The top-100 most cited articles of biomarkers in congenital heart disease: a bibliometric analysis

Introduction

Congenital heart disease (CHD) is typically defined as a defect in the structure and function of the heart caused by abnormal heart development before birth. The prevalence of CHD has gradually increased from 8.2 to 9.4 cases per 1,000 live births over the past 10 years (1,2). CHD may be caused by chromosomal abnormalities, environmental factors and micronutrient deficiencies, but there remains substantial uncertainty regarding risk factors of 80% cases (3-5). Improvements in surgical practice and intervention had resulted in a significant reduction in CHD mortality (6,7). The number of deaths due to CHD in 2017 was estimated to be 261,247 (range from 216,567 to 308,159), a decrease of 34.5% from the estimated in 1990. The decline in mortality had also led to an estimated 12 million patients with CHD worldwide in 2017, an increase of 18.7% from 1990 (8). With all improvements in care, it might be predicted that adult with congenital heart disease (ACHD) will eventually grow to an estimated 75,000 patients per ten million residents (9).

With the landscape of CHD dramatically changing, the sequelae of CHD and its treatments have increasingly emerged (10). The detection of fetal CHD and evaluation of postoperative risk are the keys to reducing mortality and improve the management of CHD. The use of biomarkers have been demonstrated to provide a minimally-invasive method that can be used to monitor the basic conditions in CHD, and incorporated into daily clinical practice for risk stratification and optimize therapeutic regimens. This is the reason why biomarkers have attracted more and more attentions in recent years (11,12). The biomarker is a quantifiable and surrogate indicator that can reflect the existence or severity of a disease. Biomarkers are broadly defined as clinical observations, laboratory tests, or imaging parameters (13) that may be able to reflect the pathophysiological process of heart disease and also be able to provide meaningful information about prognosis, to help guide clinical decision-making. Biomarkers had already played an integral role in the treatment and management of patients with heart failure and coronary heart disease because of the important information the values provided (14-17). This had also prompted the enthusiasm for research of biomarkers in CHD field meanwhile clinicians start to recognize the diagnostic and prognostic significance of biomarkers in CHD patients. In the newly released 2020 ESC Guidelines for the management of ACHD, the emerging role of biomarkers in the follow-up of ACHD had also been proposed as a new concept (18).

Bibliometric analysis was used to help determine the frequency of articles cited describing CHD and biomarkers and may help to define areas for future research. Bibliometric analysis is a research method that uses mathematical or statistical methods to describe the quantity of external characteristics of literature, and then evaluates and predicts the current status and development trend of science and technology (19-21). Bibliometrics analysis mainly uses quantitative methods to analyze the metrological characteristics of papers published in a certain field. It is an emerging discipline that studies mathematical laws in literature. Co-word analysis is an important method of bibliometrics, which can be used to identify trends and hot topics. Use modern statistical technology to classify subject keywords, summarize research hotspots and research structure, which have important reference value for planning subject layout and adjusting discipline direction (22,23).

In this study, bibliometric analysis was used to reveal the top-100 cited articles of biomarkers in CHD field for the first time, in order to provide an insight on the citation frequency of top-cited articles published on biomarkers in CHD field, to help recognize the quality of the works, discoveries, and the research trends steering biomarkers in CHD field, hoping to provide a reference for future research in this field.

Methods

Database and search strategy

We conducted a highly sensitive search for publications of biomarkers in CHD using the Web of Science (WoS) Core Collection database on 4 June 2020. Articles published between January 1980 and June 2020 were searched. The search strategies were shown in Table 1. The 100 most frequently cited articles identified in the search were reviewed by two of the authors (one is a cardiovascular surgeon, and the other is a researcher from evidence-based medicine center) independently. After the independent screening, two researchers cross-checked and discussed the disagreements, and finally reached a consensus on whether the suspected articles should be included. No time and language limitations were implemented on the retrieval. Document Types such as meeting abstracts, news item, conference proceeding, letters to the editor, correction, and editorial material were excluded. The review of biomarkers in cardiovascular disease (CVD) involves CHD and the review of CHD referred to biomarkers were also included. Studies on non-human subjects were also included. The citation rate was defined as the total number of citations divided by the number of years since the article was published.

