ArticleJAMA network open2023
Global Trends in Highly Cited Studies in COVID-19 Research.
Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers, 1 of them a synthesis 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Low reporting quality limits the contribution of human organ models to COVID-19 research: a systematic review.EBioMedicine · 2026Pooled it
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- Global research trends in liver regeneration and immunomodulation: A perspective from bibliometric analysis.Human vaccines & immunotherapeutics · 2025Article
- Minimalistic transcriptomic signatures permit accurate early prediction of COVID-19 mortality.JCI insight · 2025Article
- Exploring the changing landscape of medical imaging: insights from highly cited studies before and during the COVID-19 pandemic.European radiology · 2025Article
- Post-COVID-19 Syndrome as Described by Patients: A Qualitative Study.Healthcare (Basel, Switzerland) · 2025Article
- Trends and Hotspots in Nanomedicine Applications for Pain: A Bibliometric Analysis from 1999 to 2024.ACS omega · 2025Article
- Global vaccine research and application hotspots and trends: a systematic bibliometric analysis based on SCIE highly cited papers.BMJ open · 2025Article
- The Development of Publications on Catheter-Related Bladder Discomfort: A Bibliometric Analysis.Therapeutics and clinical risk management · 2025Article
- Low back pain in China: Disease burden and bibliometric analysis.World journal of orthopedics · 2024Article
- Mapping knowledge landscapes and emerging trends of Marburg virus: A text-mining study.Heliyon · 2024Article
- Bibliometric analysis of publication trends on ocular hygiene and infections in the past two decades.GMS hygiene and infection control · 2024Article
- Beyond nodes and edges: a bibliometric analysis on graph theory and neuroimaging modalities.Frontiers in neuroscience · 2024Review
- Incorrect Institution Name in Author Affiliations.JAMA network open · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Since the onset of the COVID-19 outbreak, an extremely high number of studies have been published worldwide, with variable quality. Research trends of highly cited papers may enable identification of influential research, providing insights for new research ideas; it is therefore important to investigate trends and focus on more influential publications in COVID-19-related studies. Objective: To examine research trends of highly cited studies by conducting a bibliometric analysis of highly cited studies in the previous 2 months about COVID-19. Design, Setting, and Participants: In this cross-sectional study, Essential Science Indicators (ESI) and Web of Science (WOS) Core Collection were used to find studies with a focus on COVID-19 that were identified as highly cited studies from Clarivate Analytics. Highly cited studies were extracted from the ESI database bimonthly between January 2020 and December 2022. Bibliographic details were extracted from WOS and combined with ESI data using unique accession numbers. The number of highly cited studies was counted based on the fractional counting method. Data were analyzed from January through July 2023. Main Outcomes and Measures: The number of publications by research field, country, and institutional affiliation. Results: The number of published COVID-19-related highly cited studies was 14 studies in January to February 2020, peaked at 1292 studies in November to December 2021, and showed a downward trend thereafter, reaching 649 studies in November to December 2022. China had the highest number of highly cited studies per 2-month period until July to August 2020 (138.3 studies vs 103.7 studies for the US, the second highest country), and the US had the greatest number of highly cited studies afterward (159.9 studies vs 157.6 studies for China in September to October 2020). Subsequently, the number of highly cited studies per 2-month period published by China declined (decreasing from 179.7 studies in November to December 2020 to 40.7 studies in September to October 2022), and the UK produced the second largest number of such studies in May to June 2021 (171.3 studies). Similarly, the top 5 institutional affiliations in May to June 2020 by highly cited studies per 2-month period were from China (Huazhong University: 14.7 studies; University of Hong Kong: 6.8 studies; Wuhan University: 4.8 studies; Zhejiang University: 4.5 studies; Fudan University: 4.5 studies), while in November to December 2022, the top 5 institutions were in the US and UK (Harvard University: 15.0 studies; University College London: 11.0 studies; University of Oxford: 10.2 studies; University of London: 9.9 studies; Imperial College London: 5.8 studies). Conclusions and Relevance: This study found that the total number of highly cited studies related to COVID-19 peaked at the end of 2021 and showed a downward trend until the end of 2022, while the origin of these studies shifted from China to the US and UK.
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What OpenQuestion holds
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.