The Video intervention to Inspire Treatment Adherence for Life (VITAL Start): protocol for a multisite randomized controlled trial of a brief video-based intervention to improve antiretroviral adherence and retention among HIV-infected pregnant women in Malawi.

BACKGROUND: Improving maternal antiretroviral therapy (ART) retention and adherence is a critical challenge facing prevention of mother-to-child transmission (PMTCT) of HIV programs. There is an urgent need for evidence-based, cost-effective, and scalable interventions to improve maternal adherence and retention that can be feasibly implemented in overburdened health systems. Brief video-based interventions are a promising but underutilized approach to this crisis. We describe a trial protocol to evaluate the effectiveness and implementation of a standardized educational video-based intervention targeting HIV-infected pregnant women that seeks to optimize their ART retention and adherence by providing a VITAL Start (Video intervention to Inspire Treatment Adherence for Life) before committing to lifelong ART. METHODS: This study is a multisite parallel group, randomized controlled trial assessing the effectiveness of a brief facility-based video intervention to optimize retention and adherence to ART among pregnant women living with HIV in Malawi. A total of 892 pregnant women living with HIV and not yet on ART will be randomized to standard-of-care pre-ART counseling or VITAL Start. The primary outcome is a composite of retention and adherence (viral load < 1000 copies/ml) 12 months after starting ART. Secondary outcomes include assessments of behavioral adherence (self-reported adherence, pharmacy refill, and tenofovir diphosphate concentration), psychosocial impact, and resource utilization. We will also examine the implementation of VITAL Start via surveys and qualitative interviews with patients, partners, and health care workers and conduct cost-effectiveness analyses. DISCUSSION: This is a robust evaluation of an innovative facility-based video intervention for pregnant women living with HIV, with the potential to improve maternal and infant outcomes. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03654898. Registered on 31 August 2018.

VITAL Start: Video-Based Intervention to Inspire Treatment Adherence for Life-Pilot of a Novel Video-Based Approach to HIV Counseling for Pregnant Women Living with HIV.

We developed and piloted a video-based intervention targeting HIV-positive pregnant women to optimize antiretroviral therapy (ART) retention and adherence by providing a VITAL Start (Video-intervention to Inspire Treatment Adherence for Life) before ART. VITAL Start (VS) was grounded in behavior-determinant models and developed through an iterative multi-stakeholder process. Of 306 pregnant women eligible for ART, 160 were randomized to standard of care (SOC), 146 to VS and followed for one-month. Of those assigned to VS, 100% completed video-viewing; 96.5% reported they would recommend VS. Of 11 health workers interviewed, 82% preferred VS over SOC; 91% found VS more time-efficient. Compared to SOC, VS group had greater change in HIV/ART knowledge (p < 0.01), trend towards being more likely to start ART (p = 0.07), and better self-reported adherence (p = 0.02). There were no significant group differences in 1-month retention and pharmacy pill count. VITAL Start was highly acceptable, feasible, with promising benefits to ART adherence.

Grey and white matter abnormalities in temporal lobe epilepsy with and without mesial temporal sclerosis.

Temporal lobe epilepsy with (TLE-mts) and without (TLE-no) mesial temporal sclerosis display different patterns of cortical neuronal loss, suggesting that the distribution of white matter damage may also differ between the sub-groups. The purpose of this study was to examine patterns of white matter damage in TLE-mts and TLE-no and to determine if identified changes are related to neuronal loss at the presumed seizure focus. The 4 T diffusion tensor imaging (DTI) and T1-weighted data were acquired for 22 TLE-mts, 21 TLE-no and 31 healthy controls. Tract-based spatial statistics (TBSS) was used to compare fractional anisotropy (FA) maps and voxel-based morphometry (VBM) was used to identify grey matter (GM) volume atrophy. Correlation analysis was conducted between the FA maps and neuronal loss at the presumed seizure focus. In TLE-mts, reduced FA was identified in the genu, body and splenium of the corpus callosum, bilateral corona radiata, cingulum, external capsule, ipsilateral internal capsule and uncinate fasciculus. In TLE-no, FA decreases were identified in the genu, the body of the corpus callosum and ipsilateral anterior corona radiata. The FA positively correlated with ipsilateral hippocampal volume. Widespread extra-focal GM atrophy was associated with both sub-groups. Despite widespread and extensive GM atrophy displaying different anatomical patterns in both sub-groups, TLE-mts demonstrated more extensive FA abnormalities than TLE-no. The microstructural organization in the corpus callosum was related to hippocampal volume in both patients and healthy subjects demonstrating the association of these distal regions.

A two-level multimodality imaging Bayesian network approach for classification of partial epilepsy: preliminary data.

BACKGROUND: Quantitative neuroimaging analyses have demonstrated gray and white matter abnormalities in group comparisons of different types of non-lesional partial epilepsy. It is unknown to what degree these type-specific patterns exist in individual patients and if they could be exploited for diagnostic purposes. In this study, a two-level multi-modality imaging Bayesian network approach is proposed that uses information about individual gray matter volume loss and white matter integrity to classify non-lesional temporal lobe epilepsy with (TLE-MTS) and without (TLE-no) mesial-temporal sclerosis and frontal lobe epilepsy (FLE). METHODS: 25 controls, 19 TLE-MTS, 22 TLE-no and 14 FLE were studied on a 4T MRI and T1 weighted structural and DTI images acquired. Spatially normalized gray matter (GM) and fractional anisotropy (FA) abnormality maps (binary maps with voxels 1 SD below control mean) were calculated for each subject. At the first level, each group's abnormality maps were compared with those from all the other groups using Graphical-Model-based Morphometric Analysis (GAMMA). GAMMA uses a Bayesian network and a Markov random field based contextual clustering method to produce maps of voxels that provide the maximal distinction between two groups and calculates a probability distribution and a group assignment based on this information. The information was then combined in a second level Bayesian network and the probability of each subject to belong to one of the three epilepsy types calculated. RESULTS: The specificities of the two level Bayesian network to distinguish between the three patient groups were 0.87 for TLE-MTS and TLE-no and 0.86 for FLE, the corresponding sensitivities were 0.84 for TLE-MTS, 0.72 for TLE-no and 0.64 for FLE. CONCLUSION: The two-level multi-modality Bayesian network approach was able to distinguish between the three epilepsy types with a reasonably high accuracy even though the majority of the images were completely normal on visual inspection.