For two articles with the same absolute number of citations, the literature with high citation rate will be given priority.

Data collection and statistical analysis

Two reviewers individually classified the articles via Endnote X8 for further categorization, and extracted the following data: authors, title, publication year, citation frequency, journal name, impact factor (IF), institutions of authors, country of authors, keywords, co-citation references, co-citation authors, co-citation source journals.

The Microsoft Excel 2019 was applied to analyze publication year, journals, citation frequency, countries, institutions, co-citation references, co-citation authors, and a bubble plot was created to show the relationship between publication year and citations. Furthermore, a scatter plot of IF and average citation frequency of journals was also made using Microsoft Excel. We fitted the trend line to find the relationship between IF of journals and the average citation frequency of articles published on it. The IF of journals was obtained from the 2019 Journal Citation Reports (Clarivate Analytics, 2019).

Visualized analysis and network mapping

VOSviewer 1.6.9 (Leiden University, Leiden, The Netherlands) was used to extract key information, for the high frequency fields such as countries and keywords, we make a network map for visual analysis, and furthermore analyze the potential clustering (24). In cluster analysis, different colors showed different fields or directions, and represent different sub-clusters or classifications in this field. Before performing the analysis, data were standardized. We standardized different expressions about the same author or keyword into the uniform expression to reduce the bias in data analysis, and standardization was carried out manually by the authors. We also reclassified articles from England, Northern Ireland, Scotland, and Wales to the United Kingdom (UK) and articles from Hong Kong, Macau and Taiwan to China (25). CiteSpace is a scientific application for progressive knowledge domain visualization, it reveals the dynamics in scientific literature as well as visualizing and analyzing trends and patterns in a given research field (26,27). CiteSpace 5.7.R1 was used in this study to detect bursts for co-occurrence keywords and co-cited references, and design the dual-map overlay of journals. Bursts are defined as a characteristic such as author, keyword, or co-cited reference, which are cited frequently over a period of time.

Results

A total of 877 articles were reviewed and 237 have been cited more than 14 times. The selected 100 most cited related articles underwent subsequent analysis. Among the top-100 publications, 89 were original research and the remaining 11 were reviews, and the total number of citations was 3,536 while Hirsch Index was 32 (28). The authors, title, journal, and volume of the top 100 publications, as well as the citations and citation rate, were listed in available online: https://cdn.amegroups.cn/static/public/apm-21-2422-01.pdf.

Distribution of publication years

Figure 1 showed the time and citations distribution. After the identification of the 100 most frequently cited articles, the first article was published in 1996 by Taggart et al. (29). Compared with the previous years, the citation frequency of articles published after 2005 had increased significantly. Due to the relatively low number of citations, none of the articles published in the past three years from 2018 to 2020 ranked in the top 100. From Figure 1, we can also find that the average highest citations appeared in 2007, the highest total citations appeared in 2012, and most articles (n=15) published in 2013.

Figure 1 Bubble plot of published years and citations. Produced by Microsoft Excel 2019 (Microsoft Corp., Redmond, WA, USA). In the bubble plot, the X-axis represented the time range of top 100 cited papers, the Y-axis symbolized the total amount of citations per year, the bubble size stood for the average amount of citations per article in every year. In the data label, the former (red color) is the value of total citations, the middle (green color) is the value of bubble size, and the last (blue color) is the number of papers.

Sources of journals

The top 100 cited articles were published in 56 journals. Table 2 listed the top ten contributing journals. For the complete journal list, see in Table S1. There were 28 (50%) journals from United States of America (USA), in which 56 of the 100 articles had been published. The top ten productive journals published 41 of the total number of articles. Pediatric Cardiology published the largest number of papers (n=8), followed by Journal of Thoracic and Cardiovascular Surgery (n=5) and International Journal of Cardiology (n=5). Of the top ten most prolific journals in our analysis, seven were specialized journals of cardiology, one was general medical journal, one focused on biochemistry, and one focused on pediatric nephrology.

