Bibliometrics is a systematic method that is broadly defined as a quantitative examination of published documents (Broadus, 1987; De Bellis, 2009). Using approaches such as content analysis, text analysis, citation analysis, keyword co-occurrence, co-citation analysis, or co-authoring analysis, Pritchard described bibliometrics as the application of mathematics and statistical methodologies to books and other media of communication (Pritchard, 1969; Dias, 2019). By highlighting the most significant articles, the bibliometric analysis might help the scholar avoid becoming overwhelmed by the massive amount of publications (Karydakis et al., 2019). Utilizing citation data, citation analysis quantifies the study’s influence as a reflection of the volume of citations a publication accumulates over time (Yadava et al., 2019). Additionally, citation analysis is employed to assess academic impacts (Liu et al., 2013). The papers with a high citation count are assumed to contain insightful suggestions for further studies (Jeung et al., 2011) and their authors are regarded as significant figures in the field (Butt et al., 2019).

The majority of bibliometric studies used citation analysis to determine the most popular papers, authors, journals, countries, co-authorship of authors, and keyword co-occurrences (Alarcon-Ruiz et al., 2019; Lee et al., 2019). Citation analysis has been applied in a variety of fields to identify the most significant publications (States et al., 2019). The frequency with which a text has been cited by other researchers can be determined using techniques of citation analysis (Xu et al., 2015). Citation analysis methods have recently made their way into the medical studies (Chen, 2004; Gupta et al., 2019).

The study had nothing to do with the approval of ethical committees. The WoS database was used to retrieve the data for our study. Data were gathered in December 2020 utilizing the WoS database’s internet search engine. In this study, the authors conducted a comprehensive search of all papers using the term “Preeclampsia” as the search query. Only the “TITLE” was the subject of keyword searches. As a result, a group of 3754 papers written between 1985 and 2020 were gathered. Then, this collection was fixed as the foundation for all ensuing VOSviewer analyses. The application CiteSpace and VOSviewer (1.6.11) was used to create bibliometric network visualizations (Chen, 2004; Van Eck & Waltman, 2009).

A review of the literature revealed that 14,230 publications about preeclampsia were published between 1985 and 2020. Article (3,754), Proceedings Paper (221), Early Access (62), and book chapter are among these publications (13). In this study, 7,653 of the 7,869 English-language papers that fall under the category of obstetrics and gynaecology were examined. The total number of articles eventually decreased to 3,754 (Figure 1).

Country maps were created using Gunnmap. VOSviewer software was used to examine the bibliometric co-occurrence keyword analysis, CiteSpace for the analysis of keywords trends, Carrot2 for the analysis of bibliometric document co-citations, and Bibliometrix^® for the analysis of the strategic map.

A total of 3,495 papers were included. Figure 2 shows the growth in preeclampsia research from 1985 to 2020 in terms of publications (total studies/TS) and citations (total citations/TC) each year. Over half of the articles (51% of them) were published within the last 10 years.

The top 20 document-producing authors, nations/regions, and organizations/institutions are recognized. The ranked authors who reproduced preeclampsia articles between 1985 and 2020 were Sibai, B.M. (TS = 98); Roberts, J.M. (TS = 64); Romero, R. (TS = 55); Nicolaides, K.H. (TS = 48); Martin, JN (TS = 32); Chaiworapongsa, T (TS = 30); Hassan, S.S. (TS = 29); Steegers EAP (TS = 28); Baker PN (TS = 27); Saade GR (TS = 27); Staff, A.C. (TS = 28); Dekker, G.A. (TS = 26); Erez O (TS = 26); Van Pampus MG (TS = 26); Nisell H (TS = 25); Karumanchi, S.A. (TS = 24); Redman CWG (TS = 24); Von Dadelszen P (TS = 24); Wang YP (TS = 24); and Franx A (TS = 22).

