Affiliations: [a] Department of Medicine, Section of Gerontologyand Geriatrics, University of Perugia, Perugia, Italy
| [b] Department of Medicine, Section of Neurology, Center for Memory Disturbances-Lab of Clinical Neurochemistry, University of Perugia, Perugia, Italy
| [c] Neurology Unit, Presidio Ospedaliero Alto Chiascio, USL 1 Umbria, Italy
Correspondence:
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Correspondence to: Prof. Patrizia Mecocci, MD, PhD, Section of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Piazzale Gambuli, 1, 06132 Perugia, Italy. Tel.: +39 075 5783270; Fax: +39 075 5783878; E-mail: [email protected].
Note: [1] These authors contributed equally to this work.
Abstract: In recent years, many efforts have been spent to identify sensitive biomarkers able to improve the accuracy of Alzheimer’s disease (AD) diagnosis. Two different workgroups (NIA-AA and IWG) included cerebrospinal fluid (CSF) and neuroimaging findings in their sets of criteria in order to improve diagnostic accuracy as well as early diagnosis. The number of subjects with cognitive impairment increases with aging but the oldest old (≥85 years of age), the fastest growing age group, is still the most unknown from a biological point of view. For this reason, the aim of our narrative mini-review is to evaluate the pertinence of the new criteria for AD diagnosis in the oldest old. Moreover, since different subgroups of oldest old have been described in scientific literature (escapers, delayers, survivors), we want to outline the clinical profile of the oldest old who could really benefit from the use of biomarkers for early diagnosis. Reviewing the literature on biomarkers included in the diagnostic criteria, we did not find a high degree of evidence for their use in the oldest old, although CSF biomarkers seem to be still the most useful for excluding AD diagnosis in the “fit” subgroup of oldest old subjects, due to the high negative predictive value maintained in this age group.
Keywords: Aging, Alzheimer’s disease, biomarker, cerebrospinal fluid, MRI, oldest-old, PET
