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Expedited Publication, Original Article

COVID-19 and ophthalmology

A scientometric analysis

Kalra, Gagan; Kaur, Rishemjit1; Ichhpujani, Parul; Chahal, Rutvi; Kumar, Suresh

Author Information
Indian Journal of Ophthalmology: May 2021 - Volume 69 - Issue 5 - p 1234-1240
doi: 10.4103/ijo.IJO_3284_20
  • Open

Abstract

Coronavirus disease 2019 (COVID-19) outbreak that started in December 2019, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has become a global emergency.[12] Ever since, the pandemic has taken its toll with an increasing number of cases and deaths.

Till date, the World Health Organization (WHO) and the US Center for Disease Control and Prevention (CDC) have provided guidelines only for the management of patients with COVID-19 in terms of infection control and symptomatic relief. No specific vaccines or antiviral drugs are currently available for the SARS-CoV-2. Therefore, it is important to keep an eye on world literature for possible ideas and breakthroughs. The first scientometric analysis for COVID-19 research was published in March 2020.[3] The author explored the PubMed database and the WHO database for publications pertaining to COVID-19 from December 2019 up until March 18, 2020. Felici and Poleminin carried out another bibliometric analysis of the publications on COVID-19 up until April 20, 2020.[4]

Ophthalmologists are at high risk of exposure to the disease due to close contact with patients during the slit-lamp examination and manifestation of disease as ocular conjunctivitis.[56] In addition, the major patient volume seeking ophthalmic care comprises the elderly population, which has been reported to be a high-risk population.[7] With a growing interest in COVID-19 research all over the world, a scientometric study of specifically the ophthalmology-related COVID-19 research is needed. This quantitative analysis of the data will provide meaningful insight for future research in the context of ophthalmology. There is no bibliometric analysis available to date that specifically focuses on developments in COVID-19 research in the ophthalmology field.

Methods

The current descriptive, scientometric study targeted a schematic view of a scientific map in the field of glaucoma. We used a web of science (https://webofknowledge.com), as our database for our analysis on February 23, 2021, using institutional access. The search query was TS = (“novel coronavirus 2019” OR “coronavirus 2019” OR “COVID 2019” OR “COVID 19” OR “nCOV” OR “SARS-CoV-2” OR “COVID-19”) AND WC = (“Ophthalmology”), where TS represents the topic and WC represents the web of science category. Since the study is based on public access bibliometric data, and did not involve any human subjects or any patient data, ethics committee deemed that a committee review was not required for this study.

The query was done using all the variations of this term for the duration up to February 22, 2021. The data were exported in WoS raw data (.txt) file format that was used as a data source in the Bibliometrix R library (Aria M & Cuccurullo C) and Biblioshiny app. All analyses were performed in the R environment (v4.0.1, John Chambers and colleagues, Bell Laboratories). Articles about COVID-19 in ophthalmology were analyzed using different metrics as described below.

General information

These metrics included the overall composition of our dataset pertaining to the total number of research items, total number of authors, total number of references cited, research item type, and the total number of sources.

Geographical distribution

Country-wise scientific production and total country citations were used to quantify contributions made by a certain geographic area to this body of research and ascertain the impact of these contributions. Metrics such as Single-Country Production (SCP) and Multi-Country Production (MCP) were used to ascertain the extent of intercountry collaboration.

Source metrics

Total scientific production by the source was deployed as a metric to identify the distribution of research items across various contributing sources.

Hirsch index (h-index) and a total number of citations (TC; total times cited count) are two important author-level parameters. h-index is a metric that attempts to measure both the productivity and citation impact of the publications of a scientist. While initially proposed for authors, the h-index has been successfully applied for papers and journals.[8] In addition to the metrics obtained from our local dataset, we also collected h-indices for the top-ranking journals from Scimago JR (https://www.scimagojr.com/) to compare the overall impact of a source to the impact contributed to COVID-19 in ophthalmology.

