Evidence map›Paper›PMID 35272711›Full record

ArticleAlzheimer's research & therapy2022

A multi-regression framework to improve diagnostic ability of optical coherence tomography retinal biomarkers to discriminate mild cognitive impairment and Alzheimer's disease.

Jacqueline Chua, Chi Li, Lucius Kang Hua Ho, Damon Wong, Bingyao Tan, Xinwen Yao, Alfred Gan, Florian Schwarzhans, Gerhard Garhöfer, Chelvin C A Sng and 8 more

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's research & therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 11% of its field
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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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  11. Alzheimer's disease pathophysiology in the Retina.Progress in retinal and eye research · 2024
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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

18 authors at 6 institutions in 4 countries.

Jacqueline ChuaSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Chi LiSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Lucius Kang Hua HoSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Damon WongSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Bingyao TanSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Xinwen YaoSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Alfred GanSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Florian SchwarzhansCenter for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management, Medical University Vienna, Vienna, Austria.
Gerhard GarhöferDepartment of Clinical Pharmacology, Medical University Vienna, Vienna, Austria.
Chelvin C A SngSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Saima HilalMemory Aging and Cognition Centre, Departments of Pharmacology and Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Narayanaswamy VenketasubramanianMemory Aging and Cognition Centre, Departments of Pharmacology and Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Carol Y CheungDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Sha Tin, Hong Kong.
Georg FischerCenter for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management, Medical University Vienna, Vienna, Austria.
Clemens VassDepartment of Ophthalmology and Optometry, Medical University Vienna, Vienna, Austria.
Tien Yin WongSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
Christopher Li-Hsian ChenMemory Aging and Cognition Centre, Departments of Pharmacology and Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Leopold SchmettererSingapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore. leopold.schmetterer@seri.com.sg.ORCID 0000-0002-7189-1707
National University of Singapore · SGSingapore Eye Research Institute · SGNanyang Technological University · SGMedical University of Vienna · ATStatistics Austria · ATChinese University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiagnostic performance of optical coherence tomography (OCT) to detect Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains limited. We assessed whether compensating the circumpapillary retinal nerve fiber layer (cpRNFL) thickness for multiple demographic and anatomical factors as well as the combination of macular layers improves the detection of MCI and AD.

methodsThis cross-sectional study of 62 AD (n = 92 eyes), 108 MCI (n = 158 eyes), and 55 cognitively normal control (n = 86 eyes) participants. Macular ganglion cell complex (mGCC) thickness was extracted. Circumpapillary retinal nerve fiber layer (cpRNFL) measurement was compensated for several ocular factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between the groups. The main outcome measure was OCT thickness measurements.

resultsParticipants with MCI/AD showed significantly thinner measured and compensated cpRNFL, mGCC, and altered retinal vessel density (p < 0.05). Compensated RNFL outperformed measured RNFL for discrimination of MCI/AD (AUC = 0.74 vs 0.69; p = 0.026). Combining macular and compensated cpRNFL parameters provided the best detection of MCI/AD (AUC = 0.80 vs 0.69; p < 0.001). CONCLUSIONS AND RELEVANCE: Accounting for interindividual variations of ocular anatomical features in cpRNFL measurements and incorporating macular information may improve the identification of high-risk individuals with early cognitive impairment.

Indexed as

Alzheimer DiseaseCognitive DysfunctionBiomarkersCross-Sectional StudiesHumansNerve FibersRetinal Ganglion CellsTomography, Optical CoherenceBiomarkersAlzheimer’s diseasemild cognitive impairmentOptical coherence tomography

Identifiers

PMID35272711
PMCPMC8908577
OpenAlexW4220770776

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.