GEMINI-OS : platform informatics for data-driven neuromodulation
GEMINI-OS : platform informatics for data-driven neuromodulation
批准号:
10036282
负责人:
金额:
$232.23万
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
脑深部刺激(DBS)是治疗晚期帕金森病(PD)和震颤的一种公认的治疗方法,可以显著提高他们的生活质量。帕金森病是一种进行性疾病,有对症治疗,但没有治愈方法。在晚期,药物可能无法控制症状,通常会引起运动和非运动相关的副作用。在这个阶段,帕金森病患者可以被转介到DBS中心,在那里,包括一名神经科医生和一名脑外科医生在内的专家团队在可能提供手术之前进行广泛的评估。虽然DBS可以改变生活,但多达四分之一的患者无法从DBS中受益,一些人甚至在手术后病情恶化。相反,一些将从中受益的患者没有得到治疗。这种失败或无法获得治疗的主要原因是这种强大疗法的选择过程不正确。虽然设备的技术进步在过去20年里极大地改善了DBS治疗的提供,但选择最佳候选者的能力一直保持稳定。选择过程基于30多年前建立的标准,主要由单个中心的结果、经验和知识提供信息。因此,进行DBS手术的决定是基于对所有数据的手动临床评估,这些数据依赖于不同中心每个团队的技能和经验,从而导致高度的可变性。该项目将开发一种新的临床工具,将促进和改进DBS患者的选择。我们将开发一个新的平台,将手术前和手术后的数据结合起来,以确定哪些因素可以预测手术结果的好坏。为患者选择提供一个数据驱动的客观工具,将通过以下方式改进这一过程:1)减少手术后病情恶化的人数;2)增加提供治疗的人数,包括早期阶段的患者;3)让临床医生对选择过程有更大的信心。这一平台还将使各小组能够借鉴使用该平台的所有中心的经验,而不仅仅是他们自己的经验。目前,由于资格标准狭窄,英国只有500人符合临床资格,尽管更多的患者被认为可能受益。这一平台将给予更大的信心,以扩大准入,让更多的患者受益。
英文摘要
Deep Brain Stimulation (DBS) is an established treatment for advanced Parkinson's disease (PD) and tremor which may significantly improve their quality of life. PD is a progressive disease for which there are symptomatic treatments but no cure. In the advanced stages, medications can fail to control symptoms and commonly cause movement and non-movement related side effects. At this stage, people with PD can be referred to a DBS centre where a team of experts, including a neurologist and a brain surgeon, conduct extensive assessments before potentially offering surgery.While DBS can be a life-changing treatment, up to 1 in 4 patients fail to benefit from DBS and some even worsen following surgery. Conversely, some patients who would benefit from it are not offered treatment. The main reason for such failure or inaccessibility to treatment is due to the incorrect selection process for this powerful therapy. Whilst technological improvements in the devices have massively improved the delivery of DBS treatment over the last 20 years, the ability to select the best candidates has remained static.The selection process is based on criteria established more than 30 years ago and is largely informed by the outcomes, experience and knowledge by an individual centre. Thus, the decision to undertake DBS surgery is based on manual clinical evaluation of all the data which relies on the skills and experience of each individual team at the different centres, leading to high levels of variability.This project will develop a new clinical tool which will facilitate and improve patient selection for DBS. We will develop a novel platform that combines data from before and after surgery to determine what factors predict a good or poor outcome from surgery. Providing a data-driven, objective tool for patient selection, will improve the process by: 1) reducing the number of people who will deteriorate following surgery; 2) increasing the number of people who are offered treatment, including those in the earlier stages; 3) giving clinicians greater confidence in the selection process. This platform will also allow the teams to draw on the experience from all of the centres using the platform, rather than just their own. Currently, only 500 people in the UK meet the clinical eligibility due to the narrow eligibility criteria although many more patients are thought to potentially benefit. This platform would give greater confidence to widen access and allow more patients to benefit.
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