Burst Keywords Research Articles

Knowledge domain and emerging trends in diabetic cardiomyopathy: A scientometric review based on CiteSpace analysis.

ObjectiveTo review the literature related to diabetic cardiomyopathy (DCM), and investigate research hotspots and development trends of this field in the relevant studies based on CiteSpace software of text mining and visualization in scientific literature.MethodsThe relevant literature from the last 20 years was retrieved from the Web of Science (WoS) Core Collection database. After manual selection, each document record includes title, authors, year, organization, abstract, keywords, citation, descriptors, and identifiers. We imported the downloaded data into CiteSpace V (version 5.8.R2) to draw the knowledge map and conduct cooperative network analysis, cluster analysis, burst keyword analysis, and co-citation analysis.ResultsAfter manual screening, there were 3,547 relevant pieces of literature published in the last 18 years (from 2004 to 2021), including 2,935 articles and reviews, which contained 15,533 references, and the number was increasing year by year. The publications of DCM were dedicated by 778 authors of 512 institutions in 116 countries. The People's Republic of China dominated this field (1,117), followed by the USA (768) and Canada (176). In general, most articles were published with a focus on “oxidative stress,” “heart failure,” “diabetic cardiomyopathy,” “dysfunction,” “cardiomyopathy,” “expression,” “heart,” “mechanism,” and “insulin resistance.” Then, 10 main clusters were generated with a modularity Q of 0.6442 and a weighted mean silhouette of 0.8325 by the log-likelihood ratio (LLR) algorithm, including #0 heart failure, #1 perfused heart, #2 metabolic disease, #3 protective effect, #4 diabetic patient, #5 cardiac fibrosis, #6 vascular complication, #7 mitochondrial dynamics, #8 sarcoplasmic reticulum, and #9 zinc supplementation. The top five references with the strongest citation bursts include “Boudina and Abel”, “Jia et al.”, “Fang et al.”, “Poornima et al.”, and “Aneja et al.”.ConclusionThe global field of DCM has expanded in the last 20 years. The People's Republic of China contributes the most. However, there is little cooperation among authors and institutions. Overall, this bibliometric study identified the hotspots in DCM research, including “stress state,” “energy metabolism,” “autophagy,” “apoptosis,” “inflammation,” “fibrosis,” “PPAR,” etc. Thus, further research focuses on these topics that may be more helpful to identify, prevent DCM and improve prophylaxis strategies to bring benefit to patients in the near future.

Characteristics of nitrogen deposition research within grassland ecosystems globally and its insight from grassland microbial community changes in China.

As global change continues to intensify, the mode and rate of nitrogen input from the atmosphere to grassland ecosystems had changed dramatically. Firstly, we conducted a systematic analysis of the literature on the topic of nitrogen deposition impacts over the past 30 years using a bibliometric analysis. A systematic review of the global research status, publication patterns, research hotspots and important literature. We found a large number of publications in the Chinese region, and mainly focuses on the field of microorganisms. Secondly, we used a meta-analysis to focus on microbial changes using the Chinese grassland ecosystem as an example. The results show that the research on nitrogen deposition in grassland ecosystems shows an exponential development trend, and the authors and research institutions of the publications are mainly concentrated in China, North America, and Western Europe. The keyword clustering results showed 11 important themes labeled climate change, elevated CO2, species richness and diversity, etc. in these studies. The burst keyword analysis indicated that temperature sensitivity, microbial communities, etc. are the key research directions. The results of the meta-analysis found that nitrogen addition decreased soil microbial diversity, and different ecosystems may respond differently. Treatment time, nitrogen addition rate, external environmental conditions, and pH had major effects on microbial alpha diversity and biomass. The loss of microbial diversity and the reduction of biomass with nitrogen fertilizer addition will alter ecosystem functioning, with dramatic impacts on global climate change. The results of the study will help researchers to further understand the subject and have a deep understanding of research hotspots, which are of great value to future scientific research.

Research hotspots and emerging trends of deep learning applications in orthopedics: A bibliometric and visualized study.

