Evidence map›Paper›PMID 33804977›Full record

ArticleJournal of clinical medicine2021

Impact of COVID-19 at the Ocular Level: A Citation Network Study.

Miguel Ángel Sánchez-Tena, Clara Martinez-Perez, Cesar Villa-Collar, Cristina Alvarez-Peregrina

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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  5. Article
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.

Miguel Ángel Sánchez-TenaFaculty of Biomedical and Health Sciences, Universidad Europea de Madrid, 28670 Madrid, Spain.ORCID 0000-0002-2583-1789
Clara Martinez-PerezFaculty of Biomedical and Health Sciences, Universidad Europea de Madrid, 28670 Madrid, Spain.ORCID 0000-0002-0996-5007
Cesar Villa-CollarFaculty of Biomedical and Health Sciences, Universidad Europea de Madrid, 28670 Madrid, Spain.ORCID 0000-0002-6743-8264
Cristina Alvarez-PeregrinaFaculty of Biomedical and Health Sciences, Universidad Europea de Madrid, 28670 Madrid, Spain.ORCID 0000-0003-1097-4581

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe main objective of this study was to use citation networks to analyze the relationship between different publications on the impact of COVID-19 at an ocular level and their authors. Furthermore, the different research areas will be identified, and the most cited publication will be determined. MATERIALS AND

methodsThe publications were searched within the Web of Science database, using "ocular", "SARS-CoV-2", "ophthalmology", "eyesight", and "COVID-19" as keywords for the period between January 2020 and January 2021. The Citation Network Explorer and the CiteSpace software were used to analyze the different publications.

resultsA total of 389 publications with 890 citations generated on the web were found. It must be highlighted that July was the month with the largest number of publications. The most cited ones were "Characteristics of Ocular Findings of Patients with Coronavirus Disease 2019 (COVID-19) in Hubei Province, China" by Wu et al., which was published in May 2020. Three groups covering the different research areas in this field were found using the clustering functions: ocular manifestations, teleophthalmology, and personal protective equipment.

conclusionsThe citation network has shown a comprehensive and objective analysis of the main studies on the impact of COVID-19 in ocular disease.

Indexed as

COVID-19COVID-19 conjunctivitisocular diseaseSARS-CoV-2

Identifiers

PMID33804977
PMCPMC8036864

What OpenQuestion holds

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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.