Norwich Medical School is a medical school based at the University of East Anglia, in Norwich, England. It is part of the Faculty of Medicine and Health sciences at the university. The first intake of students was in 2002. The school has a 5-year MBBS course, with the possibility of intercalation after year 3 or 4.
Introduction Surgery in patients with diabetes mellitus is associated with increased morbidity and mortality compared with those who do not have diabetes mellitus. This is likely multifactorial and could be attributed to organisational issues; dysglycaemia; hospital-acquired diabetic ketoacidosis; errors with insulin prescribing and administration; issues with fluids and electrolytes; and systemic and surgical site infections. There was a need to update guidance for the peri-operative management of diabetes mellitus given improvements in our understanding, introduction of novel drugs and development of wearable technologies. Methods This was a multidisciplinary consensus statement with a diverse authorship group, including diabetologists; anaesthetists; surgeons; pharmacists; surgical diabetes inpatient specialist nurses; and patients with lived experience. We undertook a directed literature search and a three-round Delphi process to develop, refine and agree recommendations. Results Following three rounds, 38 recommendations were included, spanning all phases of the peri-operative pathway. Recommendations were made for organisations and general principles for the management of patients with diabetes, aiming to improve pathways, implement protocols and support training. We prioritise individualised care plans, encourage clinical judgement regarding proceeding with surgery with out-of-range HbA1c concentrations and recommend ensuring appropriate insulin regimens are prescribed and administered. We also provide guidance for capillary blood glucose and ketone monitoring and management; safe handovers of care; and multidisciplinary care plans for the peri-operative use of wearables. Discussion This consensus statement provides principles to be applied throughout the entire peri-operative pathway by healthcare professionals, institutions and patients. It is hoped that the implementation of these key recommendations will improve experience and outcomes for patients with diabetes mellitus having surgery.
Artificial Intelligence (AI) played a transformative role in accelerating vaccine development during the COVID-19 pandemic. By enabling computational triage of antigens, AI reduced candidate attrition through early identification of sequences with favorable immunogenicity and safety. Integrated pipelines using epitope prediction, structure modeling, and in silico assays enabled rapid prototyping and early testing. AI supported rapid mRNA optimization, adaptive clinical trial design, and real-time pharmacovigilance. This chapter explores AI's roles across the vaccine pipeline, from early discovery to public health policy modeling. Real-world case studies, including Pfizer-BioNTech and Moderna, illustrate its impact. AI also opens new avenues for personalized vaccines, immunotherapies, and future pandemic readiness through machine learning, deep learning, and natural language processing.
Introduction:Approximately 600,000 people die every year in the United Kingdom including 24,000 who die in the Emergency Department (ED). The National Audit of Care at the End of Life looks at the care of dying people during their last hospital admission. However, patients who die in the ED are excluded from this audit and therefore little is currently known about this population. Purpose:This service evaluation aimed to describe the population who died in a 12-month period in five NHS EDs, including whether palliative care teams were involved. Patients and methods:Records from all eligible patients in the 12 months from 1st June 2022 were reviewed. Anonymised data from each site was collated and compared. Results:There were 704,303 ED patient presentations across the 5 sites, and 852 deaths. The mean age of death was 74.04 with a slight male preponderance of 56.8%. Between sites there was a wide range (0.4%-25%) of involvement from palliative care with these patients whilst in ED. The overwhelming majority had a medical (rather than surgical or traumatic) cause of death. Conclusion:Research is needed in order to ascertain how care can be improved for this group of patients. More UK-centric work is required to understand the characteristics of patients who die in EDs including their cause of death and ethnicity, as well as an exploration of whether greater palliative care collaboration in ED improves patient, family and staff experience.
Vulval squamous cell carcinoma (VSCC) accounts for ∼90% of vulval cancers in England. Diagnosis is often delayed due to nonspecific presentations, limited screening, poor awareness and reluctance to undergo intimate examinations. Other than sentinel lymph node biopsies, management advances have been scarce. This national retrospective cohort study describes epidemiological trends, diagnostic stage, referral routes, treatment and survival in England (2013–2022) among self-identifying women.
The growing complexity of biological threats necessitates advanced biosurveillance systems capable of three core functions. Traditional surveillance faces challenges due to fragmented data, delayed information sharing, and weak coordination between public health and environmental sectors. Advances in artificial intelligence, particularly in machine learning, deep learning, and data fusion, enable integration of diverse data sources such as epidemiological, environmental, remote sensing, genomic, and digital health data for active risk assessment. Explainable AI improves transparency and supports informed decision-making, while multi-source analytics strengthen early warning, situational awareness, and risk forecasting for emerging threats linked to zoonoses and climate change. Developing AI-driven biosurveillance systems with ethical, transparent, and resilient One Health approaches is essential to address issues of data quality, bias, privacy, and governance.
