Developing a matrix to identify and prioritise research recommendations in HIV Prevention

BACKGROUND: HIV prevention continues to be problematic in the UK, as it does globally. The UK Department of Health has a strategic direction with greater focus on prevention as part of its World Class Commissioning Programme. There is a need for targeted evidence-based prevention initiatives. This is an exploratory study to develop an evidence mapping tool in the form of a matrix: this will be used to identify important gaps in contemporary HIV prevention evidence relevant to the UK. It has the potential to aid prioritisation in future research.METHODS: Categories for prevention and risk groups were developed for HIV prevention in consultation with external experts. These were used as axes on a matrix tool to map evidence. Systematic searches for publications on HIV prevention were undertaken using electronic databases for primary and secondary research undertaken mainly in UK, USA, Canada, Australia and New Zealand, 2006-9. Each publication was screened for inclusion then coded. The risk groups and prevention areas in each paper were counted: several publications addressed multiple risk groups. The counts were exported to the matrix and clearly illustrate the concentrations and gaps of literature in HIV prevention.RESULTS: 716 systematic reviews, randomised control trials and other primary research met the inclusion criteria for HIV prevention. The matrix identified several under researched areas in HIV prevention.CONCLUSIONS: This is the first categorisation system for HIV prevention and the matrix is a novel tool for evidence mapping. Some important yet under-researched areas have been identified in HIV prevention evidence: identifying the undiagnosed population; international adaptation; education; intervention combinations; transgender; sex-workers; heterosexuals and older age groups.<br/

Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis

\ua9 The Author(s) 2024.Metabolic dysfunction-associated steatohepatitis (MASH) is a major cause of liver-related morbidity and mortality, yet treatment options are limited. Manual scoring of liver biopsies, currently the gold standard for clinical trial enrollment and endpoint assessment, suffers from high reader variability. This study represents the most comprehensive multisite analytical and clinical validation of an artificial intelligence (AI)-based pathology system, AI-based measurement of metabolic dysfunction-associated steatohepatitis (AIM-MASH), to assist pathologists in MASH trial histology scoring. AIM-MASH demonstrated high repeatability and reproducibility compared to manual scoring. AIM-MASH-assisted reads by expert MASH pathologists were superior to unassisted reads in accurately assessing inflammation, ballooning, MAS ≥ 4 with ≥1 in each score category and MASH resolution, while maintaining non-inferiority in steatosis and fibrosis assessment. These findings suggest that AIM-MASH could mitigate reader variability, providing a more reliable assessment of therapeutics in MASH clinical trials

Rifaximin in non-alcoholic steatohepatitis: An open-label pilot study

Aim Gut microbial dysbiosis is implicated in the pathogenesis of non‐alcoholic steatohepatitis (NASH). We investigated downstream effects of gut microbiota modulation on markers of hepatic inflammation, steatosis, and hepatic and peripheral insulin sensitivity in patients with NASH using rifaximin therapy. Methods Patients with biopsy‐proven NASH and elevated aminotransferase values were included in this open‐label pilot study, all receiving 6 weeks rifaximin 400 mg twice daily, followed by a 6‐week observation period. The primary endpoint was change in alanine aminotransferase (ALT) after 6 weeks of rifaximin. Secondary endpoints were change in hepatic lipid content and insulin sensitivity measured with a hyperinsulinemic–euglycemic clamp. Results Fifteen patients (13 men and 2 women) with a median (range) age of 46 (32–63) years were included. Seven had diabetes on oral hypoglycemic medications and 8 had no diabetes. After 6 weeks of therapy, no differences were seen in ALT (55 [33–191] vs. 63 [41–218] IU/L, P = 0.41), peripheral glucose uptake (28.9 [19.4–48.3] to 25.5 [17.7–47.9] μmol/kg/min, P = 0.30), hepatic insulin sensitivity (35.2 [15.3–51.7]% vs. 30.0 [10.8–50.5]%, P = 0.47), or hepatic lipid content (21.6 [2.2–46.2]% vs. 24.8 [1.7–59.3]%, P = 0.59) before and after rifaximin treatment. After 12 weeks from baseline, serum ALT increased to 83 (30–217) IU/L, P = 0.02. There was a significant increase in the homeostasis model assessment–estimated insulin resistance index (P = 0.05). The urinary metabolic profile indicated a significant reduction in urinary hippurate with treatment, which reverted to baseline after cessation of rifaximin, although there was no consistent difference in relative abundance of fecal microbiota with treatment. Conclusion These data do not indicate a beneficial effect of rifaximin in patients with NASH