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Magnitude and predictors of antiretroviral treatment failure among HIV-infected children in Fiche and Kuyu hospitals, Oromia region, Ethiopia: a retrospective cohort study.

Seid YassinGebremedhin Beedemariam Gebretekle
Published in: Pharmacology research & perspectives (2017)
The objective of the study was to assess the magnitude and predictors of first-line antiretroviral treatment failure among HIV-infected children. A retrospective cohort study was conducted between January 2006 and December 2015. All pediatric patients of <15 years old and who took at least 6 months of ART in Fiche and Kuyu hospitals of Oromia region, Ethiopia were included in the study. Collected data were entered and analyzed using SPSS version 20. Multivariable logistic regression was employed to identify predictors of treatment failure. Data of 269 children were analyzed and majority (53.9%) of the children were males with a mean age of 9.8 ± 3.64 years. Based on the two WHO criteria, overall ART failure was found to be 51 (18.8%), of which 33 (12.26%) had clinical and 18 (6.69%) had immunologic failures. The mean time to the detection of treatment failure was 41 ± 24.96 months. Children's age between 6 and 9 years (AOR = 0.26, 95% CI: 0.09, 0.72) was protective toward treatment failure, while lost to follow-up (AOR = 7.54, 95% CI: 2.35, 24.16), died (AOR = 22.22, 95% CI: 3.75, 131.54), transferred out (AOR = 3.34, 95% CI: 1.41, 7.87), suboptimal adherence to ART (AOR = 4.85, 95% CI: 1.82, 12.93), baseline CD4 count of <50 cells/mm3 (AOR = 4.28, 95% CI: 3.49, 5.9), and WHO advanced clinical stage (AOR = 2.46, 95% CI: 1.14, 5.31) were found to be predictors of treatment failure. The study revealed that the treatment failure is high and the mean time to develop treatment failure is short. The predictors for treatment failure were suboptimal adherence, lost to follow-up, transferred out, initial CD4 count <50 cells/mm3, initial WHO stages 3 and 4. On the other hand, being in the age of 6-9 years is protective from developing treatment failure as compared to the other age category.
Keyphrases
  • hiv infected
  • healthcare
  • young adults
  • combination therapy
  • metabolic syndrome
  • electronic health record
  • insulin resistance
  • hepatitis c virus
  • south africa
  • artificial intelligence