AIM: To investigate whether the presence of human leukocyte antigen(HLA) marker could add new information to discriminated atypical diabetic type 2 patients.METHODS: We analyzed 199 patients initially diagnosed as typ...AIM: To investigate whether the presence of human leukocyte antigen(HLA) marker could add new information to discriminated atypical diabetic type 2 patients.METHODS: We analyzed 199 patients initially diagnosed as type 2 diabetes who are treated in special care diabetes clinics(3rd level). This population was classified in "atypical"(sample A) and "classic"(sample B) according to HLA typing. We consider "classic patient" when has absence of type 1 diabetes associated HLA alleles and no difficulties in their diagnosis and treatments. By the other hand, we considered "atypical patient" when show type 1 diabetes associated HLA alleles and difficulties in their diagnosis and treatments. The standard protocol Asociacion Latinoamericana de Diabetes 2006 was used for patients follow up. To analyze differences between both populations in paraclinical parameters we used unpaired t tests and contingence tables. Bivariate and multivariate analyses were carried out using the SPSS software program. In all studies we assume differences statistically significant, with a P-value < 0.05 corrected and 95%CI.RESULTS: The typing HLA in the "atypical" populations show that 92.47% patients presented at list one type 1 diabetes associated HLA alleles(DQB1*0201-0302 and DR 3-4) and 7.53% had two of its. The results showed for categorical variables(family history, presence or absence of hypertension and/or dyslipidemia, reason for initial consultation) the only difference found was at dyslipidemia(OR = 0.45, 0.243 < OD < 0.822(P < 0.001). In relation to continuous variables we found significant differences between atypical vs classic only in cholesterol(5.07 ± 1.1 vs 5.56 ± 1.5, P < 0.05), high density lipoproteins(1.23 ± 0.3 vs 1.33 ± 0.3, P < 0.05) and low density lipoproteins(2.86 ± 0.9 vs 3.38 ± 1.7, P < 0.01). None of the variables had discriminating power when logistic regression was done.CONCLUSION: We propose an algorithm including HLA genotyping as a tool to discriminate atypical patients, complementing international treatment guidelines for complex patients.展开更多
文摘AIM: To investigate whether the presence of human leukocyte antigen(HLA) marker could add new information to discriminated atypical diabetic type 2 patients.METHODS: We analyzed 199 patients initially diagnosed as type 2 diabetes who are treated in special care diabetes clinics(3rd level). This population was classified in "atypical"(sample A) and "classic"(sample B) according to HLA typing. We consider "classic patient" when has absence of type 1 diabetes associated HLA alleles and no difficulties in their diagnosis and treatments. By the other hand, we considered "atypical patient" when show type 1 diabetes associated HLA alleles and difficulties in their diagnosis and treatments. The standard protocol Asociacion Latinoamericana de Diabetes 2006 was used for patients follow up. To analyze differences between both populations in paraclinical parameters we used unpaired t tests and contingence tables. Bivariate and multivariate analyses were carried out using the SPSS software program. In all studies we assume differences statistically significant, with a P-value < 0.05 corrected and 95%CI.RESULTS: The typing HLA in the "atypical" populations show that 92.47% patients presented at list one type 1 diabetes associated HLA alleles(DQB1*0201-0302 and DR 3-4) and 7.53% had two of its. The results showed for categorical variables(family history, presence or absence of hypertension and/or dyslipidemia, reason for initial consultation) the only difference found was at dyslipidemia(OR = 0.45, 0.243 < OD < 0.822(P < 0.001). In relation to continuous variables we found significant differences between atypical vs classic only in cholesterol(5.07 ± 1.1 vs 5.56 ± 1.5, P < 0.05), high density lipoproteins(1.23 ± 0.3 vs 1.33 ± 0.3, P < 0.05) and low density lipoproteins(2.86 ± 0.9 vs 3.38 ± 1.7, P < 0.01). None of the variables had discriminating power when logistic regression was done.CONCLUSION: We propose an algorithm including HLA genotyping as a tool to discriminate atypical patients, complementing international treatment guidelines for complex patients.
