title: CD4 count outperforms World Health Organization clinical algorithm for point-of-care HIV diagnosis among hospitalised HIV-exposed Malawian infants.
abstract: OBJECTIVE
  To determine, for the WHO algorithm for point-of-care diagnosis of HIV infection, the agreement levels between paediatricians and non-physician clinicians, and to compare sensitivity and specificity profiles of the WHO algorithm and different CD4 thresholds against HIV PCR testing in hospitalised Malawian infants.
  
  
  METHODS
  In 2011, hospitalised HIV-exposed infants <12 months in Lilongwe, Malawi, were evaluated independently with the WHO algorithm by both a paediatrician and clinical officer. Blood was collected for CD4 and molecular HIV testing (DNA or RNA PCR). Using molecular testing as the reference, sensitivity, specificity and positive predictive value (PPV) were determined for the WHO algorithm and CD4 count thresholds of 1500 and 2000 cells/mm(3) by paediatricians and clinical officers.
  
  
  RESULTS
  We enrolled 166 infants (50% female, 34% <2 months, 37% HIV infected). Sensitivity was higher using CD4 thresholds (<1500, 80%; <2000, 95%) than with the algorithm (physicians, 57%; clinical officers, 71%). Specificity was comparable for CD4 thresholds (<1500, 68%, <2000, 50%) and the algorithm (paediatricians, 55%, clinical officers, 50%). The positive predictive values were slightly better using CD4 thresholds (<1500, 59%, <2000, 52%) than the algorithm (paediatricians, 43%, clinical officers 45%) at this prevalence.
  
  
  CONCLUSIONS
  Performance by the WHO algorithm and CD4 thresholds resulted in many misclassifications. Point-of-care CD4 thresholds of <1500 cells/mm(3) or <2000 cells/mm(3) could identify more HIV-infected infants with fewer false positives than the algorithm. However, a point-of-care option with better performance characteristics is needed for accurate, timely HIV diagnosis.
authors.affiliation: University of North Carolina Project Lilongwe, Lilongwe, Malawi.
authors.forename: Madalitso
authors.initials: M
authors.lastname: Maliwichi
authors.forename: Nora E
authors.initials: NE
authors.lastname: Rosenberg
authors.forename: Rebekah
authors.initials: R
authors.lastname: Macfie
authors.forename: Dan
authors.initials: D
authors.lastname: Olson
authors.forename: Irving
authors.initials: I
authors.lastname: Hoffman
authors.forename: Charles M
authors.initials: CM
authors.lastname: van der Horst
authors.forename: Peter N
authors.initials: PN
authors.lastname: Kazembe
authors.forename: Mina C
authors.initials: MC
authors.lastname: Hosseinipour
authors.forename: Eric D
authors.initials: ED
authors.lastname: McCollum
mesh_terms: D000465:Algorithms; D018791:CD4 Lymphocyte Count; D015496:CD4-Positive T-Lymphocytes / Q000378:metabolism*; D005260:Female; D015658:HIV Infections / Q000175:diagnosis*; D006282:Health Personnel; D006760:Hospitalization; D006801:Humans; D007223:Infant; D018445:Infectious Disease Transmission, Vertical; D008295:Malawi; D008297:Male; D019095:Point-of-Care Systems; D012016:Reference Values; D012680:Sensitivity and Specificity; D014944:World Health Organization
keywords: Africa; Afrique; HIV; VIH; algorithme clinique; algoritmo clínico; clinical algorithm; diagnostic précoce; diagnóstico in situ; diagnóstico infantil temprano; early infant diagnosis; lieu des soins; paediatric; pediátrico; point-of-care; pédiatrique; África
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