Evidence map›Paper›PMID 29988470›Full record

ReviewFrontiers in aging neuroscience2018

Potential Utility of Retinal Imaging for Alzheimer's Disease: A Review.

Huan Liao, Zhuoting Zhu, Ying Peng

Abstract readReview
In one paragraph

Review in Frontiers in aging neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 2 pooled it
–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

38 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  20. Imaging the eye and its relevance to diabetes care.Journal of diabetes investigation · 2021
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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

3 authors.

Huan LiaoDepartment of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Zhuoting ZhuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
Ying PengDepartment of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ensuing upward shift in demographic distribution due to the increase in life expectancy has resulted in a rising prevalence of Alzheimer's disease (AD). The heavy public burden of AD, along with the urgent to prevent and treat the disease before the irreversible damage to the brain, calls for a sensitive and specific screening technology to identify high-risk individuals before cognitive symptoms arise. Even though current modalities, such as positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarker, showed their potential clinical uses in early detection of AD, the high cost, narrow isotope availability of PET probes and invasive characteristics of CSF biomarker limited their broad utility. Therefore, additional tools for detection of AD are needed. As a projection of the central nervous system (CNS), the retina has been described as a "window to the brain" and a novel marker for AD. Low cost, easy accessibility and non-invasive features make retina tests suitable for large-scale population screening and investigations of preclinical AD. Furthermore, a number of novel approaches in retina imaging, such as optical coherence tomography (OCT), have been developed and made it possible to visualize changes in the retina at a very fine resolution. In this review, we outline the background for AD to accelerate the adoption of retina imaging for the diagnosis and management of AD in clinical practice. Then, we focus on recent findings on the application of retina imaging to investigate AD and provide suggestions for future research directions.

Indexed as

Alzheimer’s diseaseearly detectionnovel biomarkerretinal imagingreview

Identifiers

PMID29988470
PMCPMC6024140

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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.