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OBJECTIVE: To develop a new algorithm for the presumptive diagnosis of severe disease associated with human immunodeficiency virus (HIV) infection in children less than 18 months of age for the purpose of identifying children who require antiretroviral therapy (ART). METHODS: A conditional probability model was constructed and non-virologic parameters in various combinations were tested in a hypothetical cohort of 1000 children aged 6 weeks, 6 months and 12 months to assess the sensitivity, specificity, and positive and negative predictive values of these algorithms for identifying children in need of ART. The modelled parameters consisted of clinical criteria, rapid HIV antibody testing and CD4+ T-lymphocyte (CD4) count. FINDINGS: In children younger than 18 months, the best-performing screening algorithm, consisting of clinical symptoms plus antibody testing plus CD4 count, showed a sensitivity ranging from 71% to 80% and a specificity ranging from 92% to 99%. Positive and negative predictive values were between 61% and 97% and between 95% and 96%, respectively. In the absence of virologic tests, this alternate algorithm for the presumptive diagnosis of severe HIV disease makes it possible to correctly initiate ART in 91% to 98% of HIV-positive children who are at highest risk of dying. CONCLUSION: The algorithms presented in this paper have better sensitivity and specificity than clinical parameters, with or without rapid HIV testing, for the presumptive diagnosis of severe disease in HIV-positive children less than 18 months of age. If implemented, they can increase the number of HIV-positive children successfully initiated on ART. |
