Bălăeţ Maria, Alhajraf Falah, Zerenner Tanja, Welch Jessica, Razzaque Jamil, Lo Christine, Giunchiglia Valentina, Trender William, Lerede Annalaura, Hellyer Peter J, Manohar Sanjay G, Malhotra Paresh, Hu Michele, Hampshire Adam
Department of Brain Sciences, Imperial College London, London, UK.
Oxford Parkinson's Disease Centre, Nuffield Department Clinical Neurosciences, University of Oxford, Oxford, UK.
NPJ Digit Med. 2024 May 7;7(1):118. doi: 10.1038/s41746-024-01124-6.
Automated online cognitive assessments are set to revolutionise clinical research and healthcare. However, their applicability for Parkinson's Disease (PD) and REM Sleep Behavioural Disorder (RBD), a strong PD precursor, is underexplored. Here, we developed an online battery to measure early cognitive changes in PD and RBD. Evaluating 19 candidate tasks showed significant global accuracy deficits in PD (0.65 SD, p = 0.003) and RBD (0.45 SD, p = 0.027), driven by memory, language, attention and executive underperformance, and global reaction time deficits in PD (0.61 SD, p = 0.001). We identified a brief 20-min battery that had sensitivity to deficits across these cognitive domains while being robust to the device used. This battery was more sensitive to early-stage and prodromal deficits than the supervised neuropsychological scales. It also diverged from those scales, capturing additional cognitive factors sensitive to PD and RBD. This technology offers an economical and scalable method for assessing these populations that can complement standard supervised practices.
自动化在线认知评估将彻底改变临床研究和医疗保健。然而,其在帕金森病(PD)和快速眼动睡眠行为障碍(RBD,一种强烈的PD前驱症状)中的适用性尚未得到充分探索。在此,我们开发了一套在线测试组合,以测量PD和RBD的早期认知变化。对19项候选任务的评估显示,PD患者存在显著的整体准确性缺陷(0.65标准差,p = 0.003),RBD患者也存在显著缺陷(0.45标准差,p = 0.027),这是由记忆、语言、注意力和执行功能表现不佳所致,且PD患者存在整体反应时间缺陷(0.61标准差,p = 0.001)。我们确定了一个简短的20分钟测试组合,它对这些认知领域的缺陷具有敏感性,同时对所使用的设备具有鲁棒性。该测试组合对早期和前驱期缺陷比有监督的神经心理量表更敏感。它也与那些量表不同,捕捉到了对PD和RBD敏感的其他认知因素。这项技术为评估这些人群提供了一种经济且可扩展的方法,可以补充标准的有监督的做法。