• Login
    • Login
    Advanced Search
    View Item 
    •   UoN Digital Repository Home
    • Journal Articles
    • Faculty of Health Sciences (FHS)
    • View Item
    •   UoN Digital Repository Home
    • Journal Articles
    • Faculty of Health Sciences (FHS)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Performance Of The Integrated Management Of Childhood Illness Algorithm For Diagnosis Of Hiv-1 Infection Among African Infants.

    Thumbnail
    View/Open
    Abstract.pdf (25.42Kb)
    Date
    2012
    Author
    Diener
    Slyker, Jennifer
    Christinei, Gichuh
    Dalton, Wamalwa
    Lara, C.
    Tapia, Kenneth A
    Richardson, Barbra A.
    Dalton, Wamalwa
    Farquhar, Carey
    Overbaugh, Julie Maleche-Obimbo Elizabeth
    Maleche-Obimbo, Elizabeth
    John-Stewart, Grace
    Advisor
    http://profiles.uonbi.ac.ke/cgichuhi/publications/performance-integrated-management-childhood-illness-algorithm diagnosis-hiv-1
    Type
    Article
    Language
    en
    Metadata
    Show full item record

    Abstract
    Objectives: Early infant HIV-1 diagnosis and treatment substantially improve survival. Where virologic HIV-1 testing is unavailable, integrated management of childhood illness (IMCI) clinical algorithms may be used for infant HIV-1 screening. We evaluated the performance of the 2008 WHO IMCI HIV algorithm in a cohort of HIV-exposed Kenyan infants. Methods: From 1999 to 2003, 444 infants had monthly clinical assessments and quarterly virologic HIV-1 testing. Using archived clinical data, IMCI sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated using virologic testing as a gold standard. Linear regression and survival analyses were used to determine the effect of age on IMCI performance and timing of diagnosis. Results: Overall IMCI sensitivity, specificity, PPV, and NPV value were 58, 87, 52, and 90%, respectively. Sensitivity (1.4%) and PPV (14%) were lowest at 1 month of age, when 81% of HIV infections already had occurred. Sensitivity increased with age (P <  0.0001), but remained low throughout infancy (range 1.4–35%). Specificity (range 97–100%) was high at each time point and was not associated with age. Fifty-eight percent of HIV-1-infected infants (50 of 86) were eventually diagnosed by IMCI, and use of IMCI was estimated to delay diagnosis in HIV-infected infants by a median of 5.9 months (P < 0.0001). Conclusion: IMCI had low sensitivity during the first month of life, when the majority of HIV-1 infections had already occurred and initiation of treatment is most critical. Although sensitivity increased with age, the substantial delay in HIV-1 diagnosis using IMCI limits its utility in early infant HIV-1 diagnosis
    URI
    http://profiles.uonbi.ac.ke/cgichuhi/publications/performance-integrated-management-childhood-illness-algorithm-diagnosis-hiv-1
    http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/30157
    http://journals.lww.com/aidsonline/Fulltext/2012/09240/Performance_of_the_integrated_management_of.10.aspx
    http://www.ncbi.nlm.nih.gov/pubmed/22824627
    Citation
    Performance of the integrated management of childhood illness algorithm for diagnosis of HIV-1 infection among African infants., Diener, Lara C., Slyker Jennifer A., Christine Gichuhi, Dalton Wamalwa, Tapia Kenneth A., Richardson Barbra A., Dalton Wamalwa, Farquhar Carey, Overbaugh Julie, Maleche-Obimbo Elizabeth, and John-Stewart Grace , AIDS (London, England), 2012 Sep 24, Volume 26, Issue 15, p.1935-41, (2012)
    Publisher
    University of Nairobi
     
    School of medicine (Paediatrics)
     
    Collections
    • Faculty of Health Sciences (FHS) [10418]

    Copyright © 2022 
    University of Nairobi Library
    Contact Us | Send Feedback

     

     

    Useful Links
    UON HomeLibrary HomeKLISC

    Browse

    All of UoN Digital RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Copyright © 2022 
    University of Nairobi Library
    Contact Us | Send Feedback