Bradford’s law

Bradford’s law of scattering helps to identify the core journals relevant to the research field. It is based on the principle of centric productivity zones, where the journals are divided into different zones having the same number of articles.

Document metrics

Local citation score and global citation score are metrics that represent the number of times a research item is cited either locally or globally, respectively. These metrics were used to identify the most commonly cited local and global research items.

Author profile

As previously highlighted, the Hirsch index (h-index) and a total number of citations (TC; total times cited count) are author-level parameters that have proven insightful for measuring the impact of a scientist. We used these metrics to compare author impact in this study. Corresponding author affiliations and their contributions were identified and compiled to analyze affiliation-wise contributions. Collaboration index (CI) is another metric used to quantify collaboration between authors and can be calculated as total authors of multi-authored articles/total multiauthored articles.

Cocitation network

A cocitation measures the frequency that two research items are cited together by a research item in that field of research. Cocitation network is visualized by drawing an arc between two articles that are cocited by a research item. “Betweenness” is a measure of how often a node is located on the shortest path between other nodes in the network. “Closeness” is less dependent on relations between individual nodes because a node can be close to two (or more) densely connected clusters.

Keyword metrics

KeyWords Plus® is unique to Web of Science and consists of words and phrases harvested from the titles of the cited articles and are also searched in the topic search. Author keywords are those keywords that are provided by authors at the time of submission of the research item for publication. Frequency metrics were used to identify commonly occurring keywords, topics, and themes.

Co-occurrence network

The nodes represent the keywords and their size reflects the occurrence frequency. The edges represent the connections between the nodes and their thickness reflects the co-occurrence frequency of nodes. The stronger connection or higher co-occurrence frequency is reflected by a thicker edge. The color of nodes represents their community/theme, where the nodes present in the same theme are more similar to each other than the nodes present in the other themes.

Thematic map

In a thematic map, each community/theme is represented on a two-dimensional plot of centrality vs density. Centrality can be interpreted as the importance of a theme in the research field and density can be treated as a measure of the development of the theme. Based on the centrality and density values, themes can be divided into four types:

  • Motor themes: Themes in the upper-right quadrant with the higher values of centrality and density, which are both developed and form an important pillar in shaping the research field.
  • Basic and transversal themes: Themes in the lower-right quadrant with higher values of centrality and lower values of density, which are weakly developed but important for a research field.
  • Niche themes: Themes in the upper-left quadrant with higher values of density but lower values of centrality reflect the highly developed but isolated themes.
  • Emerging or declining themes: Themes in the lower-left quadrant, both weakly developed and marginal in the research field.

Country-keyword-source three-field plot

This plot helps visualize the distribution of topic/keywords in this body of research across countries and sources. Such visualization helps better understanding the kind of research that is being conducted in different geographical spaces and which leading sources are featuring this research.

Results

A total of 616 research items appeared in our search results. These items were drafted by 2398 authors and published in 63 journals. There were a total of 6172 references in this result and the average citations per document is 4.019. The search results were comprised of original articles (n = 237, 38.5%), letter (n = 182, 29.5%), editorial material (n = 138, 22.4%), review articles (n = 54, 8.8%), and correction (n = 5, 0.8%).

Geographic distribution

The most relevant countries by the number of publications were India (n = 138, Single Country Publication (SCP) = 122), United States of America (n = 95, SCP = 84), United Kingdom (n = 63, SCP = 53), China (n = 60, SCP = 47), and Italy (n = 39, SCP = 32) among others. Most relevant country by the number of citations were China (n = 940), Singapore (n = 455), India (n = 266), United States of America (n = 204), and Italy (n = 130) among others. Global collaboration network over the period analyzed in the study is represented in the Fig. 1. Table 1 enlists country wise production of articles, both single country and multiple country productions. Supplementary Table 1 enlists countries by number of citations.

