Pre-therapy inflammation and coagulation activation and long-term CD4 count responses to the initiation of antiretroviral therapy

OBJECTIVES Pre-antiretroviral therapy (ART) inflammation and coagulation activation predict clinical outcomes in HIV-positive individuals. We assessed whether pre-ART inflammatory marker levels predicted the CD4 count response to ART. METHODS Analyses were based on data from the Strategic Management of Antiretroviral Therapy (SMART) trial, an international trial evaluating continuous vs. interrupted ART, and the Flexible Initial Retrovirus Suppressive Therapies (FIRST) trial, evaluating three first-line ART regimens with at least two drug classes. For this analysis, participants had to be ART-naïve or off ART at randomization and (re)starting ART and have C-reactive protein (CRP), interleukin-6 (IL-6) and D-dimer measured pre-ART. Using random effects linear models, we assessed the association between each of the biomarker levels, categorized as quartiles, and change in CD4 count from ART initiation to 24 months post-ART. Analyses adjusted for CD4 count at ART initiation (baseline), study arm, follow-up time and other known confounders. RESULTS Overall, 1084 individuals [659 from SMART (26% ART naïve) and 425 from FIRST] met the eligibility criteria, providing 8264 CD4 count measurements. Seventy-five per cent of individuals were male with the mean age of 42 years. The median (interquartile range) baseline CD4 counts were 416 (350-530) and 100 (22-300) cells/μL in SMART and FIRST, respectively. All of the biomarkers were inversely associated with baseline CD4 count in FIRST but not in SMART. In adjusted models, there was no clear relationship between changing biomarker levels and mean change in CD4 count post-ART (P for trend: CRP, P = 0.97; IL-6, P = 0.25; and D-dimer, P = 0.29). CONCLUSIONS Pre-ART inflammation and coagulation activation do not predict CD4 count response to ART and appear to influence the risk of clinical outcomes through other mechanisms than blunting long-term CD4 count gain.

Effect of low count sums on quantitative environmental reconstructions: an example using subfossil chironomids

The concentrations of chironomid remains in lake sediments are very variable and, therefore, chironomid stratigraphies often include samples with a low number of counts. Thus, the effect of low count sums on reconstructed temperatures is an important issue when applying chironomid‐temperature inference models. Using an existing data set, we simulated low count sums by randomly picking subsets of head capsules from surface‐sediment samples with a high number of specimens. Subsequently, a chironomid‐temperature inference model was used to assess how the inferred temperatures are affected by low counts. The simulations indicate that the variability of inferred temperatures increases progressively with decreasing count sums. At counts below 50 specimens, a further reduction in count sum can cause a disproportionate increase in the variation of inferred temperatures, whereas at higher count sums the inferences are more stable. Furthermore, low count samples may consistently infer too low or too high temperatures and, therefore, produce a systematic error in a reconstruction. Smoothing reconstructed temperatures downcore is proposed as a possible way to compensate for the high variability due to low count sums. By combining adjacent samples in a stratigraphy, to produce samples of a more reliable size, it is possible to assess if low counts cause a systematic error in inferred temperatures.

CD4 count at antiretroviral therapy initiation and the risk of loss to follow-up: results from a multicentre cohort study.

BACKGROUND Antiretroviral therapy (ART) initiation is now recommended irrespective of CD4 count. However data on the relationship between CD4 count at ART initiation and loss to follow-up (LTFU) are limited and conflicting. METHODS We conducted a cohort analysis including all adults initiating ART (2008-2012) at three public sector sites in South Africa. LTFU was defined as no visit in the 6 months before database closure. The Kaplan-Meier estimator and Cox's proportional hazards models examined the relationship between CD4 count at ART initiation and 24-month LTFU. Final models were adjusted for demographics, year of ART initiation, programme expansion and corrected for unascertained mortality. RESULTS Among 17 038 patients, the median CD4 at initiation increased from 119 (IQR 54-180) in 2008 to 257 (IQR 175-318) in 2012. In unadjusted models, observed LTFU was associated with both CD4 counts <100 cells/μL and CD4 counts ≥300 cells/μL. After adjustment, patients with CD4 counts ≥300 cells/μL were 1.35 (95% CI 1.12 to 1.63) times as likely to be LTFU after 24 months compared to those with a CD4 150-199 cells/μL. This increased risk for patients with CD4 counts ≥300 cells/μL was largest in the first 3 months on treatment. Correction for unascertained deaths attenuated the association between CD4 counts <100 cells/μL and LTFU while the association between CD4 counts ≥300 cells/μL and LTFU persisted. CONCLUSIONS Patients initiating ART at higher CD4 counts may be at increased risk for LTFU. With programmes initiating patients at higher CD4 counts, models of ART delivery need to be reoriented to support long-term retention.