BackgroundAs a research hotspot, deep learning has been continuously combined with various research fields in medicine. Recently, there is a growing amount of deep learning-based researches in orthopedics. This bibliometric analysis aimed to identify the hotspots of deep learning applications in orthopedics in recent years and infer future research trends.MethodsWe screened global publication on deep learning applications in orthopedics by accessing the Web of Science Core Collection. The articles and reviews were collected without language and time restrictions. Citespace was applied to conduct the bibliometric analysis of the publications.ResultsA total of 822 articles and reviews were finally retrieved. The analysis showed that the application of deep learning in orthopedics has great prospects for development based on the annual publications. The most prolific country is the USA, followed by China. University of California San Francisco, and Skeletal Radiology are the most prolific institution and journal, respectively. LeCun Y is the most frequently cited author, and Nature has the highest impact factor in the cited journals. The current hot keywords are convolutional neural network, classification, segmentation, diagnosis, image, fracture, and osteoarthritis. The burst keywords are risk factor, identification, localization, and surgery. The timeline viewer showed two recent research directions for bone tumors and osteoporosis.ConclusionPublications on deep learning applications in orthopedics have increased in recent years, with the USA being the most prolific. The current research mainly focused on classifying, diagnosing and risk predicting in osteoarthritis and fractures from medical images. Future research directions may put emphasis on reducing intraoperative risk, predicting the occurrence of postoperative complications, screening for osteoporosis, and identification and classification of bone tumors from conventional imaging.

Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on Autism Spectrum Disorder Neuroimaging.

Background Autism spectrum disorder (ASD) is a chronic developmental disability caused by differences in the brain. The gold standard for the diagnosis of this condition is based on behavioral science, but research on the application of neurological detection to diagnose the atypical nervous system of ASD is ongoing. ASD neuroimaging research involves the examination of the brain's structure, functional connections, and neurometabolic. However, limited medical resource and the unique heterogeneity of ASD have resulted in many challenges when neuroimaging is utilized. Objective This bibliometric study is aimed at summarizing themes and trends in research on autism spectrum disorder neuroimaging and at proposing potential directions for future inquiry. Methods Citations were downloaded from the Web of Science Core Collection database on neuroimaging published from January 1, 2012, to December 31, 2021. The retrieved information was analyzed using Bibliometric.com, CiteSpace.5.8. R3, and VOS viewer. Results A total of 1,363 papers were published across 58 regions. The United States was the leading source of publications. The League of European Research Universities published the largest number of articles (171). Burst keywords from 2018 to 2021 include identification and network. The clusters of references that continued into 2020 included graph theory, functional connectivity, and classification, which represent key research topics. Conclusions Imaging data is being used to identify neuro-network models with higher accuracy for ASD discrimination. Functional near-infrared imaging is advantageous compared to other neuroimaging. In the future, research on systematic and accurate computer-aided diagnosis technology should be encouraged. Moreover, the study of neuroimaging of ASD in different psychological and behavioral states can inspire new ideas about the diagnosis and intervention training of ASD and should be explored.

Research trends of the neuroimaging in aphasia: A bibliometric analysis and visualization analysis from 2004 to 2021

ObjectivesTo review the current research status of the neuroimaging of aphasia, and reveal the hotspots and frontiers of research in this field.MethodsWe searched articles related to the neuroimaging research on aphasia since Web of Science (WOS) database construction and extracted the data. CiteSpace and VOSviewer were used for the country/institution analysis, journal analysis, discipline analysis, burst keyword analysis and cited-reference cluster analysis.ResultsOf the studies retrieved from WOS, 2922 studies that related to the neuroimaging of aphasia were screened and finally included 2799 articles for research. The United States of America and University of California San Francisco were the main countries and institutions in this field. Brain had the highest impact factor in both published and cited journals. Through the discipline and topic analysis of this field, the most common category was Neurosciences and Neurology. The keyword with the strongest citation strength was “functional connectivity,” and the recent burst keywords were “functional connectivity” and “network.” The co-citation network showed seven clusters greater than 100. Among the top 5 clusters, the most recently formed cluster, Cluster #2 (progressive supranuclear palsy), had an average year of 2017. The literature in the top 5 clusters mainly focused on 3 aspects, specifically, the discovery of language processing models, injury and recovery mechanisms of post-stroke aphasia (PSA), and diagnosis of primary progressive aphasia (PPA) variants.ConclusionThe results of this bibliometric study revealed the following three research hotspots in the neuroimaging of aphasia: clarifying the connotation of the most recognized language processing model, the dual-stream model, exploring the injury mechanism based on the dual-stream model and the recovery mechanism involving the left and right hemispheres of PSA, and determining the diagnostic criteria for PPA variants. A major research trend is to combine new neuroimaging technology, such as PET tracer technology, to realize the visual presentation of disease-specific proteins to improve the pathological diagnostic criteria of PPA variants. Accordingly, a visualized analysis of literature that uses CiteSpace provides a more rapid, repeatable and flexible method, which is more conducive to capturing research hotspots and emerging trends.

