Background: Enhanced surveillance and molecular characterisation studies of hepatitis E virus (HEV) in England and Wales have been undertaken since 2003. The dynamics of hepatitis E have changed recently with an increase in the number of indigenous cases and an observed viral shift.
Methods: HEV antibody and RNA data were analysed to ascertain the annual number of acute infections, the HEV genotype disposition and viral phylogeny. These data were investigated in the context of collected travel history and demographic data.
Results: In total, 2713 acute hepatitis E cases were diagnosed, of which 1376 were indigenous infections. Travel associated cases remained steady and mainly associated with Genotype 1 infections. In contrast, major fluctuations were noted in indigenously-acquired cases with a dramatic year on year increase during 2010-2012. Molecular characterisation demonstrated indigenous infections to cluster into two distinct phylogenetic groups with the emergence of a novel group of Genotype 3 viruses coinciding with the recent increase in cases.
Conclusions: HEV infection rates are dynamic in England and Wales, influenced by changing trends in indigenously-acquired cases. The recent increase in indigenous cases and the emergence of indigenous viruses not commonly circulating prior to 2010 suggest that the risk of acquiring HEV has changed.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1093/infdis/jit652 | DOI Listing |
Philos Trans R Soc Lond B Biol Sci
January 2025
University College London Institute for Sustainable Resources, Central House, 14 Upper Woburn Place, London WC1H 0NN, UK.
The natural capital concept positions the natural environment as an asset, crucial for the flow of goods and benefits to humanity. There is a growing trend in applying this concept in marine environmental management in the United Kingdom (UK). This study evaluates six varied marine decisions across England, Scotland and Wales.
View Article and Find Full Text PDFAust N Z J Public Health
January 2025
School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, New Lambton, NSW, 2305, Australia; Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, Australia. Electronic address:
Intern Med J
January 2025
Cardiology Department, John Hunter Hospital Newcastle, Newcastle, New South Wales, Australia.
Background: Clozapine has demonstrated superiority in improving both positive and negative symptoms of treatment-resistant schizophrenia; however, there are associated treatment-limiting side effects, including myocarditis, cardiomyopathy and agranulocytosis.
Aim: This retrospective cohort study describes the prevalence of myocarditis, left ventricular (LV) dysfunction, cardiovascular risk factors and outcomes in a cohort of patients maintained on clozapine therapy.
Methods: Data were retrospectively collated from patients who had a diagnosis of schizophrenia, had been managed with clozapine at any stage during their care and undergone at least one echocardiogram.
BMJ Support Palliat Care
January 2025
Palliative Care, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
Introduction: The National Audit of Care at the End of Life reports the quality of care provided to people dying in hospital. This paper reports the bereavement (quality) survey data about the families' view of care provided to the patient and support provided to the family.
Methods: Anonymised summary data were retrieved from 'Key findings for patients and carers on the quality of end of life care in acute and community hospitals' reports 2019-2022 and the summary report 2018.
EClinicalMedicine
August 2024
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom.
Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!