Evidence map›Paper›PMID 35447469›Full record

ArticleNeuroImage. Clinical2022

A multi-regression approach to improve optical coherence tomography diagnostic accuracy in multiple sclerosis patients without previous optic neuritis.

Jacqueline Chua, Mihai Bostan, Chi Li, Yin Ci Sim, Inna Bujor, Damon Wong, Bingyao Tan, Xinwen Yao, Florian Schwarzhans, Gerhard Garhöfer and 6 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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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

16 authors at 6 institutions in 4 countries.

Jacqueline ChuaSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, National University of Singapore, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
Mihai BostanCarol Davila University of Medicine and Pharmacy, Bucharest, Romania; Ophthalmology Emergency Hospital, Bucharest, Romania.
Chi LiSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
Yin Ci SimSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
Inna BujorCarol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Damon WongSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore.
Bingyao TanSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore.
Xinwen YaoSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore.
Florian SchwarzhansCenter for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management, Medical University Vienna, Vienna, Austria; Department of Clinical Pharmacology, Medical University Vienna, Vienna, Austria.
Gerhard GarhöferDepartment of Clinical Pharmacology, Medical University Vienna, Vienna, Austria.
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.
Cristina TiuCarol Davila University of Medicine and Pharmacy, Bucharest, Romania; Emergency University Hospital, Department of Neurology, Bucharest, Romania.
Ruxandra PirvulescuCarol Davila University of Medicine and Pharmacy, Bucharest, Romania; Emergency University Hospital, Department of Ophthalmology, Bucharest, Romania.
Alina Popa-CherecheanuCarol Davila University of Medicine and Pharmacy, Bucharest, Romania; Emergency University Hospital, Department of Ophthalmology, Bucharest, Romania. Electronic address: alina_cherecheanu@yahoo.com.
Leopold SchmettererSingapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, National University of Singapore, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore; Department of Clinical Pharmacology, Medical University Vienna, Vienna, Austria; Center for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, Austria; Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland. Electronic address: leopold.schmetterer@meduniwien.ac.at.
Singapore National Eye Center · SGCarol Davila University of Medicine and Pharmacy · ROSingapore Eye Research Institute · SGClinical Emergency Hospital Bucharest · ROMedical University of Vienna · ATStatistics Austria · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptical coherence tomography (OCT) is a retinal imaging system that may improve the diagnosis of multiple sclerosis (MS) persons, but the evidence is currently equivocal. To assess whether compensating the peripapillary retinal nerve fiber layer (pRNFL) thickness for ocular anatomical features as well as the combination with macular layers can improve the capability of OCT in differentiating non-optic neuritis eyes of relapsing-remitting MS patients from healthy controls.

methods74 MS participants (n = 129 eyes) and 84 age- and sex-matched healthy controls (n = 149 eyes) were enrolled. Macular ganglion cell complex (mGCC) thickness was extracted and pRNFL measurement was compensated for ocular anatomical factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between groups.

resultsParticipants with MS showed significantly thinner mGCC, measured and compensated pRNFL (p ≤ 0.026). Compensated pRNFL achieved better performance than measured pRNFL for MS differentiation (AUC, 0.75 vs 0.80; p = 0.020). Combining macular and compensated pRNFL parameters provided the best discrimination of MS (AUC = 0.85 vs 0.75; p < 0.001), translating to an average improvement in sensitivity of 24 percent for differentiation of MS individuals.

conclusionThe capability of OCT in MS differentiation is made more robust by accounting OCT scans for individual anatomical differences and incorporating information from both optic disc and macular regions, representing markers of axonal damage and neuronal injury, respectively.

Indexed as

Multiple SclerosisOptic NeuritisHumansNerve FibersRetinal Ganglion CellsTomography, Optical CoherenceMacular ganglion cell and inner plexiform layerMacular ganglion cell complexOptical coherence tomographyPeripapillary retinal nerve fiber layerRelapsing-remitting multiple sclerosis

Identifiers

PMID35447469
PMCPMC9043868
OpenAlexW4223952515

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.