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      Prognostic value of long-term trajectories of depression for incident diabetes mellitus in patients with stable coronary heart disease

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          Abstract

          Background

          Diabetes mellitus (DM) and depression are bidirectionally interrelated. We recently identified long-term trajectories of depression symptom severity in individuals with coronary heart disease (CHD), which were associated with the risk for subsequent cardiovascular events (CVE). We now investigated the prognostic value of these trajectories of symptoms of depression with the risk of incident DM in patients with stable coronary heart disease.

          Methods

          The KAROLA cohort included CHD patients participating in an in-patient rehabilitation program (years 1999/2000) and followed for up to 15 years. We included 1048 patients (mean age 59.4 years, 15% female) with information on prevalent DM at baseline and follow-up data. Cox proportional hazards models were used to model the risk for incident DM during follow-up by depression trajectory class adjusted for age, sex, education, smoking status, body mass index, and physical activity. In addition, we modeled the excess risk for subsequent CVE due to incident DM during follow-up for each of the depression trajectories.

          Results

          DM was prevalent in 20.7% of patients at baseline. Over follow-up, 296 (28.2%) of patients had a subsequent CVE. During follow-up, 157 (15.0%) patients developed incident DM before experiencing a subsequent CVE. Patients following a high-stable depression symptom trajectory were at substantially higher risk of developing incident DM than patients following a low-stable depression symptom trajectory (hazard ratio (HR) = 2.50; 95% confidence interval (CI) (1.35, 4.65)). A moderate-stable and an increasing depression trajectory were associated with HRs of 1.48 (95%-CI (1.10, 1.98)) and 1.77 (95%-CI (1.00, 3.15)) for incident DM. In addition, patients in the high-stable depression trajectory class who developed incident DM during follow-up were at 6.5-fold risk (HR = 6.51; 95%-CI (2.77, 15.3)) of experiencing a subsequent cardiovascular event.

          Conclusions

          In patients with CHD, following a trajectory of high stable symptoms of depression was associated with an increased risk of incident DM. Furthermore, incident DM in these patients was associated with a substantially increased risk of subsequent CVE. Identifying depressive symptoms and pertinent treatment offers might be an important and promising approach to enhance outcomes in patients with CHD, which should be followed up in further research and practice.

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          Most cited references38

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          The Hospital Anxiety and Depression Scale

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            From inflammation to sickness and depression: when the immune system subjugates the brain.

            In response to a peripheral infection, innate immune cells produce pro-inflammatory cytokines that act on the brain to cause sickness behaviour. When activation of the peripheral immune system continues unabated, such as during systemic infections, cancer or autoimmune diseases, the ensuing immune signalling to the brain can lead to an exacerbation of sickness and the development of symptoms of depression in vulnerable individuals. These phenomena might account for the increased prevalence of clinical depression in physically ill people. Inflammation is therefore an important biological event that might increase the risk of major depressive episodes, much like the more traditional psychosocial factors.
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              Is Open Access

              Epidemiology of Type 2 Diabetes – Global Burden of Disease and Forecasted Trends

              The rising burden of type 2 diabetes is a major concern in healthcare worldwide. This research aimed to analyze the global epidemiology of type 2 diabetes. We analyzed the incidence, prevalence, and burden of suffering of diabetes mellitus based on epidemiological data from the Global Burden of Disease (GBD) current dataset from the Institute of Health Metrics, Seattle. Global and regional trends from 1990 to 2017 of type 2 diabetes for all ages were compiled. Forecast estimates were obtained using the SPSS Time Series Modeler. In 2017, approximately 462 million individuals were affected by type 2 diabetes corresponding to 6.28% of the world’s population (4.4% of those aged 15–49 years, 15% of those aged 50–69, and 22% of those aged 70+), or a prevalence rate of 6059 cases per 100,000. Over 1 million deaths per year can be attributed to diabetes alone, making it the ninth leading cause of mortality. The burden of diabetes mellitus is rising globally, and at a much faster rate in developed regions, such as Western Europe. The gender distribution is equal, and the incidence peaks at around 55 years of age. Global prevalence of type 2 diabetes is projected to increase to 7079 individuals per 100,000 by 2030, reflecting a continued rise across all regions of the world. There are concerning trends of rising prevalence in lower-income countries. Urgent public health and clinical preventive measures are warranted.

                Author and article information

                Contributors
                raphael.peter@uni-ulm.de
                Journal
                Cardiovasc Diabetol
                Cardiovasc Diabetol
                Cardiovascular Diabetology
                BioMed Central (London )
                1475-2840
                13 May 2021
                13 May 2021
                2021
                : 20
                : 108
                Affiliations
                [1 ]GRID grid.6582.9, ISNI 0000 0004 1936 9748, Institute of Epidemiology and Medical Biometry, , Ulm University, ; Ulm, Germany
                [2 ]GRID grid.7497.d, ISNI 0000 0004 0492 0584, Division of Clinical Epidemiology and Ageing Research, , German Cancer Research Center (DKFZ), ; Heidelberg, Germany
                [3 ]GRID grid.6190.e, ISNI 0000 0000 8580 3777, Faculty of Medicine and University Hospital Cologne, Heart Center, , University of Cologne, ; Cologne, Germany
                [4 ]GRID grid.7700.0, ISNI 0000 0001 2190 4373, Network Ageing Research, , University of Heidelberg, ; Heidelberg, Germany
                [5 ]Klinik Schwabenland, Isny-Neutrauchburg, Germany
                [6 ]GRID grid.6936.a, ISNI 0000000123222966, Deutsches Herzzentrum München, Technische Universität München, ; Munich, Germany
                [7 ]GRID grid.452396.f, ISNI 0000 0004 5937 5237, German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, ; Munich, Germany
                Author information
                http://orcid.org/0000-0003-4310-9500
                Article
                1298
                10.1186/s12933-021-01298-3
                8120929
                33985516
                aaf9705f-1ce9-4794-aa46-1b21fa38662a
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 23 February 2021
                : 5 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: #01GD9820/0
                Funded by: Pitzer Foundation (Germany)
                Award ID: Pitzer Foundation (Germany)
                Funded by: Universität Ulm (1055)
                Categories
                Original Investigation
                Custom metadata
                © The Author(s) 2021

                Endocrinology & Diabetes
                depression,trajectories,diabetes mellitus,coronary heart disease
                Endocrinology & Diabetes
                depression, trajectories, diabetes mellitus, coronary heart disease

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