Global Research on Cognitive Frailty: A Bibliometric and Visual Analysis of Papers Published during 2013–2021

This study analyzed the current status, hotspots, and emerging trends of global research on cognitive frailty, in order to provide new research ideas for researchers. Articles and reviews related to cognitive frailty, published from 2013 to 2021, were retrieved from the Web of Science Core Collection (WoSCC) database on 26 November 2021. CiteSpace 5.8.R3 was employed for data analyses. A total of 2077 publications were included. There has been a rapid growth of publications on cognitive frailty research since 2016. The United States, Italy, England, and Australia have been the leading research centers of cognitive frailty; however, China has also recently focused on this topic. The National Center for Geriatrics and Gerontology, and Shimada H. were found to be the most prolific institution and author, respectively. Co-citation analysis identified 16 clusters, of which the largest was cognitive frailty. The keywords which occurred most frequently were “older adult”, followed by “cognitive impairment”, “frailty”, “risk”, “dementia”, “prevalence”, “mortality”, “health”, and “Alzheimer’s disease”. Burst keyword detection revealed a rising interest in cognitive frailty models. By analyzing these publications from recent years, this study provides a comprehensive analysis of cognitive frailty research.

A Bibliometric and Knowledge-Map Analysis of Macrophage Polarization in Atherosclerosis From 2001 to 2021.

In recent years, studies of macrophage polarization in atherosclerosis have become an intense area of research. However, there are few bibliometric analyses regarding this area. In this review, we used CiteSpace 5.8.R3 and VOSviewer 1.6.16 software to perform text mining and knowledge-map analysis. We explored the development process, knowledge structure, research hotspots, and potential trends using a bibliometric and knowledge-map analysis to provide researchers with a macroscopic view of this field. The studies concerning macrophage polarization in atherosclerosis were downloaded from the Web of Science Core Collection. A total of 781 studies were identified and published by 954 institutions from 51 countries/regions. The number of studies of macrophage polarization in atherosclerosis increased over time. Arteriosclerosis Thrombosis and Vascular Biology published the highest number of articles and was the top co-cited journal. De Winther was the most prolific researcher, and Moore had the most co-citations. The author co-occurrence map illustrated that there was active cooperation among researchers. The most productive countries were the United States and China. Amsterdam University, Harvard University, and Maastricht University were the top three productive institutions in the research field. Keyword Co-occurrence, Clusters, and Burst analysis showed that “inflammation,” “monocyte,” “NF kappa B,” “mechanism,” and “foam cell” appeared with the highest frequency in studies. “Oxidative stress,” “coronary heart disease,” and “prevention” were the strongest citation burst keywords from 2019 to 2021.

Exercise for Stroke Rehabilitation: A Bibliometric Analysis of Global Research From 2001 to 2021.

ObjectiveTo make a bibliometric analysis of global trends in research into exercise interventions for stroke between 2001 and 2021.MethodThis study did the systematic literature from 2001 to 2021 in Web of Science Core Collection. CiteSpace software was used to analyze the relationship of publications with countries, journals, authors, references, and keywords.ResultsA total of 3,484 publications were obtained in the bibliometric analysis. The number of publications increased gradually over the period. The United States have the most number of publications. The journal stroke had the most citations per paper (106.95) and the highest impact factor (IF 2020, 7.194). The most high frequency keywords are “stroke,” “rehabilitation,” and “recovery,” the top of burst key words are “health,” “speed,” and “aerobic exercise”.ConclusionThese findings provide the trends of exercise for stroke s and provided the potential research frontiers in the past 20 years. It will be a useful basis for further research into focus issues, cooperators, development trends.

Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study.

BackgroundPatients with retinal diseases may exhibit serious complications that cause severe visual impairment owing to a lack of awareness of retinal diseases and limited medical resources. Understanding how artificial intelligence (AI) is used to make predictions and perform relevant analyses is a very active area of research on retinal diseases. In this study, the relevant Science Citation Index (SCI) literature on the AI of retinal diseases published from 2012 to 2021 was integrated and analyzed.ObjectiveThe aim of this study was to gain insights into the overall application of AI technology to the research of retinal diseases from set time and space dimensions.MethodsCitation data downloaded from the Web of Science Core Collection database for AI in retinal disease publications from January 1, 2012, to December 31, 2021, were considered for this analysis. Information retrieval was analyzed using the online analysis platforms of literature metrology: Bibliometrc, CiteSpace V, and VOSviewer.ResultsA total of 197 institutions from 86 countries contributed to relevant publications; China had the largest number and researchers from University College London had the highest H-index. The reference clusters of SCI papers were clustered into 12 categories. “Deep learning” was the cluster with the widest range of cocited references. The burst keywords represented the research frontiers in 2018-2021, which were “eye disease” and “enhancement.”ConclusionsThis study provides a systematic analysis method on the literature regarding AI in retinal diseases. Bibliometric analysis enabled obtaining results that were objective and comprehensive. In the future, high-quality retinal image–forming AI technology with strong stability and clinical applicability will continue to be encouraged.

