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Braz. j. infect. dis ; 11(4): 390-394, Aug. 2007. tab
Artículo en Inglés | LILACS | ID: lil-460697

RESUMEN

Genotype testing for HIV-1 drug resistance is useful for selecting antiretroviral drug regimens for patients experiencing therapeutic failure, but the optimal means for interpreting the test results is unknown because many HIV-1 protease and reverse transcriptase (RT) mutations contribute to drug resistance. This study identified common combinations of resistance mutations related to antiretroviral resistance profiles. From April 2002 to March 2004, 101 protease and RT sequences were determined for HIV-1 isolates from patients who were failing antiretroviral therapy. The resistance profile was evaluated using the Stanford Database program. Male patients predominated (76.2 percent), the median age was 38 years, the average CD4 count was 279.21 cells/mm³ and the average viral load was 4.49 log. In relation to protease inhibitors (IP) 31 mutation patterns were detected, 49 mutation patterns were detected in Nucleoside RT Inhibitors (NRTI), and 17 patterns were found in the Non Nucleoside RT Inhibitors (NNRTI). K65R was detected in 5.9 percent of the isolates. The most frequent mutations were: L90M, M184V and K103N related to PI's, NRTI's and NNRTI's, respectively. The best antiretroviral susceptibility was found to be Lopinavir in the PI class and Tenofovir in the NRTI class. The top six mutation patterns accounted for 49 percent of the resistance to PI's, for 38.5 percent of NRTI resistance, and the top two mutation patterns accounted for 40.9 percent of resistance to NNRTI's.


Asunto(s)
Adolescente , Adulto , Anciano , Niño , Femenino , Humanos , Masculino , Persona de Mediana Edad , Fármacos Anti-VIH/uso terapéutico , Farmacorresistencia Viral/genética , Infecciones por VIH/virología , VIH-1 , Mutación , Brasil , Genotipo , Infecciones por VIH/tratamiento farmacológico , Proteasa del VIH/genética , Transcriptasa Inversa del VIH/genética , VIH-1 , ARN Viral/genética , Insuficiencia del Tratamiento , Carga Viral
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