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Braz. j. med. biol. res ; 38(2): 221-225, fev. 2005. tab
Artículo en Inglés | LILACS | ID: lil-393647

RESUMEN

Diabetic retinopathy (DR) is a sight-threatening chronic complication of diabetes mellitus and is the leading cause of acquired blindness in adults. In this cross-sectional study, we investigated the prevalence of and the factors associated with DR in an analysis of 210 consecutive and unrelated Brazilian Caucasians with type 2 diabetes mellitus. Retinopathy was evaluated by ophthalmoscopy and/or biomicroscopy through dilated pupils. The relationship between clinical and metabolic variables and the presence of DR was assessed by logistic regression analysis. DR was detected in 99 of the 210 patients (47 percent). In the univariate logistic regression analyses, male sex, duration of diabetes, body mass index, glycated hemoglobin, C-peptide, LDL cholesterol, smoking, and albumin excretion rate were found to be associated with the presence of DR. However, the multiple logistic regression analysis showed that only duration of diabetes (odds ratio (OR) = 1.15, 95 percent CI = 1.09-1.22; P < 0.001), glycated hemoglobin (OR = 1.21, 95 percent CI = 1.01-1.46; P = 0.047) and albumin excretion rate >100 µg/min (OR = 12.72, 95 percent CI = 3.89-41.56; P < 0.001) were independently associated with DR. Although DR was found to be frequent among Brazilian type 2 diabetic patients, its prevalence was within the range observed in other Caucasian populations. Our findings emphasize the need for good glycemic control in order to prevent or delay the onset of DR, since the most well-known risk factors for the development of this complication in type 2 diabetes mellitus, such as duration of diabetes, glycated hemoglobin and albumin excretion rate were independently related to DR.


Asunto(s)
Humanos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Diabetes Mellitus Tipo 2 , Retinopatía Diabética/epidemiología , Brasil/epidemiología , Estudios Transversales , Retinopatía Diabética/sangre , Retinopatía Diabética/diagnóstico , Población Blanca , Modelos Logísticos , Prevalencia , Factores de Riesgo
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