Department of Clinical and Experimental Medicine, Neurology Unit, University of Pisa, Pisa, Italy.
Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
Neurol Sci. 2024 Oct;45(10):4657-4668. doi: 10.1007/s10072-024-07631-4. Epub 2024 Jun 10.
Rare neurological diseases as a whole share peculiar features as motor and/or cognitive impairment, an elevated disability burden, a frequently chronic course and, in present times, scarcity of therapeutic options. The rarity of those conditions hampers both the identification of significant prognostic outcome measures, and the development of novel therapeutic approaches and clinical trials. Collection of objective clinical data through digital devices can support diagnosis, care, and therapeutic research. We provide an overview on recent developments in the field of digital tools applied to rare neurological diseases, both in the care setting and as providers of outcome measures in clinical trials in a representative subgroup of conditions, including ataxias, hereditary spastic paraplegias, motoneuron diseases and myopathies.
罕见神经疾病整体具有一些共同特征,包括运动和/或认知障碍、较高的残疾负担、常呈慢性病程,且目前治疗选择有限。这些疾病的罕见性既妨碍了重要预后指标的识别,也妨碍了新治疗方法和临床试验的发展。通过数字设备收集客观临床数据可以支持诊断、护理和治疗研究。我们概述了应用于罕见神经疾病领域的数字工具的最新进展,包括在护理环境中的应用,以及作为临床试验中代表性亚组疾病(包括共济失调、遗传性痉挛性截瘫、运动神经元疾病和肌病)的预后指标的应用。
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