ABSTRACT
BACKGROUND: Anesthesiology departments and professional organizations increasingly recognize the need to embrace diverse membership to effectively care for patients, to educate our trainees, and to contribute to innovative research. 1 Bibliometric analysis uses citation data to determine the patterns of interrelatedness within a scientific community. Social network analysis examines these patterns to elucidate the network's functional properties. Using these methodologies, an analysis of contemporary scholarly work was undertaken to outline network structure and function, with particular focus on the equity of node and graph-level connectivity patterns. METHODS: Using the Web of Science, this study examines bibliographic data from 6 anesthesiology-specific journals between January 1, 2017, and August 26, 2022. The final data represent 4453 articles, 19,916 independent authors, and 4436 institutions. Analysis of coauthorship was performed using R libraries software. Collaboration patterns were assessed at the node and graph level to analyze patterns of coauthorship. Influential authors and institutions were identified using centrality metrics; author influence was also cataloged by the number of publications and highly cited papers. Independent assessors reviewed influential author photographs to classify race and gender. The Gini coefficient was applied to examine dispersion of influence across nodes. Pearson correlations were used to investigate the relationship between centrality metrics, number of publications, and National Institutes of Health (NIH) funding. RESULTS: The modularity of the author network is significantly higher than would be predicted by chance (0.886 vs random network mean 0.340, P < .01), signifying strong community formation. The Gini coefficient indicates inequity across both author and institution centrality metrics, representing moderate to high disparity in node influence. Identifying the top 30 authors by centrality metrics, number of published and highly cited papers, 79.0% were categorized as male; 68.1% of authors were classified as White (non-Latino) and 24.6% Asian. CONCLUSIONS: The highly modular network structure indicates dense author communities. Extracommunity cooperation is limited, previously demonstrated to negatively impact novel scientific work. 2 , 3 Inequitable node influence is seen at both author and institution level, notably an imbalance of information transfer and disparity in connectivity patterns. There is an association between network influence, article publication (authors), and NIH funding (institutions). Female and minority authors are inequitably represented among the most influential authors. This baseline bibliometric analysis provides an opportunity to direct future network connections to more inclusively share information and integrate diverse perspectives, properties associated with increased academic productivity. 3 , 4.
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on the practice of medicine worldwide, particularly in anesthesiology. As the clinical realm has rapidly adjusted to the realities of the pandemic, anesthesiology literature has also changed significantly to reflect this. The purpose of this study was to characterize the effects the COVID-19 pandemic has had on anesthesiology literature. Specifically, it was hypothesized that the COVID-19-related literature in the anesthesiology community would gain more interest than non-COVID-19-related articles. A total of 15 anesthesiology-related journals with the highest impact factor in 2019, according to the Journal Citation Reports (JCR), were selected for data collection. An advanced PubMed search identified 5,722 COVID-19-related articles published by these journals in 2020. Next, articles with titles including "corona," "COVID," "COVID-19," "pandemic," "SARS," or "SARS-CoV-2" were selected for inclusion in the study, which resulted in 676 (12%) articles. A Kruskal-Wallis test was used to assess the Altmetric score, which is a weighted calculation of the attention an article receives online, for COVID-19 versus non-COVID-19 articles. Articles were then further characterized across multiple different variables, including country of origin, month published, type of article, and subspecialty of anesthesiology it pertained to. Of the 15 journals investigated, 676 (12%) articles of the 5,722 total articles published were found to be COVID-19-related material. The majority of the articles were found to be published in April (18%), May (19.5%), and June (14%). The majority of these articles were related either to general anesthesia (operating room anesthesiology that is not tied to a particular subspecialty fellowship track) (48%) or critical care (39%). By article type, most were determined to be editorial (71%) in nature, followed by original research articles (21%), of which most were cross-sectional (55%) studies. When compared with non-COVID-19-related articles, COVID-19-related articles had a significantly greater Altmetric score (29.518 versus 8.6333, p < 0.001). Of the COVID-19-related articles, original articles had the greatest Altmetric score, when compared to editorials and guidelines (54.794 versus 20.777 versus 40.643, p < 0.002). The response of the academic anesthesiology community to the COVID-19 pandemic was strong and timely, with a particularly strong focus on critical care anesthesia. The impact of the pandemic was strongly felt by the anesthesiology community, and their timely response served to guide our country and world through an incredibly challenging time. The pandemic highlighted the value of anesthesiologists worldwide, not only in the operating room setting but particularly as critical care physicians.