Figure 1
Figure 1:
Global collaboration network
Table 1
Table 1:
Country-wise production of articles: Single-country and Multi-country productions
Supplementary Table 1
Supplementary Table 1:
Country by number of citations

Source metrics

The most relevant journals in terms of scientific production were Indian Journal of Ophthalmology (IJO) (n = 127), Eye (n = 54), Graefe’s Archive for Clinical and Experimental Ophthalmology (n = 43), Ocular Immunology and Inflammation (n = 26), and Ophthalmology (n = 26) among others.

Most cited journals were JAMA Ophthalmology (n = 298, SCIMAGO h- index = 190), Graefe’s Archive for Clinical and Experimental Ophthalmology (n = 278, SCIMAGO h-index = 96), Ophthalmology (n = 248, SCIMAGO h-index = 229), Ocular Immunology and Inflammation (n = 237, SCIMAGO h-index = 53), and Indian Journal of Ophthalmology (n = 227, SCIMAGO h-index = 47) among others.

In terms of source impact where TC = total citations and NP = number of publications, Graefe’s Archive for Clinical and Experimental Ophthalmology (h-index = 7, g-index = 16, TC = 278, NP = 43, SCIMAGO h-index = 96), Indian Journal of Ophthalmology (IJO) (h-index = 7, g-index = 10, TC = 227, NP = 127, SCIMAGO h-index = 47), Acta Ophthalmologica (h-index = 7, g-index = 13, TC = 192, NP = 20, SCIMAGO h-index = 82), Eye (h-index = 6, g-index = 11, TC = 151, NP = 54, SCIMAGO h-index = 93), and Ocular Immunology and inflammation (h-index = 3, g-index = 6, TC = 47, NP = 6, SCIMAGO h-index = 53) were sources that had the highest impact contributions to this body of research [Supplementary Table 2].

Supplementary Table 2
Supplementary Table 2:
Most impactful sources for COVID-19 research in Ophthalmology by h-index

Bradford’s law of scattering

Bradford’s law of scattering yielded top core sources contributing to this body of research. These top sources were identified as IJO, Eye and Graefe’s Archive for Clinical, and Experimental Ophthalmology [Supplementary Fig. 1].

Document metrics

Wu 2020 (Local Citation Score [LCS] = 100, Country = China), Seah 2020 (LCS = 74, Country = Singapore), Lai 2020 (LCS = 66, Country = Hong Kong, SAR), Seah 2020 (LCS = 62, Country = Singapore), and Chen 2020 (LCS = 45, Country = China) were the most locally cited references (LCRs). Supplementary Table 3 enlists the top LCRs.

Supplementary Table 3
Supplementary Table 3:
Top 20 locally cited references

Global citation score (GCS) provides the citation frequency based on the full Web of Science count at the time the data was downloaded. Wu 2020 (GCS = 259, Country = China), Seah 2020 (GCS = 156, Country = Singapore), Lai THT 2020 (GCS = 121, Country = Hong Kong, SAR), Seah 2020 (LCS = 74, Country = Singapore), and Li 2020 (GCS = 90, UK) had the greatest number of global citations. Table 2 enlists top global citation documents.

Table 2
Table 2:
Top 20 globally cited documents

Author profile of publications

There was a total of 2398 authors and 3218 author appearances. Sixty-two research items had a single author. Documents per author was 0.257 and authors per document was 3.89. In our collection, 80.0% (n = 1918) of the authors have published only one article, 18.4% (n = 441) have published between 2 and 4 articles, 1.62% (n = 39) have published five or more articles and 0.25% (n = 6) have published 10 or more articles. The greatest number of research items were by Sharma (n = 16), Shetty (n = 12), Bandello (n = 10), Honavar (n = 10), Li (n = 10), and Sachdev (n = 10) among others. The collaboration index was noted to be 4.24.

