Brit J Hosp Med
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Review Case Reports
The impact of an anomalous third segment of the vertebral artery on bypass surgery: a case report and literature review.
The horizontal part of the third segment (V3) of the vertebral artery (VA) is a critical anastomotic site for bypass procedures involving either donor or recipient vessels. It is rare for the V3 segment to deviate from its typical course of passing through the atlanto-transverse foramen. V3 anomaly encountered in occipital artery (OA)-V3 bypass surgery has not been previously reported. ⋯ During the operation, it was noted that the V3 horizontal segment could not be identified within the left VA groove, leading to initial suspicion of left V3 disuse atrophy attributed to prolonged chronic ischaemia. Consequently, there was a need to modify the operative method and to transition from an OA-V3 bypass to an OA-posterior inferior cerebellar artery bypass. Post-operative computed tomography angiography confirmed that indeed, the left V3 did not traverse through the transverse foramen of the atlas and instead entered the dural membrane between the first cervical vertebra (C1) and the second cervical vertebra (C2).
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A 46-year-old man presented with a small bowel prolapsing through the anus after straining on the toilet, which was starting to become ischaemic. He admitted to inserting a plastic object in his rectum about half an hour before straining. The bowel was kept moist by placing an intravenous drip line with saline dripping onto a wet swab. ⋯ At the re-look the small bowel appeared healthy, therefore no resection was performed. However, a loop colostomy was fashioned to protect the upper rectal perforation repair. This shows that resection is not always required in such cases.
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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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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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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.