The medians (25th–75th quartiles) of IF between the 56 journals were 3.05 (2.12, 5.21). Figure 2 showed the relationship between IF and the average amount of citations per journal. The relationship between the IF of journals and the average citations per journal was found by fitting the linear function (y =1.8074x +24.74, R²=0.1562). We use the trend line as a benchmark, and take 20 citation frequency as the floating interval to form a range, and there were nine outlier journals outside the range.

Figure 2 Scatter plot of impact factor and average amount of citations per journal. Produced by Microsoft Excel 2019 (Microsoft Corp., Redmond, WA, USA). IF, impact factor.

Countries collaboration

The geographical distribution of top-100 publications of biomarkers in CHD involved 23 countries (see Figure 3). The USA contributed 36 articles, followed by China (n=15) and Germany (n=14). For articles completed by cooperation between different countries, this article will be included in the number of articles issued by different countries. International collaboration was analyzed based on country using the VOSviewer. Figure 4 presented a visualization map of collaboration between different countries with minimum occurrences of three. The visualization map showed ten countries distributed in five different clusters, and each cluster with a unique color represented a close working network. The USA had the strongest collaboration network, represented by a total link strength of 13, followed by The United Kingdom (UK) (total link strength eight), Canada, and Italy (both have a total link strength of six).

Figure 3 Countries contributed to the top-100 cited articles. Produced by Microsoft Excel 2019 (Microsoft Corp., Redmond, WA, USA).

Figure 4 The network map of countries for the top 100 most cited articles on biomarkers in congenital heart disease. Produced by VOSviewer 1.6.9 (Leiden University, Leiden, The Netherlands).

Authorship/organizations collaboration

A total of 639 authors were extracted in the top-100 cited articles. The collaboration between authors is mostly limited in the same research workgroup, and the collaboration between teams was not reflected in the top 100 articles. Table 3 showed the authors contributed to three or more papers in this field.

There was a total of 184 institutions. Table 4 listed 11 institutions that had published three or more top-cited papers on biomarkers in CHD. The University of Cincinnati College of Medicine from USA and the Fondazione Toscana G. Monasterio from Italy were both prolific and participated in publishing 5 articles, respectively. The collaboration between institutions was the same as the collaboration between teams, and there were no obvious connections to conform a network map (see in Figure S1).

Co-citation analysis

Co-citation analysis showed a total of 21 authors had at least ten citations (0.86% of all the authors in the field). There were three articles co-cited up to ten times. The most cited publication with a citation count of 12 which was published by Lancet (30). The five journals which total citation frequency higher than 100 times were Circulation (n=241), Journal of The American College of Cardiology (n=137), Journal of Thoracic and Cardiovascular Surgery (n=123), American Journal of Cardiology (n=108), and Pediatric Cardiology (n=103), respectively. In CiteSpace, the threshold was set to top 80 in a one-year slice, strong citation bursts of co-cited references were not detected. Figure 5 showed the dual-map overlay of journals. The left side represented the map of citing journals and the right side represented the map of cited journals. The label represented the subject covered by the journal. Colored curves represent paths of references, originating from the citing map on the left and pointing to the cited map on the right (31). There were two main citation paths (both green) shown on the map. The green paths mean papers published in medicine/medical/clinical mostly cited journals in molecular/biology/genetics, health/nursing/medicine. Figure 6 showed the most frequently cited journals (occurrences ≥20) in the co-citation analysis.

Figure 5 The dual-map overlay of journals related to biomarkers in congenital heart disease. Produced by CiteSpace 5.7.R3 (Drexel University, Philadelphia, PA, USA). The green paths are the main citation paths: Papers published in medicine/medical/clinical mostly cited journals in molecular/biology/genetics, health/nursing/medicine.

Figure 6 Hotspot of the source of the journal with co-citation references. Produced by VOSviewer 1.6.9 (Leiden University, Leiden, The Netherlands).

