could prove useful in future studies.

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          Most cited references29

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          The prevalence of comorbid depression in adults with diabetes: a meta-analysis.

          To estimate the odds and prevalence of clinically relevant depression in adults with type 1 or type 2 diabetes. Depression is associated with hyperglycemia and an increased risk for diabetic complications; relief of depression is associated with improved glycemic control. A more accurate estimate of depression prevalence than what is currently available is needed to gauge the potential impact of depression management in diabetes. MEDLINE and PsycINFO databases and published references were used to identify studies that reported the prevalence of depression in diabetes. Prevalence was calculated as an aggregate mean weighted by the combined number of subjects in the included studies. We used chi(2) statistics and odds ratios (ORs) to assess the rate and likelihood of depression as a function of type of diabetes, sex, subject source, depression assessment method, and study design. A total of 42 eligible studies were identified; 20 (48%) included a nondiabetic comparison group. In the controlled studies, the odds of depression in the diabetic group were twice that of the nondiabetic comparison group (OR = 2.0, 95% CI 1.8-2.2) and did not differ by sex, type of diabetes, subject source, or assessment method. The prevalence of comorbid depression was significantly higher in diabetic women (28%) than in diabetic men (18%), in uncontrolled (30%) than in controlled studies (21%), in clinical (32%) than in community (20%) samples, and when assessed by self-report questionnaires (31%) than by standardized diagnostic interviews (11%). The presence of diabetes doubles the odds of comorbid depression. Prevalence estimates are affected by several clinical and methodological variables that do not affect the stability of the ORs.
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            Mobility limitation in the older patient: a clinical review.

            Mobility limitations are common in older adults, affecting the physical, psychological, and social aspects of an older adult's life. To identify mobility risk factors, screening tools, medical management, need for physical therapy, and efficacy of exercise interventions for older primary care patients with limited mobility. Search of PubMed and PEDro from January 1985 to March 31, 2013, using the search terms mobility limitation, walking difficulty, and ambulatory difficulty to identify English-language, peer-reviewed systematic reviews, meta-analyses, and Cochrane reviews assessing mobility limitation and interventions in community-dwelling older adults. Articles not appearing in the search referenced by reviewed articles were also evaluated. The most common risk factors for mobility impairment are older age, low physical activity, obesity, strength or balance impairment, and chronic diseases such as diabetes or arthritis. Several tools are available to assess mobility in the ambulatory setting. Referral to physical therapy is appropriate, because physical therapists can assess mobility limitations and devise curative or function-enhancing interventions. Relatively few studies support therapeutic exercise to improve mobility limitation. Strong evidence supports resistance and balance exercises for improving mobility-limiting physical weakness and balance disorders. Assessing a patient's physical environment and the patient's ability to adapt to it using mobility devices is critical. Identification of older adults at risk for mobility limitation can be accomplished through routine screening in the ambulatory setting. Addressing functional deficits and environmental barriers with exercise and mobility devices can lead to improved function, safety, and quality of life for patients with mobility limitations.
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              Do SF-36 summary component scores accurately summarize subscale scores?

              Standard scoring algorithms were recently made available for aggregating scores from the eight SF-36 subscales in two distinct, higher-order summary scores: Physical Component Summary (PCS) and Mental Component Summary (MCS). Recent studies have suggested, however, that PCS and MCS scores are not independent and may in part be measuring the same constructs. The aims of this paper were to examine and illustrate (1) relationships between SF-36 subscale and PCS, MCS scores, (2) relationships between PCS and MCS scores, and (3) their implications for interpreting research findings. Simulation analyses were conducted to illustrate the contributions of various aspects of the scoring algorithm to potential discrepancies between subscale profile and summary component scores. Using the Swedish SF-36 normative database, correlation and regression analyses were performed to estimate the relationship between the two components, as well as the relative contributions of the subscales to the components. Discrepancies between subscale profile and component scores were identified and explained. Significant correlations (r = -0.74, -0.67) were found between PCS and MCS scores at their respective upper scoring intervals, indicating that the components are not independent. Regression analyses revealed that in these ranges PCS primarily measures aspects of mental health (57% of variance) and MCS measures physical health (65% of variance). Implications of the findings were discussed. It was concluded that the current PCS MCS scoring procedure inaccurately summarizes subscale profile scores and should therefore be revised. Until then, component scores should be interpreted with caution and only in combination with profile scores.
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                Author and article information

                Contributors
                vesna.djermanovic.dobrota@zg.t-com.hr
                phrabac@hiim.hr
                dinko.skegro@kb-merkur.hr
                rtg.smiljanic@gmail.com
                savko.dobrota@zg.t-com.hr
                ingrid.prkacin@gmail.com
                n.brkljacic@gmail.com
                kperos@idb.hr
                martina.tomic@idb.hr
                vesnas@mef.hr
                vanjakes@net.hr
                Journal
                Health Qual Life Outcomes
                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central (London )
                1477-7525
                3 December 2014
                3 December 2014
                2014
                : 12
                : 1
                : 171
                Affiliations
                [ ]Department of Diabetic Complication, Clinical Hospital Merkur, University Clinic Vuk Vrhovac, Dugi dol 4a, 10000 Zagreb, Croatia
                [ ]Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Salata 12, Zagreb, Croatia
                [ ]Department of Internal Medicine, Clinical Hospital Merkur, Zajčeva 19, 10000 Zagreb, Croatia
                [ ]Department of Diagnostic and Interventional Radiology, University hospital Center Zagreb, Kišpatićeva 12, 10000 Zagreb, Croatia
                [ ]Department of Physiology, School of Medicine, University of Zagreb, Salata 3, 10000 Zagreb, Croatia
                [ ]University Department of Neurology, University hospital Center “ Sestre milosrdnice“, Vinogradska 29, 10000 Zagreb, Croatia
                Article
                171
                10.1186/s12955-014-0171-7
                4264315
                25468384
                ba976ebf-5956-485c-b987-508465534204
                © Dermanovic Dobrota et al.; licensee BioMed Central Ltd. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 March 2014
                : 13 November 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2014

                Health & Social care
                diabetes,diabetic polyneuropathy,quality of life,comorbidities
                Health & Social care
                diabetes, diabetic polyneuropathy, quality of life, comorbidities

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