East Grinstead

The primary study objective is to compare the effectiveness of the combination of phacoemulsification with intraocular lens implant with ELIOS or competitor device in reducing IOP at 12 months postoperatively.

Hospital acquired thrombosis describes blood clots that form in the legs and lungs after someone is treated in hospital. Clots in the leg can cause swelling, pain and other problems. If a clot in the leg travels to the lungs, it may be life threatening. Having surgery increases the risk of developing blood clots. People having short-stay surgery (who either go home the same day or who stay overnight but go home shortly afterwards) are at a much lower risk of developing a blood clot than those who stay in hospital for longer. These low-risk people are often given elastic stockings (which squeeze the leg muscles) to reduce the chance of a blood clot. The risks of wearing the stockings are low but they can be uncomfortable. In the UK, there are over a million short stay surgeries performed each year and most of these people are given elastic stockings to wear. Stockings cost the NHS a lot of money and it remains unknown if they work. This study will investigate if it is worthwhile to continue using elastic stockings in people having surgery where the risk of developing blood clots is low. Adults (over 18-years) who are at low risk of developing blood clots (assessed using a nationally recognised tool) will be included.

This study will determine whether there is a difference in disease-free survival rates for patients with primary cutaneous melanoma with Breslow thickness \> 2mm or 1-2mm with ulceration (pT2b-pT4b, AJCC 8th edition), treated with either a 1cm excision margin or 2cm margin. The study is designed to be able to prove or disprove that there is no difference in risk of the tumour recurring around the scar or anywhere else in the body between the two groups of patients. If the study shows no risk of tumour recurrence then we will also be able to determine how much of an impact the narrower excision has on patients in terms of improved quality of life and reduced side effects from the surgery and melanoma disease. This trial will also evaluate and determine the economic impact of narrower excision margins on the health services and society in general.

An automated strategy for identifying abnormalities in head scans could address the unmet clinical need for faster abnormality identification times, potentially allowing for early intervention to improve short- and long-term clinical outcomes. Radiologist shortages and increased demand for MRI scans lead to delays in reporting, particularly in the outpatient setting. Furthermore, there is a wide variation in the management of incidental findings (IFs) discovered in 'healthy volunteers.' The routine reporting of 'healthy volunteer' scans by a radiologist poses logistical and financial challenges. It would be valuable to devise automated strategies to reliably and accurately identify IFs, potentially reducing the number of scans requiring routine radiological review by up to 90%, thus increasing the feasibility of implementing a routine reporting strategy. Deep learning is a novel technique in computer science that automatically learns hierarchies of relevant features directly from the raw inputs (such as MRI or CT) using multi-layered neural networks. A deep learning algorithm will be trained on a large database of head MRI scans to recognize scans with abnormalities. This algorithm will be trained to classify a subset of these scans as normal or abnormal and then tested on an independent subset to determine its validity. If the tested neural network demonstrates high diagnostic accuracy, future research participants and patients may benefit, as not all institutions currently review their research scans for incidental findings and clinical scans may not be reported for weeks in some cases. In both research and clinical scenarios, an algorithm could rapidly identify abnormal pathology and prioritize scans for reporting. In summary, the aim is to develop a deep learning abnormality detection algorithm for use in both research and clinical settings.

Open Angle Glaucoma (OAG) is a chronic optic neuropathy causing progressive vision loss. It is well established that IOP is the only currently modifiable risk factor for glaucoma progression, and it is widely accepted that other risk factors modulate the susceptibility of an eye to IOP. This has led to a considerable body of research into neurodegenerative mechanisms and potential neuroprotective approaches. Various pathways contributing to the neurodegeneration have been implicated, and many have focussed on the role of mitochondria. Neuroprotection would significantly reduce sight loss and the burden of IOP-lowering eye drop treatment needed for disease control. There is evidence that susceptibility to IOP is related to mitochondrial function and ageing is associated with mitochondrial functional decline. The knowledge gap addressed in this trial is the relative contribution that mitochondrial function makes to glaucomatous neurodegeneration and whether boosting mitochondrial function with NAM slows progression in humans in the same way that it does in animal models. Biomarkers for mitochondrial-related susceptibility have not yet been established in humans. The proposal therefore is a new mechanism neuroprotection to improve resistance to eye pressure and evaluate the long-term safety and efficacy of NAM to preserve vision and its mechanism of action. There is strong evidence that mitochondrial dysfunction is associated with OAG susceptibility and that NAM improves mitochondrial function. Research has shown short-term vision improvement with high-dose NAM in glaucoma patients. NAM is safe and well-tolerated.