The number of articles generated by each region and the total number of citations each country has on the examined study area define the impact of the most productive regions. We select the top 20 document-producing areas in the preeclampsia field of research. The “United States” is the first dominant region (TS = 1200, TC = 49,692), and after that “Peoples R China” (TS = 311, TC = 3307) and “England” (TS = 262, TC = 12,342). Another region with a high number of publications is Turkey (TS = 232), followed by the Netherlands (TS = 196), Canada (TS = 162), Italy (TS = 152), Japan (TS = 149), Australia (TS = 145), Israel (TS = 131), Germany (TS = 130), Norway (TS = 101), Sweden (TS = 93), Brazil (TS = 91), India (TS = 80), Spain (TS = 79), South Korea (TS = 72), Iran (TS = Figure 3 displays a map of the study-based regions in red (highest) and green (lowest) colours.

The study includes 2359 institutions from various geographical areas. The top 20 organisations with the most publications are listed below. The impact of the most productive organisations in the preeclampsia discipline is determined by the total number of documents printed by each organisation and the total number of citations. The three most significant universities are the “University of Texas system” (TS = 108, TC = 3845), “Harvard University” (TS = 104, TC = 4124), and “The Pennsylvania Commonwealth System of Higher Education/PCSHE” (TS = 99, TC = 5616). Other institutions with the highest publications include, ‘The University of London’ (TS = 97, TC = 97), ‘The University of Pittsburgh’ (TS = 95, TC = 5463); ‘NIH USA’ (TS = 92, TC = 5949), ‘The University of Tennessee system’ (TS = 86, TC = 6219), ‘University of Tennessee health science center’ (TS = 84, TC = 6150), ‘NIH Eunice Kennedy Shriver national institute of child health human development NICHD’ (TS = 79, TC = 5448), ‘University of California system’ (TS = 78, TC = 4319); ‘Wayne State University’ (TS = 76, TC = 4518); ‘Magee Women’s research institute’ (TS = 69, TC = 4082), and ‘Kings College London’ (TS = 67, TC = 3426), ‘University of Oslo’ (TS = 59, TC = 2117); ‘Karolinska Institutet’ (TS = 57, TC = 1320), and ‘Erasmus university Rotterdam’ (TS = 54, TC = 1248); ‘The University of Cincinnati’ (TS = 52, TC = 3118), ‘The University of Groningen’ (TS = 52, TC = 1361), ‘King S College Hospital’ (TS = 51, TC = 2435), and ‘King S college hospital NHS foundation trust’ (TS = 51, TC = 2435).

This section introduces the 20 top Journals in order. The ‘AJOG’ is the most influential journal, with 41,991 total citations (TS = 622). The ‘Hypertension in Pregnancy’ (7247 citations, TS = 447), the ‘Journal of Maternal Fetal and Neonatal Medicine’ (3911 citations, TS = 297), the ‘Pregnancy hypertension an international journal of Womens cardiovascular health’ (1691 citations, TS = 280), the ‘Obstetrics and Gynecology’ (15,156 citations, TS = 267), the ‘Placenta’ (6038 citations, TS = 209), the ‘European journal of obstetrics gynecology and reproductive biology’ (3599 citations, TS = 152), the ‘Acta Obstetricia et Gynecologica Scandinavica’ (2763 citations, TS = 113), the ‘Reproductive sciences’ (1988 citations, TS = 113), the ‘Gynecologic and obstetric investigation’ (1948 citations, TS = 109), the ‘Archives of gynecology and obstetrics’ (1077 citations, TS = 88), the ‘American Journal of Perinatology’ (1029 citations, TS = 82), the ‘BMC Pregnancy and Childbirth’ (826 citations, TS = 79), the ‘Journal of Perinatal Medicine’ (1295 citations, TS = 79), the ‘Prenatal diagnosis’ (1377 citations, TS = 52), the ‘Clinical and Experimental Obstetrics Gynecology’ (277 citations, TS = 47), the ‘Fetal diagnosis and therapy’ (1159 citations, TS = 44), the ‘Journal of Reproductive Medicine’ (451 citations, TS = 43), the ‘British Journal of Obstetrics and Gynaecology’ (BJOJ) (3928 citations, TS = 41), the ‘Journal of the society for gynecologic investigation’ (1048 citations, TS = 40).

