Brit J Hosp Med
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Review
Don't forget the children-paediatric patients in mass casualty events and major incident planning.
Major incidents and mass casualty events can affect people of all ages. However, when planning the response to a major incident the focus is often on adult casualties rather than children. ⋯ The new Major Incident Triage Tool introduced in the National Health Service (NHS) in 2024 has a tendency to over triage paediatric casualties and so hospitals who may be receiving children following a UK major incident must be aware of this and plan for the potential implications. This article reviews the evidence and learning from previous mass casualty events and makes recommendations for hospitals to ensure that the needs of children will be met if a major incident occurs.
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Clinical reasoning is fundamental for effective clinical practice. Traditional consultation models for teaching clinical reasoning or conventional approaches for teaching students how to make a diagnosis or management plan that rely on learning through observation only, are increasingly recognised as insufficient. There are also many challenges to supporting learners in developing clinical reasoning over time as well as across different clinical presentations and contexts. ⋯ Diagnostic errors may be due to cognitive biases but also, in a majority of cases, due to a lack of clinical knowledge. Therefore, effective educational strategies to develop clinical reasoning include identifying learners' knowledge gaps, using worked examples to prevent cognitive overload, promoting the use of key features and practising the construction of accurate problem representations. Deliberate reflection on diagnostic justification is also recommended, and overall, contributes to a growing number of evidence-based and theory-driven educational interventions for reducing diagnostic errors and improving patient care.
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Aims/Background The pathogenesis of irritable bowel syndrome encompasses various factors, including abnormal gastrointestinal motility, heightened visceral sensitivity, dysfunction in the brain-gut axis, psychological influences, and disturbances in the intestinal flora. These factors manifest primarily as persistent or intermittent abdominal pain, diarrhoea, alterations in bowel habits, or changes in stool characteristics. In our investigation, we delve into the repercussions of mechanical barrier damage and immune dysfunction on symptoms among patients with post-infectious irritable bowel syndrome. ⋯ Consequently, this sets the stage for the development of long-lasting, mild chronic intestinal inflammation, ultimately culminating in the onset of post-infectious irritable bowel syndrome. Furthermore, within the framework of the gut-brain axis interaction, anxiety and depression may exacerbate intestinal inflammation in post-infectious irritable bowel syndrome patients. This interaction can perpetuate and prolong clinical symptoms in individuals with post-infectious irritable bowel syndrome, further complicating the management of the condition.
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Artificial intelligence has the potential to transform medical imaging. The effective integration of artificial intelligence into clinical practice requires a robust understanding of its capabilities and limitations. This paper begins with an overview of key clinical use cases such as detection, classification, segmentation and radiomics. ⋯ We provide a broad theoretical framework for assessing the clinical effectiveness of medical imaging artificial intelligence, including appraising internal validity and generalisability of studies, and discuss barriers to clinical translation. Finally, we highlight future directions of travel within the field including multi-modal data integration, federated learning and explainability. By having an awareness of these issues, clinicians can make informed decisions about adopting artificial intelligence for medical imaging, improving patient care and clinical outcomes.
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A 35-year-old otherwise healthy gentleman from Togo, was referred as a 'walk-in' to our clinic with polyuria and polydipsia, and a glycated haemoglobin (Hba1c) of 119 mmol/mol (13.1%). The patient also noted 5kg weight loss over a short span of time. He had a significant family history of Type 2 Diabetes Mellitus (T2DM). ⋯ Urinalysis showed glycosuria (1000 mg/dL) but was negative for nitrites and white cells. Renal, liver and thyroid function tests were all within normal limits. He had mild metabolic acidosis.