CHIABRANDO GUSTAVO ALBERTO
Congresos y reuniones científicas
Título:
Biochemical Parameters Discriminate Diabetic Patients With Clinically Significant Macular Edema (CSME) From Diabetic Patients Without CSME
Autor/es:
S¨¢NCHEZ MC; COLLINO CJ; BARONI MV; FORZINETTI G; FERRER D; CHIABRANDO GA; GRAMAJO AL; JUAREZ PC; GARCIA LG; LUNA JD
Lugar:
Fort Lauderdale, Florida, USA
Reunión:
Congreso; ARVO 2010 Annual Meeting; 2010
Institución organizadora:
Association for Research in Vision and Ophthalmology
Resumen:
Purpose: Diabetic macular edema is a common phenomenon associated with visual loss in diabetic patients and is characterized by accumulation of extracellular fluid in the retina. Up to now, the etiopathogenesis of this disease is not well known, which makes difficult the development of an effective treatment. The objective of this work was to determine different biochemical parameters in order to discriminate diabetic patients with clinically significant macular edema (CSME) from diabetic patients without CSME.
Methods: Peripheral whole blood samples were obtained of diabetic patients with CSME (n=27), diabetic patients without CSME and retinopathy (n=14) and controls (n=16). Quantitative assays were performed for 18 different biochemical parameters measured by conventional clinical laboratory tests with the exception of monocyte LRP1 and T lymphocyte (TL) surface antigens, including TLCD3+, TLCD4+, and TLCD4+CD8+, which were determined by flow cytometry using a Cytoron Absolute (Ortho Diagnostic System, Raritan, NJ), operated with Immunocount II software. The data were analyzed by WinMDI 2.8 software. All biochemical parameters were analyzed using Lineal Discriminant Analysis and Kruskal Wallis (Statistica version 7.0).
Results: Discriminant analysis applied on these 18 parameters allow differentiating diabetic patients with CSME, diabetic patients without CSME and controls with 86.4% certainty. This means that only 8 of 57 patients analyzed were misclassified. The mean value of Red cells, haemoglobin, haematocrit, lymphocytes, HDL cholesterol, triglicerides, glucose and HbA1c was statistically different between groups of patients (p¡Ü0.05).
Conclusions: Taken together all biochemical parameters allowed to statistically discrimination between CSME from the two other patient groups.
Methods: Peripheral whole blood samples were obtained of diabetic patients with CSME (n=27), diabetic patients without CSME and retinopathy (n=14) and controls (n=16). Quantitative assays were performed for 18 different biochemical parameters measured by conventional clinical laboratory tests with the exception of monocyte LRP1 and T lymphocyte (TL) surface antigens, including TLCD3+, TLCD4+, and TLCD4+CD8+, which were determined by flow cytometry using a Cytoron Absolute (Ortho Diagnostic System, Raritan, NJ), operated with Immunocount II software. The data were analyzed by WinMDI 2.8 software. All biochemical parameters were analyzed using Lineal Discriminant Analysis and Kruskal Wallis (Statistica version 7.0).
Results: Discriminant analysis applied on these 18 parameters allow differentiating diabetic patients with CSME, diabetic patients without CSME and controls with 86.4% certainty. This means that only 8 of 57 patients analyzed were misclassified. The mean value of Red cells, haemoglobin, haematocrit, lymphocytes, HDL cholesterol, triglicerides, glucose and HbA1c was statistically different between groups of patients (p¡Ü0.05).
Conclusions: Taken together all biochemical parameters allowed to statistically discrimination between CSME from the two other patient groups.
