000168832 001__ 168832
000168832 005__ 20240229133620.0
000168832 0247_ $$2doi$$a10.1186/s12933-021-01298-3
000168832 0247_ $$2pmid$$apmid:33985516
000168832 0247_ $$2altmetric$$aaltmetric:106757777
000168832 037__ $$aDKFZ-2021-01083
000168832 041__ $$aEnglish
000168832 082__ $$a610
000168832 1001_ $$00000-0003-4310-9500$$aPeter, Raphael S$$b0
000168832 245__ $$aPrognostic value of long-term trajectories of depression for incident diabetes mellitus in patients with stable coronary heart disease.
000168832 260__ $$aLondon$$bBioMed Central$$c2021
000168832 3367_ $$2DRIVER$$aarticle
000168832 3367_ $$2DataCite$$aOutput Types/Journal article
000168832 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1637228533_30114
000168832 3367_ $$2BibTeX$$aARTICLE
000168832 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000168832 3367_ $$00$$2EndNote$$aJournal Article
000168832 500__ $$a#LA:C070# /2021 May 13;20(1):108
000168832 520__ $$aDiabetes 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.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.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.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.
000168832 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0
000168832 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo01.inet.dkfz-heidelberg.de
000168832 650_7 $$2Other$$aCoronary heart disease
000168832 650_7 $$2Other$$aDepression
000168832 650_7 $$2Other$$aDiabetes mellitus
000168832 650_7 $$2Other$$aTrajectories
000168832 7001_ $$aJaensch, Andrea$$b1
000168832 7001_ $$0P:(DE-He78)1b59582b6c05ac4e57aa8b90dd9667f9$$aMons, Ute$$b2$$udkfz
000168832 7001_ $$0P:(DE-He78)c67a12496b8aac150c0eef888d808d46$$aSchöttker, Ben$$b3$$udkfz
000168832 7001_ $$aSchmucker, Roman$$b4
000168832 7001_ $$aKoenig, Wolfgang$$b5
000168832 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b6$$udkfz
000168832 7001_ $$0P:(DE-HGF)0$$aRothenbacher, Dietrich$$b7$$eLast author
000168832 773__ $$0PERI:(DE-600)2093769-6$$a10.1186/s12933-021-01298-3$$gVol. 20, no. 1, p. 108$$n1$$p108$$tCardiovascular diabetology$$v20$$x1475-2840$$y2021
000168832 909CO $$ooai:inrepo02.dkfz.de:168832$$pVDB
000168832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)1b59582b6c05ac4e57aa8b90dd9667f9$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000168832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)c67a12496b8aac150c0eef888d808d46$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000168832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aDeutsches Krebsforschungszentrum$$b6$$kDKFZ
000168832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000168832 9131_ $$0G:(DE-HGF)POF4-313$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vKrebsrisikofaktoren und Prävention$$x0
000168832 9130_ $$0G:(DE-HGF)POF3-313$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vCancer risk factors and prevention$$x0
000168832 9141_ $$y2021
000168832 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bCARDIOVASC DIABETOL : 2019$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Blind peer review$$d2021-05-04
000168832 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bCARDIOVASC DIABETOL : 2019$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2021-05-04
000168832 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2021-05-04
000168832 9201_ $$0I:(DE-He78)M050-20160331$$kM050$$lM050 Krebsprävention$$x0
000168832 9201_ $$0I:(DE-He78)C070-20160331$$kC070$$lC070 Klinische Epidemiologie und Alternf.$$x1
000168832 980__ $$ajournal
000168832 980__ $$aVDB
000168832 980__ $$aI:(DE-He78)M050-20160331
000168832 980__ $$aI:(DE-He78)C070-20160331
000168832 980__ $$aUNRESTRICTED