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  • Journal article
    patel NP, seneci CS, yang GZY, darzi AD, teare JTet al.,

    Flexible platforms for natural orifice transluminal and endoluminal surgery. Endoscopy International Open, 2(02), E117-E123.

    , Endoscopy International Open
  • Journal article
    Vrielink TJCO, Pang YW, Zhao M, Lee S-L, Darzi A, Mylonas GPet al.,

    Surgical task-space optimisation of the CYCLOPS robotic system

    The CYCLOPS is a cable-driven parallel mechanism used for minimally invasiveapplications, with the ability to be customised to different surgical needs;allowing it to be made procedure- and patient-specific. For adequateoptimisation, however, appropriate data on clinical constraints and task-spaceis required. Whereas the former can be provided through preoperative planningand imaging, the latter remains a problem, primarily for highly dexterous MISsystems. The current work focuses on the development of a task-spaceoptimisation method for the CYCLOPS system and the development of a datacollection method in a simulation environment for minimally invasivetask-spaces. The same data collection method can be used for the development ofother minimally invasive platforms. A case-study is used to illustrate thedeveloped method for Endoscopic Submucosal Dissection (ESD). This paper showsthat using this method, the system can be succesfully optimised for thisapplication.

  • Journal article
    Nurek M, Rayner C, Freyer A, Taylor S, Järte L, MacDermott N, Delaney BCet al.,

    Recommendations for the Recognition, Diagnosis, and Management of Patients with Post COVID-19 Condition ('Long COVID'): A Delphi Study

    , SSRN Electronic Journal
  • Journal article
    Espinosa-Gonzalez AB, Neves AL, Fiorentino F, Prociuk D, Husain L, Ramtale SC, Mi E, Mi E, Macartney J, Anand SN, Sherlock J, Saravanakumar K, Mayer E, de Lusignan S, Greenhalgh T, Delaney BCet al.,

    Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool (Preprint)

    <sec> <title>BACKGROUND</title> <p>During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes.</p> </sec> <sec> <title>METHODS</title> <p>The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use o

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