Cargando…

Relationship between blood glucose and carotid intima media thickness: A meta-analysis

BACKGROUND: Increased coronary intima media thickness (CIMT) has been associated with adverse cardiovascular outcomes, as have increased glucose levels. The link has not been established between glucose and CIMT; therefore, we sought to assess the relationship between glucose and CIMT. METHODS: Medl...

Descripción completa

Detalles Bibliográficos
Autores principales: Einarson, Thomas R, Hunchuck, Jonathan, Hemels, Michiel
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2929218/
https://www.ncbi.nlm.nih.gov/pubmed/20707887
http://dx.doi.org/10.1186/1475-2840-9-37
Descripción
Sumario:BACKGROUND: Increased coronary intima media thickness (CIMT) has been associated with adverse cardiovascular outcomes, as have increased glucose levels. The link has not been established between glucose and CIMT; therefore, we sought to assess the relationship between glucose and CIMT. METHODS: Medline, EMBASE, Scopus, and Cochrane databases were searched from inception through 2009 for original research reporting both postprandial glucose levels and CIMT measurements. Glucose was classified as normal, impaired, or diabetic. Outputs included inverse variance weighted effect size and also average correlation (using the Wang and Bushman approach). Data were combined using a random effects meta-analytic model. Heterogeneity as assessed using χ(2 )and I(2); bias was examined using Egger plots and Begg-Mazumdar tau. Polynomial functions (i.e., linear, quadratic, cubic, quartic) were fit to the data and the Akaike Information Criteria were used to select the optimal model. RESULTS: We identified 172 papers; 161 were rejected (19 inappropriate design, 8 had selected patients, 101 inappropriate outcomes) leaving 11 accepted. We used data from 15,592 patients (8250 normals, 3013 impaired glucose, 4329 diabetics). There was no evidence of heterogeneity or publication bias. The overall correlation was 0.082 (CI(95%):0.066-0.098); the overall effect size was 0.294 (0.245-0.343) between diabetics and normals and 0.137 (0.072-0.202) between normals and those with impaired glucose. The equation of best fit was linear (CIMT = 0.828 + 0.009*glucose). CONCLUSIONS: There is a small but significant relationship between postprandial glucose levels and CIMT, which have both been associated with adverse cardiovascular outcomes.