Accuracy of immunological criteria for identifying virological failure in children on antiretroviral therapy - The IeDEA Southern Africa Collaboration

Objectives  To determine the diagnostic accuracy of World Health Organization (WHO) 2010 and 2006 as well as United States Department of Health and Human Services (DHHS) 2008 definitions of immunological failure for identifying virological failure (VF) in children on antiretroviral therapy (ART). Methods  Analysis of data from children (<16 years at ART initiation) at South African ART sites at which CD4 count/per cent and HIV-RNA monitoring are performed 6-monthly. Incomplete virological suppression (IVS) was defined as failure to achieve ≥1 HIV-RNA ≤400 copies/ml between 6 and 15 months on ART and viral rebound (VR) as confirmed HIV-RNA ≥5000 copies/ml in a child on ART for ≥18 months who had achieved suppression during the first year on treatment. Results  Among 3115 children [median (interquartile range) age 48 (20-84) months at ART initiation] on treatment for ≥1 year, sensitivity of immunological criteria for IVS was 10%, 6% and 26% for WHO 2006, WHO 2010 and DHHS 2008 criteria, respectively. The corresponding positive predictive values (PPV) were 31%, 20% and 20%. Diagnostic accuracy for VR was determined in 2513 children with ≥18 months of follow-up and virological suppression during the first year on ART with sensitivity of 5% (WHO 2006/2010) and 27% (DHHS 2008). PPV results were 42% (WHO 2010), 43% (WHO 2006) and 20% (DHHS 2008). Conclusion  Current immunological criteria are unable to correctly identify children failing ART virologically. Improved access to viral load testing is needed to reliably identify VF in children.

Loss to programme between HIV diagnosis and initiation of antiretroviral therapy in sub-Saharan Africa: systematic review and meta-analysis

Objectives  To assess the proportion of patients lost to programme (died, lost to follow-up, transferred out) between HIV diagnosis and start of antiretroviral therapy (ART) in sub-Saharan Africa, and determine factors associated with loss to programme. Methods  Systematic review and meta-analysis. We searched PubMed and EMBASE databases for studies in adults. Outcomes were the percentage of patients dying before starting ART, the percentage lost to follow-up, the percentage with a CD4 cell count, the distribution of first CD4 counts and the percentage of eligible patients starting ART. Data were combined using random-effects meta-analysis. Results  Twenty-nine studies from sub-Saharan Africa including 148 912 patients were analysed. Six studies covered the whole period from HIV diagnosis to ART start. Meta-analysis of these studies showed that of the 100 patients with a positive HIV test, 72 (95% CI 60-84) had a CD4 cell count measured, 40 (95% CI 26-55) were eligible for ART and 25 (95% CI 13-37) started ART. There was substantial heterogeneity between studies (P < 0.0001). Median CD4 cell count at presentation ranged from 154 to 274 cells/μl. Patients eligible for ART were less likely to become lost to programme (25%vs. 54%, P < 0.0001), but eligible patients were more likely to die (11%vs. 5%, P < 0.0001) than ineligible patients. Loss to programme was higher in men, in patients with low CD4 cell counts and low socio-economic status and in recent time periods. Conclusions  Monitoring and care in the pre-ART time period need improvement, with greater emphasis on patients not yet eligible for ART.

The role of targeted viral load testing in diagnosing virological failure in children on antiretroviral therapy with immunological failure

Objectives  To determine the improvement in positive predictive value of immunological failure criteria for identifying virological failure in HIV-infected children on antiretroviral therapy (ART) when a single targeted viral load measurement is performed in children identified as having immunological failure. Methods  Analysis of data from children (<16 years at ART initiation) at South African ART sites at which CD4 count/per cent and HIV-RNA monitoring are performed 6-monthly. Immunological failure was defined according to both WHO 2010 and United States Department of Health and Human Services (DHHS) 2008 criteria. Confirmed virological failure was defined as HIV-RNA >5000 copies/ml on two consecutive occasions <365 days apart in a child on ART for ≥18 months. Results  Among 2798 children on ART for ≥18 months [median (IQR) age 50 (21-84) months at ART initiation], the cumulative probability of confirmed virological failure by 42 months on ART was 6.3%. Using targeted viral load after meeting DHHS immunological failure criteria rather than DHHS immunological failure criteria alone increased positive predictive value from 28% to 82%. Targeted viral load improved the positive predictive value of WHO 2010 criteria for identifying confirmed virological failure from 49% to 82%. Conclusion  The addition of a single viral load measurement in children identified as failing immunologically will prevent most switches to second-line treatment in virologically suppressed children.

Simulating Energy Transfer and Upconversion in β-NaYF 4 : Yb 3+ , Tm 3+

The design of upconversion phosphors with higher quantum yield requires a deeper understanding of the detailed energy transfer and upconversion processes between active ions inside the material. Rate equations can model those processes by describing the populations of the energy levels of the ions as a function of time. However, this model presents some drawbacks: energy migration is assumed to be infinitely fast, it does not determine the detailed interaction mechanism (multipolar or exchange), and it only provides the macroscopic averaged parameters of interaction. Hence, a rate equation model with the same parameters cannot correctly predict the time evolution of upconverted emission and power dependence under a wide range of concentrations of active ions. We present a model that combines information about the host material lattice, the concentration of active ions, and a microscopic rate equation system. The extent of energy migration is correctly taken into account because the energy transfer processes are described on the level of the individual ions. This model predicts the decay curves, concentration, and excitation power dependences of the emission. This detailed information can be used to predict the optimal concentration that results in the maximum upconverted emission.