Simone Castagno

Translation readiness of model-based synthetic tabular data in healthcare: a systematic review and governance audit

Simone Castagno, Alagu Subramanian, Ilias Ektor Epanomeritakis, Benjamin Gompels et autres

OBJECTIVES: To evaluate the clinical applications and translation readiness of model-based synthetic tabular data in healthcare, and identify gaps in governance reporting that may hinder translation. MATERIALS AND METHODS: We systematically searched Ovid MEDLINE and Embase (2010-August 2025; PROSPERO: CRD42025635514) for studies …

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The anterior cruciate ligament (ACL) injury ‘Epidemic’: A perfect storm for Post-Traumatic Osteoarthritis

Benjamin Gompels, Florence Bradshaw, Simone Castagno, Mark Bowditch et autres

Anterior cruciate ligament (ACL) injuries are increasingly common, particularly among women and adolescents participating in high-intensity, multidirectional sports. Despite being a small ligament, the ACL has a disproportionately large impact on an individual's physical and psychological well-being and has gained significant media …

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THE PAEDIATRIC ANTERIOR CRUCIATE LIGAMENT (ACL) NATIONAL AUDIT STUDY (PANA)

Benjamin Gompels, Daniel Hide, Daniel Collins, Florence Bradshaw et autres

Paediatric anterior cruciate ligament (ACL) injuries are increasingly common and pose significant management challenges. Without proper treatment, they can lead to persistent joint instability, cumulative meniscal damage and osteoarthritis. The Paediatric ACL National Audit (PANA) Study assessed UK practices, focusing on adherence …

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Evaluating the Effect of Hypoxia on Adipose-Derived Mesenchymal Stromal Cells In Vivo: A Systematic Review

Benjamin Gompels, Alexandra Macmillan, Simone Castagno, Antonia Vogt et autres

INTRODUCTION: Adipose-Derived Mesenchymal Stromal Cells (ADMSCs) are a developing area of cell therapy due to their ease of access and differentiation potential. Within in vitro studies, culturing cells at low oxygen tension (< 21%) can modulate the immune function of MSCs, enhance …

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Feasibility study of the Cambridge knee injury tool (CamKIT): 18-month analysis of acute knee injuries at an urgent treatment centre

Thomas Molloy, Benjamin Gompels, Simone Castagno, Andrew W. McCaskie et autres

Background: Soft tissue knee injuries are associated with many short- and long-term consequences. Currently, obstacles in the diagnostic pathway lead to inefficiencies in the management process, resulting in suboptimal patient outcomes. Early stratification of knee injury severity is essential for guiding timely …

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MOTION CAPTURE AND ANTERIOR CRUCIATE INJURY RISK: IS THERE A GOLD STANDARD? A SYSTEMATIC REVIEW

Tomos LL Mather, Ava O Machesney, Elizabeth Mainwaring, Ben D Gomples et autres

The anterior cruciate ligament (ACL) plays a critical role in knee stabilisation during dynamic movement but is highly susceptible to injury, particularly in female athletes, who face a 2–10 times greater risk of non-contact ACL injuries than males. Injury prevention programs (IPPs) …

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Lack of Gender-Disaggregated Data for the Psychological Impact of ACL Injury on Adolescents

David Holdroyd, Benjamin Gompels, Ilias Ektor Epanomeritakis, Alexandra Macmillan et autres

Background: This literature review examines the prevalence and severity of depression and anxiety symptoms in adolescents following ACL injury, with a focus on gender-disaggregated data. Methods: An electronic search was conducted across databases, including Ovid MEDLINE (R), PUBMED, and the Cochrane Library, …

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Outcomes of Knee Dislocations and Subluxations in Polytrauma Patients at a Major Trauma Center

Benjamin Gompels, David Holdroyd, Jonathan E. Bennett, Estelle Strangmark et autres

Background This is a retrospective service evaluation of outcomes of polytrauma patients sustaining knee dislocations and subluxations within a major trauma center (MTC). Polytrauma patients with knee dislocations are complex to manage and often sustain multiple life-threatening injuries. Although treatments have progressed, …

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Understanding the role of machine learning in predicting progression of osteoarthritis

Simone Castagno, Benjamin Gompels, Estelle Strangmark, Eve Robertson‐Waters et autres

Aims: Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). …

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Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease

Simone Castagno, Mark Birch, Mihaela van der Schaar, Andrew W. McCaskie

OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we created an automated machine learning (autoML) tool predicting the rapid progression of knee OA over a 2-year period. METHODS: We developed autoML models …

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Seizure outcomes of large volume temporo-parieto-occipital and frontal surgery in children with drug-resistant epilepsy

Simone Castagno, Felice D’Arco, Heather Battey, Christin Eltze et autres

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Raw Data Childhood Epilepsy Surgery

Simone Castagno

Raw Data - Seizure outcomes of temporoparietooccipital and frontal disconnection in children with drug-resistant epilepsy