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Streese L, Lona G, Wagner J, Knaier R, Burri A, Nève G, Infanger D, Vilser W, Schmidt-Trucksäss A, Hanssen H. Normative data and standard operating procedures for static and dynamic retinal vessel analysis as biomarker for cardiovascular risk. Sci Rep 2021; 11:14136. [PMID: 34238996 PMCID: PMC8266855 DOI: 10.1038/s41598-021-93617-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/22/2021] [Indexed: 01/10/2023] Open
Abstract
Retinal vessel phenotype is predictive for cardiovascular outcome. This cross-sectional population-based study aimed to quantify normative data and standard operating procedures for static and dynamic retinal vessel analysis. We analysed central retinal arteriolar (CRAE) and venular (CRVE) diameter equivalents, as well as retinal endothelial function, measured by flicker light-induced maximal arteriolar (aFID) and venular (vFID) dilatation. Measurements were performed in 277 healthy individuals aged 20 to 82 years of the COmPLETE study. The mean range from the youngest compared to the oldest decade was 196 ± 13 to 166 ± 17 µm for CRAE, 220 ± 15 to 199 ± 16 µm for CRVE, 3.74 ± 2.17 to 3.79 ± 2.43% for aFID and 4.64 ± 1.85 to 3.86 ± 1.56% for vFID. Lower CRAE [estimate (95% CI): - 0.52 (- 0.61 to - 0.43)], CRVE [- 0.33 (- 0.43 to - 0.24)] and vFID [- 0.01 (- 0.26 to - 0.00)], but not aFID, were significantly associated with older age. Interestingly, higher blood pressure was associated with narrower CRAE [- 0.82 (- 1.00 to - 0.63)] but higher aFID [0.05 (0.03 to 0.07)]. Likewise, narrower CRAE were associated with a higher predicted aFID [- 0.02 (- 0.37 to - 0.01)]. We recommend use of defined standardized operating procedures and cardiovascular risk stratification based on normative data to allow for clinical implementation of retinal vessel analysis in a personalized medicine approach.
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Affiliation(s)
- Lukas Streese
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Giulia Lona
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Jonathan Wagner
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Raphael Knaier
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Andri Burri
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Gilles Nève
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Denis Infanger
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Walthard Vilser
- Institute of Biomedical Engineering and Informatics, Ilmenau University of Technology, Ilmenau, Germany
| | - Arno Schmidt-Trucksäss
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland
| | - Henner Hanssen
- Department of Sport, Exercise and Health, Medical Faculty, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland.
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