Developing a digital phenotype to subdivide adult immunosuppressed COVID-19 outcomes within the English Primary Care Sentinel Network.

Background: Adults classified as immunosuppressed have been disproportionately affected by the COVID-19 pandemic. Compared to the immunocompetent, certain patients are at increased risk of suboptimal vaccine response and adverse health outcomes if infected. However, there has been insufficient work to pinpoint where these risks concentrate within the immunosuppressed spectrum; surveillance efforts typically treat the immunosuppressed as a single entity, leading to wide confidence intervals.

Combining tissue biomarkers with mpMRI to diagnose clinically significant prostate cancer. Analysis of 21 biomarkers in the PICTURE study.

Background: Serum PSA and digital rectal examination remain the key diagnostic tools for detecting prostate cancer. However, due to the limited specificity of serum PSA, the applicability of this marker continues to be controversial. Recent use of image-guided biopsy along with pathological assessment and the use of biomarkers has dramatically improved the diagnosis of clinically significant cancer.

Pressure ulcer prevention for people with long-term neurological conditions (LTNCs) who self-manage care and live at home.

Aim: To develop a Theory of Change (ToC) pathway to facilitate the development of a multi-component intervention package supporting pressure Ulcer (PU) risk identification and management, in partnership with people with Long Term Neurological Conditions (LTNC) who self-manage care and live at home, their informal carers and PAs.

Methods: A participatory approach, with extensive input from those whose lives are the focus of the research, was used throughout the 4 interlinked work packages (WP): Iterative data analysis was undertaken with emerging findings from each WP informing subsequent stages of the study.

Findings: Overall, 74 participants contributed across the 4 WPs, incorporating 31 Service Users (SU), 8 carers, 9 Personal Assistants (PAs) and 26 professional stakeholders.

ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.

Purpose: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer.

Methods: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning.

Interim 2023/2024 Season Influenza Vaccine Effectiveness in Primary and Secondary Care in the United Kingdom.

Background: We report 2023/2024 season interim influenza vaccine effectiveness for three studies, namely, primary care in Great Britain, hospital settings in Scotland and hospital settings in England.

Methods: A test negative design was used to estimate vaccine effectiveness.

Results: Estimated vaccine effectiveness against all influenzas ranged from 63% (95% confidence interval 46 to 75%) to 65% (41 to 79%) among children aged 2-17, from 36% (20 to 49%) to 55% (43 to 65%) among adults 18-64 and from 40% (29 to 50%) to 55% (32 to 70%) among adults aged 65 and over.