Keywords mapping

A total of 626 keywords were extracted and the total frequency of occurrence was 1,209. In Table 5, the 18 keywords with eight or more times presented were listed. In CiteSpace, we set the same parameters as the co-cited references citation bursts analysis, and no keyword bursts were detected during the period from 2001 to 2017. Clustering analysis for keywords occurred five or more times was presented in Figure 7, which divided into four clusters. The keywords with high frequency can accurately reveal the main topic of a field. Table 6 shows the four clusters describing disease conditions (such as heart failure) and surrogate parameters (such as proBNP) in the keyword cluster analysis. The terms “congenital heart disease” and “biomarkers” were the subject in this bibliometric analysis and were not included in any cluster.

Figure 7 The network map of keywords for the top 100 most cited articles on biomarkers in congenital heart disease. Produced by VOSviewer 1.6.9 (Leiden University, Leiden, The Netherlands).

Discussion

In 1987, Garfield published the first analysis of top-cited articles in JAMA (32). Similar citation analysis had subsequently been performed in many fields of medicine to provide useful information on aspects such as the types and levels of evidence in the articles, the most frequently studied topics, the historical development of the field, and current research trends (33,34). The total number of citations that a published article has achieved indicates the importance that the published article has on that area of practice. Analysis of the most influential publications can be helpful in recognizing main and novel issues within a specific field.

This study conducted the first bibliometric review of publications, contributions, authors, countries, and institutions related to biomarkers in CHD, and identified the most commonly cited publications and journals. The analysis not only to provide recognition to the most prolific entities in the field, but also helps agencies guide their limited resources toward authors and institutions that continuously produce high-quality work. Furthermore, this information can help researchers find potential collaborators in the field.

From 1996 to 2017, the most published literature was included in 21 years, and the absence of literature in the recent three years also indicated that recently published papers need a period of exposure time to increase their citation, which requires at least three years. Numerous factors contribute to total citations, of which the older the article was dated the more citations it tended to accumulate. This effect of time can be further explained by scientific articles reaching their peak number of citations three to ten years after publication, after which they were cited at a less recurring rate.

We explored whether the IF of a journal affects the number of citations of a paper. Journals with high IF usually attract high-quality papers, and the excellent papers can further enhance the academic influence in turn, which forms a positive feedback effect. In our analysis, journals with high IF deviated from the range confirmed this theory (35). While the journals in the upper left corner of Figure 2 were authoritative journals in this field (18,36-39), this indicated that high-quality articles in a specific field were more willing to be published in professional related journals rather than some comprehensive journals with higher IF. The outlier journals with high IF below the fitting range in the Figure 2 showed an inconsistent citation frequency. To analyze the reason for this phenomenon, some papers published in these journals were in recent years (40), and elapsed time was needed for these articles to spread and accumulate citations. There are also some articles published in comprehensive journals, which may affect the citation frequency of articles (41).

The geographic distribution of the network map of biomarkers in CHD field showed that the USA was the most productive country in terms of total publications and total citations. Most of the top 11 institutions were from the USA. This finding is consistent with previous findings that cardiovascular research activities are directly correlated with the human development index and negatively correlated with CVD burden (42). The possible reasons for developing countries with a low output may be inadequate funding, political instability, and a lack of enthusiasm and inclination for research in this area. There was no significant trend in cooperation between institutions, and it suggested that cross-institutional cooperation should be carried out to jointly improve its scientific research capabilities.

From the type of literature included, we found that the original research accounted for the majority, while the review articles were few, which indicates that this field was in its infancy and more research was needed to promote more review articles. Collaboration between authors was mainly concentrated in the same research group in the same institution while 90.20% of authors only published one top-100 article, indicating the authors continued to participate in high-cited articles on biomarkers in CHD field was few.

Our findings support the application of Bradford’s law, a bibliometric concept suggested by Brookes (43,44). The principle idea behind Bradford’s law was that most researchers obtained their citations from a few main journals in their respective field of expertise. When the researchers deviate from these core journals, their citation frequency and impact were weakened. Consequently, this tendency led to a large percentage of citations stemming from a few core journals. In summary, we identified and analyzed the co-citation characteristics of the 100 most-cited articles of biomarkers in CHD, and some core journals in this field were identified. The characteristics of these journals, highly cited references can show that prolific leading position in this field.

