ArticleFrontiers in cardiovascular medicine2022
Cardiac Involvement in COVID-19: A Global Bibliometric and Visualized Analysis.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed, 8 citations in OpenAlex.
- Research landscape on COVID-19 and liver dysfunction: A bibliometric analysis.World journal of gastroenterology · 2023Review
- Intraocular lens power calculation formulas: a scientometric analysis.Medical hypothesis, discovery & innovation ophthalmology journal · 2023Article
- Consider affection of respiratory muscles in SARS-CoV-2 related polyradiculitis with coughing but normal inflammatory markers.Annals of medicine and surgery (2012) · 2022Article
- Bibliometric and visual analysis of cardiovascular diseases and COVID-19 research.Frontiers in public health · 2022Article
- Bibliometric evaluation of 2020-2022 publications on COVID-19-related cardiovascular disease.Frontiers in cardiovascular medicine · 2022Article
- Science mapping of COVID-19 contributions in primary health care by OECD countries: A machine learning approach.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Coronavirus disease 2019 (COVID-19), which was caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), had already resulted in widespread epidemics worldwide and millions of people's deaths since its outbreak in 2019. COVID-19 had also been demonstrated to affect people's cardiac function. However, the specific mechanism and influence of this damage were not clear yet. The purpose of the present study was to provide a bibliometric analysis of the current studies related to cardiac involvement after SARS-CoV-2 infection. Methods: A bibliometric literature search was performed on the web of science. The number and type of publications, countries, institutional sources, journals, and citation patterns were analyzed. In addition, qualitative and quantitative evaluations were carried out to visualize the scientific achievements in this field by using the VOSviewer software. Results: Web of science had recorded 2,24,097 documents on COVID-19 at the time of data collection (May 12, 2022). A total of 2,025 documents related to cardiac involvement were recorded at last. The countries with the most published articles were the United States of America (USA) ( Conclusions: It was the first bibliometric analysis of publications related to COVID-19-associated cardiac disorder. This study provided academics and researchers with useful information on the most influential articles of COVID-19 and cardiac dysfunction. Cooperation between countries and institutions must be strengthened on myocarditis and HF during COVID-19 pandemic.
Indexed as
Identifiers
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.