Nicolas Grundmann1, Peter Iliff, Jeff Stringer, Catherine Wilfert. 1. Stanford University School of Medicine, Medical School Office Building (Room 323), 251 Campus Drive, Stanford, CA 94305-5404, United States of America. nico.grundmann@gmail.com
Abstract
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.
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.
Authors: Gayle G Sherman; Peter A Cooper; Ashraf H Coovadia; Adrian J Puren; Stephanie A Jones; Mantoa Mokhachane; Keith D Bolton Journal: Pediatr Infect Dis J Date: 2005-11 Impact factor: 2.129
Authors: Jeffrey S A Stringer; Isaac Zulu; Jens Levy; Elizabeth M Stringer; Albert Mwango; Benjamin H Chi; Vilepe Mtonga; Stewart Reid; Ronald A Cantrell; Marc Bulterys; Michael S Saag; Richard G Marlink; Alwyn Mwinga; Tedd V Ellerbrock; Moses Sinkala Journal: JAMA Date: 2006-08-16 Impact factor: 56.272
Authors: David E Bourne; MaryLou Thompson; Linnea L Brody; Mark Cotton; Beverly Draper; Ria Laubscher; M Fareed Abdullah; Jonny E Myers Journal: AIDS Date: 2009-01-02 Impact factor: 4.177
Authors: Madalitso Maliwichi; Nora E Rosenberg; Rebekah Macfie; Dan Olson; Irving Hoffman; Charles M van der Horst; Peter N Kazembe; Mina C Hosseinipour; Eric D McCollum Journal: Trop Med Int Health Date: 2014-04-23 Impact factor: 2.622
Authors: Eric D McCollum; Geoffrey A Preidis; Madalitso Maliwichi; Dan Olson; L Madeline McCrary; Peter N Kazembe; Charles van der Horst; Irving Hoffman; Mina C Hosseinipour Journal: J Acquir Immune Defic Syndr Date: 2014-05-01 Impact factor: 3.731
Authors: Saeed Ahmed; Maria H Kim; Nandita Sugandhi; B Ryan Phelps; Rachael Sabelli; Mamadou O Diallo; Paul Young; Dana Duncan; Scott E Kellerman Journal: AIDS Date: 2013-11 Impact factor: 4.177