Anonymous (n = 74), WHO (n = 59), Lu (n = 36), Seah (n = 31), and Xia (n = 30) were the authors with the greatest number of local citations among others whereas the most impactful authors were Li (h-index = 4, g-index = 10, TC = 144, NP = 10), Agrawal (h-index = 4, g-index = 8, TC = 302, NP = 8), Lam (h-index = 4, g-index = 8, TC = 121, NP = 8), Honavar (h-index = 4, g-index = 6, TC = 47, NP = 10), and Bandello (h-index = 4, g-index = 5, TC = 33, NP = 10) among others. Supplementary Table 4 elucidates the author impact of top 20 authors.

Supplementary Table 4
Supplementary Table 4:
Author impact of top 20 authors

The most relevant author affiliations by total number of research items published include LV Prasad Institute, Hyderabad, India (n = 52), All India Institute of Medical Science, New Delhi (AIIMS) (n = 34), Center for Sight, New Delhi (n = 25), United Christian Hospital, Hong Kong (n = 14), Anglia Ruskin University, and Cambridge, UK (n = 13) among others. Supplementary Table 5 elucidates the number of research items from various affiliations.

Supplementary Table 5
Supplementary Table 5:
Number of research items from an affiliation

The cocitation network of references pertaining to COVID-19 research in ophthalmology was created as shown in Fig. 2. The names that appeared the most were Xia (Betweenness = 99.6, Closeness = 0.020), Wu (Betweenness = 80.07, Closeness = 0.020), Lu (Betweenness = 39.4, Closeness = 0.020), Guan (Betweenness = 33.9, Closeness = 0.0196), and Seah (Betweenness = 32.2, Closeness = 0.0196) among others.

Figure 2
Figure 2:
Cocitation network

Keywords plus and author keywords

The most frequent keywords plus were coronavirus (25), SARS (16), COVID-19 (16), telemedicine (13), and ace2 receptor (12) among others. The most frequent author keywords were COVID-19 (173), SARS-CoV-2 (67), coronavirus (51), ophthalmology (38), and conjunctivitis (22).

A co-occurrence network is shown in Supplementary Figs. 2. A thematic map was generated and is depicted in Fig 3.

Figure 3
Figure 3:
Thematic map based on author keywords
  • Motor themes: These were receptor, prevalence, and inactivation.
  • Basic and transversal themes: These were telemedicine, retinopathy, coronavirus, and inactivation.
  • Niche themes: The themes covered were outcomes, impact, and transmission.
  • Emerging or declining themes: Ranibizumab, keratitis fell in the lower left quadrant.

Country-Keyword-Source three-field plot was generated for the data [Supplementary Fig. 3].

Discussion

Globally, as of February 23, 2021, there have been 111,419,939 confirmed cases of COVID-19, including 2,470,772 deaths, reported by WHO.[8] This highly transmittable and pathogenic viral infection not only affects the respiratory system but has the potential to involve other organs such as the eye. Possible theories for ocular involvement include direct inoculation of the ocular tissues from aerosolized viral particles or respiratory droplets, migration from the nasopharynx via the nasolacrimal duct, or even hematogenous spread through the lacrimal gland.[910]

COVID-19 and conjunctivitis

Authors used the keyword “conjunctivitis” in 22 research items in this body of research of which the highest number of citations was merited to the research item published in The Ocular Surface by Xian et al. Xian Zhang and colleagues reported that out of the 72 laboratories tested patients with COVID-19, only two patients had conjunctivitis and only one patient had reverse transcriptase-polymerase chain reaction (RT-PCR) proven viral RNA fragments in the ocular discharge.[11] Several studies have tried to explore the evidence of viral transmission from ocular secretions but no consensus has been reached on the definitive mode of ocular transmission. None of the studies till date have cultured the virus itself from the ocular secretions and it is only the viral RNA that has been reported in some studies to have been detected using RT-PCR.[12]

Trends in COVID-19 research in ophthalmology

Knowing the current trends in research would help develop an interprofessional approach, which will not only help to manage the COVID-19 patients with/without ophthalmic manifestations but also help to mitigate the spread of disease successfully. With a tremendous increase in COVID-19-related publications and different research related to different remote care delivery models in the outpatient,[131415] inpatient, and emergency room[16171819] settings a scientometric map must be generated of all the research currently exisiting in this area. We present a body of publications that quantified country-specific and worldwide coverage of COVID-19 literature pertaining to ophthalmology. To our knowledge, this is the first scientometric review focusing exclusively on ophthalmology and COVID-19. The volume and focus of publications showed a notable increase in the overall number of documents during the study period.

