Evidence map›Paper›PMID 36528836›Full record

ArticleNeurology and therapy2023

The Early Diagnosis of Alzheimer's Disease: A Patient-Centred Conversation with the Care Team.

Ziad Nasreddine, Valentina Garibotto, Simon Kyaga, Alessandro Padovani

Abstract read
In one paragraph

Article in Neurology and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ziad NasreddineMoCA Clinic and Institute, Longueuil, QC, Canada.
Valentina GaribottoUniversity Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
Simon KyagaBiogen International GmbH, Neuhofstrasse 30, 6340, Baar, Switzerland. simon.kyaga@biogen.com.
Alessandro PadovaniUniversity of Brescia, Brescia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder which accounts for 60-80% of dementia cases, affecting approximately 10 million people in Europe. Neuroimaging techniques and cerebrospinal fluid biomarkers used in combination with cognitive assessment tools open the door to early diagnosis of AD. However, these tools present some challenges that need to be overcome, such as low sensitivity or specificity, high cost, limited availability or invasiveness. Thus, low-cost and non-invasive alternatives, such as plasma biomarkers, have the potential to drive changes in AD screening and diagnosis. In addition to the technical aspects, organisational challenges as well as ethical concerns need to be addressed. In many countries, there is an insufficient number of specialists to recognise, evaluate and diagnose dementia and the waiting times to see a specialist are long. Given that there is currently no cure for AD, it is important to consider the potential psychological impact of an early diagnosis. In addition, counselling before biomarker sampling and during diagnosis disclosure is vital to guarantee that the patients have all the information necessary and their queries are addressed in a sensitive manner. Here, we illustrate (using a clinical vignette) current challenges of diagnosis and discuss some of the benefits and challenges of early diagnosis in AD including the value of biomarkers in combination with clinical evaluation. Lastly, some guidelines for disclosing early diagnosis of AD are provided based on our experiences.

Indexed as

Alzheimer’s diseaseBiomarkersCerebrospinal fluidEarly diagnosisNeuroimagingPatient managementPsychological impact of biomarker testing

Identifiers

PMID36528836
PMCPMC9837364

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.