Four clusters were obtained after cluster analysis, which represents the four research hotspots in this field. Cluster I was the application of natriuretic peptide in CHD. The natriuretic peptide is a common and reliable biomarker in CVD. Brain natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (NT-proBNP) can be used for comprehensive evaluation and monitoring of children with CHD, to further determine the severity and progress of heart failure and its response to treatment. BNP/NT-proBNP can also be used as an auxiliary marker for screening CHD with hemodynamic significance and prognosis of children undergoing cardiac surgery (45,46). Cluster II indicated that some genes and their related transcriptional translation agents as biomarkers were associated with prognosis or predicted the occurrence of CHD. There is a growing interest to use circulating biomarkers for risk stratification in patients with CHD such as bicuspid aortic valve. The following biomarkers are being focused on: matrix metalloproteinases (MMPs), transforming growth factor β (TGF-β), tissue inhibitors of matrix metalloproteinases (TIMPs), alpha1-antitrypsin, as well as non-coding microRNAs (47,48). Cluster III represented biomarkers in secondary injury after cardiopulmonary bypass in children with CHD, such as Neutrophil gelatinase-associated lipocalin (NGAL) and SB100 protein, which mainly involved the prediction and evaluation of kidney injury and brain injury after extracorporeal circulation (49,50). The concentration of NGAL in urine and serum represents a sensitive, specific and highly predictive early biomarker of acute kidney injury after cardiac surgery. After cardiac surgery with cardiopulmonary bypass, the brain oxygenation of infants with increased S100B concentrations is impaired during perioperative period. Astrocyte protein S100B can be used as an alternative parameter for cerebral hypoxemia after surgery for CHD. Cluster IV represented the application of biomarkers such as homocysteine, NO, and oxidative stress in the assessment of general state and cardiac injury in CHD. Identifying the nature and extent of alterations in biomarkers such as homocysteine, NO, and oxidative stress, may suggest primary intervention strategies and provide clues to a greater understanding of the pathogenesis of CHD (51,52). Keywords cluster analysis pointed out that research in these fields will still be the focus in the next few years. This may serve as a guide for the use of limited medical funding resources and for the selection of topics for young researchers.

Limitations

There were some limitations in our analysis. (I) According to the time distribution of the included literature, the application of biomarkers in CHD was relatively new. Only 60 of the top 100 literature had been cited more than 20 times, indicating that this field had not received extensive attention in the past. The quantitative bibliometric analysis needed more high impact articles in this field to reflect the general characteristics. At this time, our main aim of this analysis was summarized the future research trends, so that the limited research funding input can get effective output. Five years or ten years later, an updated quantitative analysis in this field may have a renewal in the list of top-100 article, but the overall basic characteristics and research direction reflected should not change greatly. (II) We chosen WoS core database instead of Scopus as our retrieval source database. While focusing on the quality of journal sources, we relatively missed some journals that were not included in JCR. (III) We have performed manual standardization for some keywords. This process aims to reduce the bias caused by different expressions of the same phrase, but the influence of the bias on the analysis cannot be completely eliminated.

Conclusions

According to this bibliometric study, research of biomarkers in CHD field had increased interest in these years and we also highlighted the global research trends, research subjects, and collaboration network between countries. The future research hotspots in this field were listed as follows: (I) the application of natriuretic peptide, (II) the diagnostic and prognostic value of genes and their related transcriptional translation agents, (III) the use of biomarkers to evaluate and predict the postoperative injury caused by extracorporeal circulation, (IV) and the application of other biomarkers (such as oxidative stress, homocysteine, and thrombosis) to assess and predict damage circumstance. The findings provided insight for policy-makers and researchers in making decisions, agreeing with future research precedence and contributing to continuing development in this dynamic field.

Acknowledgments

Funding: This study was supported by the Gansu Province Science and Technology Plan Funded Project under project number 20CX4ZA027 & 20CX9ZA112, Natural Science Foundation of Gansu Province under project number 21JR1RA027, and Health industry scientific research project of Gansu Province under project number GSWSKY2016-04.

Footnote

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-21-2422/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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