Besides, authors using keywords related to the coronavirus pandemic per se (COVID-19, SARS-Cov-2, corona, coronavirus, coronavirus disease 2019, 2019-nCov, COVID-19, pandemic, coronavirus; n = 337), telemedicine-related keywords had a high occurrence frequency (Telemedicine, teleophthalmology; n = 44) indicating a substantial surge in telemedicine-related research in ophthalmology during the pandemic. Conjunctivitis (n = 43), cornea (n = 25), guidelines (n = 12), and ocular surface (n = 10) were other common author keywords. While keywords plus had relatively fewer COVID-19-related keywords (Coronavirus, SARS, virus, COVID-19, Coronaviruses; n = 68). Telemedicine-related keywords (Telemedicine, teleophthalmology, telehealth, teleconsults, n = 25), Angiotensin-converting enzyme-related keywords (ACE2, angiotensin-converting enzyme, angiotensin-converting enzyme-2, n = 21), and respiratory symptom-related keywords (acute respiratory syndrome, pneumonia, n = 11) constituted other highly occurring keywords in keywords plus. With the new COVID variants and a potential new wave of COVID-19 and a possible COVID hurricane in the future, clinic schedule volumes may remain below pre-COVID-19 levels for the foreseeable future. Therefore, the role of telemedicine and teleophthalmology cannot be ignored.

From the three-field plot [Supplementary Fig. 3], it can be seen that the research pertaining to the author keyword “Guidelines” published in Indian Journal of Ophthalmology (IJO) and Current Opinion in Ophthalmology was performed in India, United Kingdom, Italy, and China. Telehealth, Telemedicine, and teleophthalmology were common keywords from sources viz., IJO, Graefe’s Clinical and Experimental Ophthalmology, Ophthalmology and Therapy, Der Ophthalmolge, Journal Francais De Ophthalmologie, BMJ Open Ophthalmology, Current Opinion in Ophthalmology, Clinical Ophthalmology, and Contact Lens and Anterior Eye. This research was conducted in countries viz. India, Israel, United Kingdom, United States of America, France, and Germany. Current Opinion in Ophthalmology, European Journal of Ophthalmology, International Ophthalmology, Acta Ophthalmologica, and Contact lens and anterior eye were sources that featured research from Spain, Egypt, Italy, China, UK, Germany, and USA with keywords PPE (personal protective equipment). Given the large population of India and China, these two countries had not only more people inflicted with the virus but also needed a strict set of standard guidelines, to curtail the spread.

Research pertaining to keywords transmission, conjunctivitis, and ocular surface symptoms was featured in Graefe’s Clinical and Experimental Ophthalmology, Eye and Vision, Ocular Immunology and Inflammation, Acta Ophthalmologica, International Journal of Ophthalmology, Journal of Medical Virology, and Der Ophthalmologe. This research originated from countries viz. China, Italy, France, Spain, Finland, UK, USA, India, Turkey, Singapore, Australia, Canada, and Columbia.

The main limitation of this paper is its intrinsic bias. It was based on the Web of Science database and we know that the results may differ according to other databases or the inclusion of other search terms.

Conclusion

Our scientometric analysis provides a descriptive quantitative analysis and provides evidence that more global contribution toward COVID-related ophthalmic research can help in the prompt implementation of protocols and guidelines across the globe that will serve mankind in these tough times.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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Keywords:

Bibliometric analysis; coronavirus and eye; coronavirus disease 2019; COVID-19 and ophthalmology; COVID-19 research trends; pandemic and ophthalmology research

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