The British journal of surgery
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Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This study aimed to develop a predictive model for early recurrence after surgery for oesophageal adenocarcinoma using a large multinational cohort and machine learning approaches. ⋯ The model derived using machine learning approaches and an international data set provided excellent performance in quantifying the risk of early recurrence after surgery, and will be useful in prognostication for clinicians and patients.
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Observational Study
Prehospital triage of acute aortic syndrome using a machine learning algorithm.
Acute aortic syndrome (AAS) comprises a complex and potentially fatal group of conditions requiring emergency specialist management. The aim of this study was to build a prediction algorithm to assist prehospital triage of AAS. ⋯ A machine learning prediction model performed well in discriminating AAS and could be clinically useful in prehospital triage of patients with suspected AAS.
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Most clinical guidelines are developed by high-income country institutions with little consideration given to either the evidence base for interventions in low- and middle-income countries (LMICs), or the specific challenges LMIC health systems may face in implementing recommendations. The aim of this study was to prioritize topics for future global surgery guidelines and then to develop a guideline for the top ranked topic. ⋯ This process led to the development of a global surgery guideline for the prevention of SSI that is both clinically relevant and implementable in LMICs.
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This paper describes the development and validation of an electronic personal assessment questionnaire for vascular conditions (ePAQ-VAS) that captures the symptomatology, quality of life and clinically relevant data of patients presenting to vascular services. ⋯ ePAQ-VAS is a holistic data-collection process that is relevant to vascular service users and has potential to contribute to patient-focused care and the collection of aggregate data for service evaluation. A demonstration version of the final version of ePAQ can be viewed at http://demo-questionnaire.epaq.co.uk/home/project?id=VASC_1.7&page=1.
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Research studies to inform clinical practice and policy in children and young people with appendicitis are hampered by inconsistent selection and reporting of outcomes. The aim of this study was to develop a core outcome set for reporting all studies of uncomplicated acute appendicitis in children and young people. ⋯ A core outcome set comprising 14 outcomes across five key domains has been developed for reporting studies in children and young people with uncomplicated acute appendicitis. Further work is required to determine how and when to measure these outcomes.