Nonvirologic Algorithms for Predicting HIV Infection Among HIV-exposed Infants Younger Than 12 Weeks of Age

Abstract

Background Early initiation of antiretroviral therapy (ART) has been shown to reduce mortality among perinatally HIV-infected infants, but availability of virologic testing remains limited in many settings. Methods We collected cross-sectional data from mother-infant pairs in three primary care clinics in Lusaka, Zambia to develop predictive models for HIV infection among infants age <12 weeks. We evaluated algorithm performance for all possible combinations of selected parameters using an iterative approach. In primary analysis, we identified the model with the highest combined sensitivity and specificity. Results Between July 2009 and May 2011, 822 eligible HIV-infected mothers and their HIV-exposed infants were enrolled; of these, 44 (5.4%) infants were diagnosed with HIV. We evaluated 382,155,260 different parameter combinations for predicting infant HIV infection. The algorithm with highest combined sensitivity and specificity required 5 of the following 7 parameter thresholds : infant CD8% > 22, infant CD4% ≤ 44, infant weight-for-age Z score ≤ 0, infant CD4 ≤ 1600 cells/μL, infant CD8 > 2200 cells/μL, maternal CD4 ≤ 600 cells/μL, and mother not currently on ART for HIV treatment. This combination had a sensitivity of 90.3%, specificity of 78.4%, positive predictive value (PPV) of 22.4%, negative predictive value (NPV) of 99.2%, and area under the curve (AUC) of 0.844. Conclusion Predicting HIV infection in HIV-exposed infants in this age group is difficult using clinical and immunologic parameters. Expansion of PCR capacity in resource-limited settings remains urgently needed.

Risk factors for carbapenem-resistant K. pneumoniae bloodstream infection and predictors of mortality in Chinese paediatric patients

“…Because there are fewer therapeutic options in children [ 13 , 14 ], the treatment of CRKP BSI is a real challenge for the paediatrician. The keys to success in preventing and treating CRKP infections are the implementation of infection control measures and early detection of patients at highest risk [ 14 ].…”