The most cited documents involved Roberts et al. (1989) (N = 1466); Khong et al. (1986) (N = 1247); Sacks et al. (1998) (N = 607) and Walsh (1985) (N = 546) respectively (Table 1). Also, the results found that 24 (out of 30 most cited) of the documents were clinical and research papers and 6 of the documents were literature reviews. About 18 articles were published in ‘AJOG’. Table 2.

One of the best bibliometrics methods is keyword analysis. The evolution of a scientific domain is discovered using the co-occurrence method (Zhu et al., 2019). The co-occurrence technique is reliable and useful for selecting the most beneficial themes over time (Wang et al., 2018). Figure 4 shows the five clusters that were created from the 60 keywords (minimum keywords, 10 times): cluster one (n = 18 items), cluster two (n = 16), cluster three (n = 13), cluster four (n = 7), and cluster five (n = 6 things). The material for each cluster is displayed in Table 3.

Topics that are expanding quickly in the field of preeclampsia were found by analyzing the frequency of keywords in subject categories. In Table 4, there are a few thematic groups with bursts and thorough details on the 25 thematic groups with the most powerful citation bursts. Preeclampsia, prostacyclin, endothelium, and thromboxane are identified by CiteSpace’s burst detection as the five topic areas with the most intense citation bursts. During a specific time, these topics were active research areas. Table 5 displays every colour section according to a timeline. A red line segment showing the beginning and finish of the burst duration is used to denote the length of a burst in a subject category. Pregnancy-induced hypertension, for instance, revealed a time of burst from 1992 to 2006 with a burst strength of 39.91 at the top of the list. The number of documents in the “pregnancy-induced hypertension” domain increased significantly between 1992 and 2006, indicating that preeclampsia research in this field was active at the time. Preeclampsia research has recently focused on topics including “cardiovascular disease,” “diagnosis,” “early onset,” “fetal growth restriction,” and “aspirin”.

Co-citation analysis is an effective technique that has gained widespread acceptance in several fields for accurately defining and visualising the intellectual structure of a study topic. In light of this, we decided to analyse the discipline’s structure using co-citation network analysis. Citespace software was used to investigate the preeclampsia discipline, which has its intellectual foundation in particular in the cited references. A network with 187 nodes and 598 edges was generated using document co-citation reference analysis in Citespace and the parameter settings: Slice length = 5; pruning: pathfinder; top N per slice: 30; top N%: 10%. (Figure 5). The LLR algorithm and title were used to cluster articles. Six clusters were ultimately procured, and Citespace gave them names automatically.

By using Carrot2, the clusters were deduced. To discover more about these clusters, the Carrot2 using the lingo algorithm was utilised on each cluster. The results showed that clusters #3 and #4 were the most recent clusters, while cluster #0 was the largest and oldest. Silhouette values of all clusters are bigger than 0.93. With 34 articles spread across 16 years, from 1985 to 2001, Cluster #0 is the largest cluster. Cluster #0 has a high degree of consistency, as evidenced by its Silhouette value of 0.936. Considering that Cluster #0 is the main cluster, its themes have been spread very widely. Carrot2 is capable of algorithmically managing the primary themes that are gleaned from the titles, keywords, and abstracts of cited documents (Table 5). The second-largest cluster, Cluster #1, contains 33 articles over the 10 years of 1985–1995 (Silhouette = 0.952). Cluster #3 is the most recent cluster (Silhouette = 0.992), and replicates significant events related to the risk of preeclampsia, placenta, sFlt-1, trimester, and growth restriction. Clusters #2, #4, and #5 all have silhouette values of 0.957, 0.949, and 0.935, respectively.