ArticleJournal of asthma and allergy2025
Knowledge Mapping of COVID-19 and Asthma/Allergic Rhinitis: A Visual and Bibliometric Analysis.
Article in Journal of asthma and allergy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Global research trends in the epidemiology of allergic disorders: a bibliometric and evidence-mapping review.Frontiers in medicine · 2026Pooled it
- Global trends in chronic kidney disease related cognitive impairment/dementia: a bibliometric analysis (2005-2025).Frontiers in neurologyPooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Numerous studies have highlighted a link between COVID-19 and respiratory allergic conditions such as asthma and allergic rhinitis (AR). Despite the growing volume of research, there remains a notable gap in the form of a comprehensive bibliometric analysis that consolidates the findings on this association. This study aims to fill that gap by systematically exploring how asthma and AR interact with COVID-19. Methods: By using the Web of Science Core Collection, we selected publications from January 2020 to October 2024 that related to COVID-19 and asthma/AR. Analysis tools such as VOSviewer and CiteSpace were employed to perform network mappings and citation analyses, focusing on co-authorship networks, keyword co-occurrences, and citation impacts to understand the research dynamics and collaborative patterns within this field. Results: A collection of 553 publications was obtained, revealing an upward trend in research volume over the study period. The United States, China, and the United Kingdom were predominant in the research output, demonstrating extensive international collaborations. The study highlighted key areas of impact, such as the influence of asthma types on COVID-19 severity and the protective effects of specific treatments like inhaled corticosteroids and biologics. Emerging trends identified included the significance of socioeconomic factors and obesity in disease outcomes, as well as evolving strategies in vaccination and interventions. Conclusion: This bibliometric analysis highlights the significant role of global research in exploring the interactions between COVID-19 and asthma/AR. It points out the reported safety and effectiveness of COVID-19 vaccines for these conditions and acknowledges the challenges in vaccine uptake among minority and socioeconomically disadvantaged groups. The study also identifies unique risks for children and obese patients during the pandemic and underscores the need for increased international collaboration and more comprehensive clinical trials, to evaluate the efficacy of treatments like inhaled corticosteroids and biologics.
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Registered trials
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.