2016, Number 2
<< Back Next >>
RCAN 2016; 26 (2)
Biomarkers of atherosclerosis as predictors of cardiovascular risk in uncomplicated high blood pressure
García SN, León ÁJL
Language: Spanish
References: 21
Page: 275-283
PDF size: 372.97 Kb.
ABSTRACT
Rationale: New biomarkers for atherosclerosis have been proposed. It is expected from their use peoples at increased risk of cardiovascular damage to be early identified and adequately treated.
Objective: To examine the associations between the new biomarkers of atherosclerosis and a clinical-epidemiological construct of cardiovascular risk (CVR) in high blood pressure (HBP) not complicated with lesion of target-organs.
Study design: Analytical, crosssectional.
Material and method: CVR was stratified in 100 un-complicated, hypertensive subjects (Males: 56.0%; Agees ≥ 60 years: 22.0%; Stage I of HBP progression: 78.0%; Evolution ‹ 5 years: 49.0%) from sex, age, tobacco use, blood pressure figures, and serum total cholesterol value. In addition, thickness of the intima layer of the carotid artery (GIM) was ultrasonographically measured. Associations between CVR, presence of albuminuria, and serum concentrations of glycated hemoglobin, troponin T, blood natruretic peptid, high sensitive C reactive protein, fibrinogen and Cystatin C.
Results: Sixty-nine percent of the subjects showed CVR between moderate-high. Twelve of the patients presented with GIM › 1.0 mm. An increased CVR was associated with hypertrigliceridemia, hypercholesterolemia, and hyperuricemia. Increased CVR was also associated with reduction of the glomerular filtration rate when estimated from Cystatin C.
Conclusions: Even in the absence of lesion of target-organs, hypertensive subjects might show a reduced glomerular filtration rate as revealed with Cystatin C. Revealed glomerular damage might result from resistance to insulin action
and/or deletereal influence of chronicallye levated blood pressure.
REFERENCES
García Sánchez N, León Álvarez JL. Sobre el comportamiento de biomarcadores de la arteriosclerosis en la hipertensión arterial. RCAN Rev Cubana Aliment Nutr 2016:26(2):252-274.
De Groot E, Hovingh GK, Wiegman A, Duriez P, Smit AJ, Fruchart JC; et al. Measurement of arterial wall thickness as a surrogate marker for atherosclerosis. Circulation 2004;109:33-8.
Salonen JT, Salonen R. Ultrasonographically assessed carotid morphology and the risk of coronary heart disease. Arterioscler Thromb 1991; 11:1245-9.
Elosua R, Morales Salinas A. Determinación del riesgo cardiovascular total. Caracterización, modelización y objetivos de la prevención según el contexto sociogeográfico. Rev Esp Cardiol 2011;11(Supl):E2-E12.
Graham I, Atar D, Borch-Johnsen K, Boysen G, Burell G, Cifkova R; et al. Guías de práctica clínica sobre prevención de la enfermedad cardiovascular: Versión resumida. Rev Esp Cardiol 2008;61(1):e1-e49.
Aminbakhsh A, Mancini GBJ. Carotid intima-media thickness measurements: What defines an abnormality? A systematic review. Clin Invest Med 1999;22:149-57.
Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D; for the Modification of Diet in Renal Disease Study Group. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Ann Intern Med 1999;130: 461-70.
Grubb A, Bjork J, Lindstrom V, Sterner G, Bondesson P, Nyman U. A cystatin C-based formula without anthropometric variables estimates glomerular filtration rate better than creatinine clearance using the Cockcroft-Gault formula. Scand J Clin Lab Invest 2005;65:153-62.
Grubb A, Nyman U, Bjork J, Lindstrom V, Rippe B, Sterner G; et al. Simple cystatin C-based prediction equations for glomerular filtration rate compared with the modification of diet in renal disease prediction equation for adults and the Schwartz and the Counahan-Barratt prediction equations for children. Clin Chem 2005;51:1420-31.
Microalb-Látex. Juego de reactivos para la determinación de albúmina en muestras de orina. Manual del usuario. Registro número 0308-15. Helfa Diagnósticos. Habana. Cuba.
Santana Porbén S, Martínez Canalejo, H. Manual de Procedimientos Bioestadísticos. Editorial EAE Académica Española. Madrid: 2012.
Santana Porbén S, Martínez Canalejo H. Manual de Estadísticas no Paramétricas. Editorial Publicia. Saarbrücken: 2013. ISBN: 978-3-639-55468-7.
Bray GA. Medical consequences of obesity. J Clin Endocrinol Metab 2004; 89:2583-9.
Hsu CC, Brancati F, Astor B, Kao WH, Steffes M, Folsom AR; et al. Blood pressure, atherosclerosis, and albuminuria in 10,113 participants of the Atherosclerosis Risk in Communities (ARIC) Study. Hypertension 2009;27: 397-409.
Talbott JH, Seegmiller JE. Gout and uric acid metabolism. Thieme Medical Publishers. New York: 1976.
Wyngaarden JB, Kelley WN. Gout and hyperuricemia. Grune & Stratton. New York: 1976.
Matsuura F, Yamashita S, Nakamura T, Nishida M, Nozaki S, Funahashi T, Matsuzawa Y. Effect of visceral fat accumulation on uric acid metabolism in male obese subjects: Visceral fat obesity is linked more closely to overproduction of uric acid than subcutaneous fat obesity. Metabolism 1998;47:929-33.
Tsouli SG, Liberopoulos EN, Mikhailidis DP, Athyros VG, Elisaf MS. Elevated serum uric acid levels in metabolic syndrome: An active component or an innocent bystander? Metabolism 2006; 55:1293-301.
Culleton BF, Larson MG, Kannel WB, Levy D. Serum uric acid and risk for cardiovascular disease and death: The Framingham Heart Study. Ann Int Med 1999;131:7-13.
Fang J, Alderman MH. Serum uric acid and cardiovascular mortality: The NHANES I epidemiologic follow-up study, 1971-1992. JAMA 2000;283(18): 2404-10.
Viazzi F, Parodi D, Leoncini G, Parodi A, Falqui V, Ratto E; et al. Serum uric acid and target organ damage in primary hypertension. Hypertension 2005;45: 991-6.