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      Employment 12 months after kidney transplantation: An in-depth bio-psycho-social analysis of the Swiss Transplant Cohort

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      1 , 1 , 1 , * , 2 , 1 , 3 , for the Psychosocial Interest Group, Swiss Transplant Cohort Study
      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          Return to work with or after a chronic disease is a dynamic process influenced by a variety of interactions between personal, work, societal and medical resources or constraints. The aim of this study was to identify predictors for employment 12 months after transplantation in kidney patients, applying a bio-psycho-social model.

          Methods

          All kidney patients followed in the Swiss Transplant Cohort between May 2008 and December 2012, aged 18 to 65 were assessed before, 6 and 12 months after transplantation.

          Results

          Of the 689 included patients, 56.2% worked 12 months post- transplantation compared to 58.9% pre-transplantation. Age, education, self-perceived health (6 months post- transplantation), pre- transplantation employment and receiving an organ from a living donor are significant predictors of employment post- transplantation. Moreover, while self-perceived health increased post- transplantation, depression score decreased only among those employed 12 months post- transplantation. Pre- transplantation employment status was the main predictor for post- transplantation employment (OR = 18.6) and was associated with sex, age, education, depression and duration of dialysis. An organ from a living donor (42.1%) was more frequent in younger patients, with higher education, no diabetes and shorter waiting time to surgery.

          Conclusion

          Transplantation did not increase employment in end-stage kidney disease patients but helped maintaining employment. Pre-transplantation employment has been confirmed to be the most important predictor of post-transplantation employment. Furthermore, socio-demographic and individual factors predicted directly and indirectly the post-transplantation employment status. With living donor, an additional predictor linked to social factors and the medical procedure has been identified.

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          Most cited references46

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          Anxiety and depression in cancer patients compared with the general population.

          The objective of this study was to compare the prevalence of anxiety and depression in cancer patients with the prevalence found in the general population, using the Hospital Anxiety and Depression Scale (HADS). Participants were 1529 cancer patients treated between 2002 and 2004 in Germany and 2037 persons from the German general population. In the cancer patients, the risk of psychiatric distress was nearly twice that of the general population. While for older age groups (61 years and above) there were only small differences between cancer patients and the general population, the differences in both scales were high for young persons. There were differences between the HADS mean scores of the patients with different tumour localisations, with high values for brain cancer and low scores for prostate cancer. The influence of the tumour stage on anxiety and depression was weak. However, depression scores of patients with a survival time less than 1 year were elevated. The results show that large sample sizes are necessary to evaluate the psychological situation of cancer patients, and that age and gender differences must be taken into account when several samples are compared.
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            The interplay of socioeconomic status, distance to center, and interdonor service area travel on kidney transplant access and outcomes.

            Variation in kidney transplant access across the United States may motivate relocation of patients with ability to travel to better-supplied areas. We examined national transplant registry and U.S. Census data for kidney transplant candidates listed in 1999 to 2009 with a reported residential zip code (n = 203,267). Cox's regression was used to assess associations of socioeconomic status (SES), distance from residence to transplant center, and relocation to a different donation service area (DSA) with transplant access and outcomes. Patients in the highest SES quartile had increased access to transplant compared with those with lowest SES, driven strongly by 76% higher likelihood of living donor transplantation (adjusted hazard ratio [aHR] 1.76, 95% confidence interval [CI] 1.70 to 1.83). Waitlist death was reduced in high compared with low SES candidates (aHR 0.86, 95% CI 0.84 to 0.89). High SES patients also experienced lower mortality after living and deceased donor transplant. Patients living farther from the transplant center had reduced access to deceased donor transplant and increased risk of post-transplant death. Inter-DSA travel was associated with a dramatic increase in deceased donor transplant access (HR 1.94, 95% CI 1.88 to 2.00) and was predicted by high SES, white race, and longer deceased-donor allograft waiting time in initial DSA. Ongoing disparities exist in kidney transplantation access and outcomes on the basis of geography and SES despite near-universal insurance coverage under Medicare. Inter-DSA travel improves access and is more common among high SES candidates.
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              Design and methodology of the Swiss Transplant Cohort Study (STCS): a comprehensive prospective nationwide long-term follow-up cohort

              In Switzerland, organ procurement is well organized at the national-level but transplant outcomes have not been systematically monitored so far. Therefore, a novel project, the Swiss Transplant Cohort Study (STCS), was established. The STCS is a prospective multicentre study, designed as a dynamic cohort, which enrolls all solid organ recipients at the national level. The features of the STCS are a flexible patient-case system that allows capturing all transplant scenarios and collection of patient-specific and allograft-specific data. Beyond comprehensive clinical data, specific focus is directed at psychosocial and behavioral factors, infectious disease development, and bio-banking. Between May 2008 and end of 2011, the six Swiss transplant centers recruited 1,677 patients involving 1,721 transplantations, and a total of 1,800 organs implanted in 15 different transplantation scenarios. 10 % of all patients underwent re-transplantation and 3% had a second transplantation, either in the past or during follow-up. 34% of all kidney allografts originated from living donation. Until the end of 2011 we observed 4,385 infection episodes in our patient population. The STCS showed operative capabilities to collect high-quality data and to adequately reflect the complexity of the post-transplantation process. The STCS represents a promising novel project for comparative effectiveness research in transplantation medicine. Electronic supplementary material The online version of this article (doi:10.1007/s10654-012-9754-y) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                27 April 2017
                2017
                : 12
                : 4
                : e0175161
                Affiliations
                [1 ]Institut Universitaire Romand de Santé au Travail (Institute for Work and Health), University of Lausanne and University of Geneva, Epalinges - Lausanne, Switzerland
                [2 ]Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland
                [3 ]Institut national de recherche et de sécurité (INRS), Vandoeuvre Les Nancy Cedex, France
                University of Toledo, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: BD AS MK.

                • Data curation: AS MK PW.

                • Formal analysis: AS RS PW.

                • Funding acquisition: BD AS MK.

                • Investigation: AS MK.

                • Methodology: BD AS MK PW.

                • Project administration: BD AS MK.

                • Resources: BD.

                • Software: AS RS PW.

                • Supervision: BD RS MK.

                • Validation: BD PW.

                • Visualization: AS.

                • Writing – original draft: BD AS RS PW.

                • Writing – review & editing: BD AS RS MK PW.

                ¶ Membership of the Psychosocial Interest Group, Swiss Transplant Cohort Study is provided in the Acknowledgements.

                Author information
                http://orcid.org/0000-0002-8604-5378
                Article
                PONE-D-16-33906
                10.1371/journal.pone.0175161
                5407833
                28448501
                84a1180c-a2f8-49ef-8779-64497d43becb
                © 2017 Danuser et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 24 August 2016
                : 21 March 2017
                Page count
                Figures: 2, Tables: 3, Pages: 17
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: PDFMP3_137125
                Award Recipient :
                The present research was funded by the Swiss National Science Foundation (subsidy No. PDFMP3_137125), http://www.snf.ch/en/Pages/default.aspx. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Social Sciences
                Economics
                Labor Economics
                Employment
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Transplantation
                Organ Transplantation
                Renal Transplantation
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Urinary System Procedures
                Renal Transplantation
                Medicine and Health Sciences
                Nephrology
                Medical Dialysis
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Regression Analysis
                Custom metadata
                Data are available from doi: 10.6084/m9.figshare.4868135.

                Uncategorized
                Uncategorized

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