Effectiveness of Patient Adherence Groups as a Model of Care for Stable Patients on Antiretroviral Therapy in Khayelitsha,Cape Town,South Africa

Background

Innovative models of care are required to cope with the ever-increasing number of patients on antiretroviral therapy in the most affected countries. This study, in Khayelitsha, South Africa, evaluates the effectiveness of a group-based model of care run predominantly by non-clinical staff in retaining patients in care and maintaining adherence.

Methods and Findings

Participation in “adherence clubs” was offered to adults who had been on ART for at least 18 months, had a current CD4 count >200 cells/ml and were virologically suppressed. Embedded in an ongoing cohort study, we compared loss to care and virologic rebound in patients receiving the intervention with patients attending routine nurse-led care from November 2007 to February 2011. We used inverse probability weighting to estimate the intention-to-treat effect of adherence club participation, adjusted for measured baseline and time-varying confounders. The principal outcome was the combination of death or loss to follow-up. The secondary outcome was virologic rebound in patients who were virologically suppressed at study entry. Of 2829 patients on ART for >18 months with a CD4 count above 200 cells/µl, 502 accepted club participation. At the end of the study, 97% of club patients remained in care compared with 85% of other patients. In adjusted analyses club participation reduced loss-to-care by 57% (hazard ratio [HR] 0.43, 95% CI = 0.21–0.91) and virologic rebound in patients who were initially suppressed by 67% (HR 0.33, 95% CI = 0.16–0.67).

Discussion

Patient adherence groups were found to be an effective model for improving retention and documented virologic suppression for stable patients in long term ART care. Out-of-clinic group-based models facilitated by non-clinical staff are a promising approach to assist in the long-term management of people on ART in high burden low or middle-income settings.     

Exploring the Spatial Association between Social Deprivation and Cardiovascular Disease Mortality at the Neighborhood Level

Cardiovascular disease (CVD), the leading cause of death in the United States, is impacted by neighborhood-level factors including social deprivation. To measure the association between social deprivation and CVD mortality in Harris County, Texas, global (Ordinary Least Squares (OLS) and local (Geographically Weighted Regression (GWR)) models were built. The models explored the spatial variation in the relationship at a census-tract level while controlling for age, income by race, and education. A significant and spatially varying association (p < .01) was found between social deprivation and CVD mortality, when controlling for all other factors in the model. The GWR model provided a better model fit over the analogous OLS model (R² = .65 vs. .57), reinforcing the importance of geography and neighborhood of residence in the relationship between social deprivation and CVD mortality. Findings from the GWR model can be used to identify neighborhoods at greatest risk for poor health outcomes and to inform the placement of community-based interventions.     

Problems,successes and challenges for the application of dispersion-corrected density-functional theory combined with dispersion-based implicit solvent models to large-scale hydrophobic self-assembly and polymorphism

The recent advent of dispersion-corrected density-functional theory (DFT) methods allows for quantitative modelling of molecular self-assembly processes, and we consider what is required to develop applications to the formation of large self-assembled monolayers (SAMs) on hydrophobic surfaces from organic solution. Focus is on application of the D3 dispersion correction of Grimme combined with the solvent dispersion model of Floris, Tomasi and Pascual–Ahuir to simulate observed scanning-tunnelling microscopy (STM) images of various polymorphs of tetraalkylporphyrin SAMs on highly oriented pyrolytic graphite surfaces. The most significant problem is identified as the need to treat SAM structures that are incommensurate with those of the substrate, providing a challenge to the use of traditional periodic-imaging boundary techniques. Using nearby commensurate lattices introduces non-systematic errors into calculated lattice constants and free energies of SAM formation that are larger than experimental uncertainties and polymorph differences. Developing non-periodic methods for polymorph interface simulation also remains a challenge. Despite these problems, existing methods can be used to interpret STM images and SAM atomic structures, distinguishing between multiple feasible polymorph types. They also provide critical insight into the factors controlling polymorphism. All this stems from a delicate balance that the intermolecular D3 and solvent Floris, Tomasi and Pascual–Ahuir corrections provide. Combined optimised treatments should yield fully quantitative approaches in the future.     

Exploring the diversity of marine-derived fungal polyketide synthases

Using an approach based on polymerase chain reaction (PCR), we examined the diversity of polyketide synthase (PKS) genes present in 160 marine fungal isolates, representing 142 species. We obtained ketosynthase (KS) domain PCR products from 99 fungal isolates, representing Dothideomycetes, Sordariomycetes, Eurotiomycetes, and incertae sedis. Sequence similarity searches and phylogenetic analysis of 29 marine partial-KS-encoding sequences revealed domains predicted to encode reducing, nonreducing, and 6-methylsalicylic acid PKSs. Bioinformatic analysis of an alignment of the KS sequences from marine-derived fungi revealed no unique motifs in this region. However, several specificity-determining positions were apparent between fungal 6-methylsalicylic acid PKSs as compared with either reducing or nonreducing PKSs. Evaluation of these positions in the context of a modelled three-dimensional protein structure highlighted their potential use as PKS classification markers. Evaluating primer-binding sites was necessary to obtain KS domain fragments from putative PKSs while maintaining a level of sequence information adequate to properly classify and characterize them.     

Mouse inbred strain differences in ethanol drinking to intoxication

Recently, we described a simple procedure, Drinking in the Dark (DID), in which C57BL/6J mice self-administer ethanol to a blood ethanol concentration (BEC) above 1 mg/ml. The test consists of replacing the water with 20% ethanol in the home cage for 4 h early during the dark phase of the light/dark cycle. Three experiments were conducted to explore this high ethanol drinking model further. In experiment 1, a microanalysis of C57BL/6J behavior showed that the pattern of ethanol drinking was different from routine water intake. In experiment 2, drinking impaired performance of C57BL/6J on the accelerating rotarod and balance beam. In experiment 3, 12 inbred strains were screened to estimate genetic influences on DID and correlations with other traits. Large, reliable differences in intake and BEC were detected among the strains, with C57BL/6J showing the highest values. Strain means were positively correlated with intake and BEC in the standard (24 h) and a limited (4 h) two-bottle ethanol vs. water test, but BECs reached higher levels for DID. Strain mean correlations with other traits in the Mouse Phenome Project database supported previously reported genetic relationships of high ethanol drinking with low chronic ethanol withdrawal severity and low ethanol-conditioned taste aversion. We extend these findings by showing that the correlation estimates remain relatively unchanged even after correcting for phylogenetic relatedness among the strains, thus relaxing the assumption that the strain means are statistically independent. We discuss applications of the model for finding genes that predispose pharmacologically significant drinking in mice.