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Blood-based near-infrared spectroscopy for the rapid low-cost detection of Alzheimer's disease

机译:基于血液的近红外光谱,用于快速低成本检测阿尔茨海默病

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摘要

Alzheimer's disease (AD) is currently under-diagnosed and is predicted to affect a great number of people in the future, due to the unrestrained aging of the population. An accurate diagnosis of AD at an early stage, prior to (severe) symptomatology, is of crucial importance as it would allow the subscription of effective palliative care and/or enrolment into specific clinical trials. Today, new analytical methods and research initiatives are being developed for the on-time diagnosis of this devastating disorder. During the last decade, spectroscopic techniques have shown great promise in the robust diagnosis of various pathologies, including neurodegenerative diseases and dementia. In the current study, blood plasma samples were analysed with near-infrared (NIR) spectroscopy as a minimally-invasive method to distinguish patients with AD (n = 111) from non-demented volunteers (n = 173). After applying multivariate classification models (principal component analysis with quadratic discriminant analysis - PCA-QDA), AD individuals were correctly identified with 92.8% accuracy, 87.5% sensitivity and 96.1% specificity. Our results show the potential of NIR spectroscopy as a simple and cost-effective diagnostic tool for AD. Robust and early diagnosis may be a first step towards tackling this disease by allowing timely intervention.
机译:阿尔茨海默氏病(AD)是目前诊断不足和预测影响的人大量在未来,由于人口的老龄化奔放。在早期阶段AD的准确诊断,之前(重度)症状,是至关重要的,因为它能够有效姑息治疗和/或注册订阅成特定的临床试验。如今,新的分析方法和研究项目正在为上一次诊断这种破坏性疾病的发展。在过去十年中,光谱技术已经显示出各种疾病,包括神经退行性疾病和老年痴呆症的诊断稳健的巨大潜力。在目前的研究中,血浆样品用近红外(NIR)光谱法分析作为微创方法来区分患者从非痴呆志愿者(N = 173)AD(N = 111)。施加多元分类模型(与二次判别分析主成分分析 - PCA-QDA)后,AD的个体被正确地鉴定具有92.8%的精确度,87.5%的灵敏度和96.1%的特异性。我们的研究结果表明近红外光谱作为一种简单,经济有效的诊断工具,用于AD的可能性。坚固,早期诊断可能是朝着允许及时介入解决这一疾病的第一步。

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