| 001 | 177499 | ||
| 005 | 20240229133742.0 | ||
| 024 | 7 | _ | |a 10.1186/s12933-021-01413-4 |2 doi |
| 024 | 7 | _ | |a pmid:34781939 |2 pmid |
| 024 | 7 | _ | |a altmetric:116987977 |2 altmetric |
| 037 | _ | _ | |a DKFZ-2021-02586 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Sinning, Christoph |0 0000-0002-7331-8840 |b 0 |
| 245 | _ | _ | |a Association of glycated hemoglobin A1c levels with cardiovascular outcomes in the general population: results from the BiomarCaRE (Biomarker for Cardiovascular Risk Assessment in Europe) consortium. |
| 260 | _ | _ | |a London |c 2021 |b BioMed Central |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1637240871_30274 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Biomarkers may contribute to improved cardiovascular risk estimation. Glycated hemoglobin A1c (HbA1c) is used to monitor the quality of diabetes treatment. Its strength of association with cardiovascular outcomes in the general population remains uncertain. This study aims to assess the association of HbA1c with cardiovascular outcomes in the general population.Data from six prospective population-based cohort studies across Europe comprising 36,180 participants were analyzed. HbA1c was evaluated in conjunction with classical cardiovascular risk factors (CVRFs) for association with cardiovascular mortality, cardiovascular disease (CVD) incidence, and overall mortality in subjects without diabetes (N = 32,496) and with diabetes (N = 3684).Kaplan-Meier curves showed higher event rates with increasing HbA1c levels (log-rank-test: p < 0.001). Cox regression analysis revealed significant associations between HbA1c (in mmol/mol) in the total study population and the examined outcomes. Thus, a hazard ratio (HR) of 1.16 (95% confidence interval (CI) 1.02-1.31, p = 0.02) for cardiovascular mortality, 1.13 (95% CI 1.03-1.24, p = 0.01) for CVD incidence, and 1.09 (95% CI 1.02-1.17, p = 0.01) for overall mortality was observed per 10 mmol/mol increase in HbA1c. The association with CVD incidence and overall mortality was also observed in study participants without diabetes with increased HbA1c levels (HR 1.12; 95% CI 1.01-1.25, p = 0.04) and HR 1.10; 95% CI 1.01-1.20, p = 0.02) respectively. HbA1c cut-off values of 39.9 mmol/mol (5.8%), 36.6 mmol/mol (5.5%), and 38.8 mmol/mol (5.7%) for cardiovascular mortality, CVD incidence, and overall mortality, showed also an increased risk.HbA1c is independently associated with cardiovascular mortality, overall mortality and cardiovascular disease in the general European population. A mostly monotonically increasing relationship was observed between HbA1c levels and outcomes. Elevated HbA1c levels were associated with cardiovascular disease incidence and overall mortality in participants without diabetes underlining the importance of HbA1c levels in the overall population. |
| 536 | _ | _ | |a 313 - Krebsrisikofaktoren und Prävention (POF4-313) |0 G:(DE-HGF)POF4-313 |c POF4-313 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo01.inet.dkfz-heidelberg.de |
| 650 | _ | 7 | |a BiomarCaRE (Biomarker for Cardiovascular Risk Assessment in Europe) |2 Other |
| 650 | _ | 7 | |a Biomarkers |2 Other |
| 650 | _ | 7 | |a Cardiovascular risk |2 Other |
| 650 | _ | 7 | |a Glycated hemoglobin A1c (HbA1c) |2 Other |
| 650 | _ | 7 | |a MORGAM (MONICA Risk Genetics Archiving and Monograph) |2 Other |
| 650 | _ | 7 | |a Mortality |2 Other |
| 700 | 1 | _ | |a Makarova, Nataliya |b 1 |
| 700 | 1 | _ | |a Völzke, Henry |b 2 |
| 700 | 1 | _ | |a Schnabel, Renate B |b 3 |
| 700 | 1 | _ | |a Ojeda, Francisco |b 4 |
| 700 | 1 | _ | |a Dörr, Marcus |b 5 |
| 700 | 1 | _ | |a Felix, Stephan B |b 6 |
| 700 | 1 | _ | |a Koenig, Wolfgang |b 7 |
| 700 | 1 | _ | |a Peters, Annette |b 8 |
| 700 | 1 | _ | |a Rathmann, Wolfgang |b 9 |
| 700 | 1 | _ | |a Schöttker, Ben |0 P:(DE-He78)c67a12496b8aac150c0eef888d808d46 |b 10 |u dkfz |
| 700 | 1 | _ | |a Brenner, Hermann |0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |b 11 |u dkfz |
| 700 | 1 | _ | |a Veronesi, Giovanni |b 12 |
| 700 | 1 | _ | |a Cesana, Giancarlo |b 13 |
| 700 | 1 | _ | |a Brambilla, Paolo |b 14 |
| 700 | 1 | _ | |a Palosaari, Tarja |b 15 |
| 700 | 1 | _ | |a Kuulasmaa, Kari |b 16 |
| 700 | 1 | _ | |a Njølstad, Inger |b 17 |
| 700 | 1 | _ | |a Mathiesen, Ellisiv Bøgeberg |b 18 |
| 700 | 1 | _ | |a Wilsgaard, Tom |b 19 |
| 700 | 1 | _ | |a Blankenberg, Stefan |b 20 |
| 700 | 1 | _ | |a Söderberg, Stefan |b 21 |
| 700 | 1 | _ | |a Ferrario, Marco M |b 22 |
| 700 | 1 | _ | |a Thorand, Barbara |0 0000-0002-8416-6440 |b 23 |
| 773 | _ | _ | |a 10.1186/s12933-021-01413-4 |g Vol. 20, no. 1, p. 223 |0 PERI:(DE-600)2093769-6 |n 1 |p 223 |t Cardiovascular diabetology |v 20 |y 2021 |x 1475-2840 |
| 909 | C | O | |o oai:inrepo02.dkfz.de:177499 |p VDB |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 10 |6 P:(DE-He78)c67a12496b8aac150c0eef888d808d46 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 11 |6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |
| 913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-313 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Krebsrisikofaktoren und Prävention |x 0 |
| 914 | 1 | _ | |y 2021 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b CARDIOVASC DIABETOL : 2019 |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2021-05-04 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Blind peer review |d 2021-05-04 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY (No Version) |0 LIC:(DE-HGF)CCBYNV |2 V:(DE-HGF) |b DOAJ |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2021-05-04 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2021-05-04 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-05-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2021-05-04 |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b CARDIOVASC DIABETOL : 2019 |d 2021-05-04 |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2021-05-04 |
| 915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2021-05-04 |
| 920 | 1 | _ | |0 I:(DE-He78)C070-20160331 |k C070 |l C070 Klinische Epidemiologie und Alternf. |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-He78)C070-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|
guest ::