Evidence map›Paper›PMID 38090277›Full record

ReviewBrain communications2023

Online clinical tools to support the use of new plasma biomarker diagnostic technology in the assessment of Alzheimer's disease: a narrative review.

Jemma Hazan, Kathy Y Liu, Nick C Fox, Robert Howard

Abstract readReview
In one paragraph

Review in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Body Composition and Alzheimer's Disease: A Holistic Review.International journal of molecular sciences · 2024
    Review
  6. Review
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.

Jemma HazanDivision of Psychiatry, University College London, London W1T 7BN, UK.ORCID https://orcid.org/0000-0002-7223-4768
Kathy Y LiuDivision of Psychiatry, University College London, London W1T 7BN, UK.ORCID https://orcid.org/0000-0002-7482-2758
Nick C FoxDementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK.
Robert HowardDivision of Psychiatry, University College London, London W1T 7BN, UK.

Funding

Medical Research Council MR/S021418/1
6 · The paper itself

Abstract

Recent advances in new diagnostic technologies for Alzheimer's disease have improved the speed and precision of diagnosis. However, accessing the potential benefits of this technology poses challenges for clinicians, such as deciding whether it is clinically appropriate to order a diagnostic test, which specific test or tests to order and how to interpret test results and communicate these to the patient and their caregiver. Tools to support decision-making could provide additional structure and information to the clinical assessment process. These tools could be accessed online, and such 'e-tools' can provide an interactive interface to support patients and clinicians in the use of new diagnostic technologies for Alzheimer's disease. We performed a narrative review of the literature to synthesize information available on this research topic. Relevant studies that provide an understanding of how these online tools could be used to optimize the clinical utility of diagnostic technology were identified. Based on these, we discuss the ways in which e-tools have been used to assist in the diagnosis of Alzheimer's disease and propose recommendations for future research to aid further development.

Indexed as

Alzheimer’s diseasebiomarkerdementiadiagnosisinvestigation

Identifiers

PMID38090277
PMCPMC10715781

What OpenQuestion holds

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Registered trials

None linked

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.