Knowledge Mapping of Olfactory Dysfunction: A Bibliometric Study.

BackgroundOlfaction is one of the five basic senses of human beings. As such, olfactory dysfunction seriously affects patients' quality of life and can even endanger them. In recent years, olfactory dysfunction has attracted greater research interest, and numerous studies have been published on olfactory dysfunction. However, there are few studies on olfactory dysfunction through bibliometric analysis. This study aims to describe the current situation and identify the foci and potential new research directions of olfactory dysfunction using a bibliometric approach.MethodsArticles related to olfactory dysfunction published from 2002 to 2021 were located in the Web of Science Core Collection of Clarivate Analytics (London, UK). Bibliometric analyses were conducted with the CiteSpace (Chaomei Chen, Drexel University, Philadelphia, PA, USA) and VOSviewer (Center for Science and Technology Studies, Leiden University, Leiden, Netherlands) software programs.ResultsThe number of articles published each year showed an upward trend, especially in 2020, where a sharp increase had occurred due to the coronavirus disease 2019 (COVID-19) pandemic. The United States was the country with the most publications and the strongest international cooperation. In terms of institutions, the greatest number of publications from a single institution came from Dresden University of Technology. Thomas Hummel was the author who had contributed the most articles. An analysis of co-citation networks and burst keywords in the field revealed a shift from “gonadotropin-releasing hormone” and “apoptosis” earlier on to “olfactory training,” “COVID-19,” and “Parkinson's disease” more recently. “Outcome,” “COVID-19,” “infection,” and “pathogenesis” are topics of the research frontier and hotspots.ConclusionMore attention has been paid to olfactory dysfunction as the understanding of it has improved in the past 20 years. This study provides researchers with an objective, systematic, and comprehensive analysis of the literature on olfactory dysfunction. The current frontier areas and hotspots in the field focus on the pathological mechanisms of olfactory dysfunction after infection with COVID-19 and its different prognoses. The pathophysiological mechanism of olfactory dysfunction in neurodegenerative diseases and COVID-19 will be a primary future research direction.

Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on the Application of Artificial Intelligence in Ophthalmic Disease Diagnosis.

Background: Artificial intelligence (AI) has been used in the research of ophthalmic disease diagnosis, and it may have an impact on medical and ophthalmic practice in the future. This study explores the general application and research frontier of artificial intelligence in ophthalmic disease detection. Methods: Citation data were downloaded from the Web of Science Core Collection database to evaluate the extent of the application of Artificial intelligence in ophthalmic disease diagnosis in publications from 1 January 2012, to 31 December 2021. This information was analyzed using CiteSpace.5.8. R3 and Vosviewer. Results: A total of 1,498 publications from 95 areas were examined, of which the United States was determined to be the most influential country in this research field. The largest cluster labeled “Brownian motion” was used prior to the application of AI for ophthalmic diagnosis from 2007 to 2017, and was an active topic during this period. The burst keywords in the period from 2020 to 2021 were system, disease, and model. Conclusion: The focus of artificial intelligence research in ophthalmic disease diagnosis has transitioned from the development of AI algorithms and the analysis of abnormal eye physiological structure to the investigation of more mature ophthalmic disease diagnosis systems. However, there is a need for further studies in ophthalmology and computer engineering.

Systematic Bibliometric Analysis of Research Hotspots and Trends on the Application of Virtual Reality in Nursing

BackgroundWith the emergence of the metaverse, virtual reality, as a digital technology, must be getting hotter. High quality virtual reality related nursing knowledge scene learning is gradually replacing traditional education and intervention skills.ObjectiveThis systematic study aimed to gain insights into the overall application of virtual reality technology in the study of nursing.MethodsCitations downloaded from the Web of Science Core Collection database for use in VR in nursing publications published from January 1, 2012, to December 31, 2021, were considered in the research. Information retrieval was analyzed using https://bibliometric.com/app, CiteSpace.5.8. R3, and VOS viewer.ResultsA total of 408 institutions from 95 areas contributed to relevant publications, of which the United States is the most influential country in this research field. The clustering labels of cited documents were obtained from the citing documents. Virtual simulation, virtual learning, clinical skills, and dementia are the clustering labels of co-cited documents. The burst keywords represented the research frontiers in 2020–2021, which were knowledge and simulation.ConclusionVirtual nursing has had an impact on both nurses and clients. With the emergence of the concept of the metaverse, the research and application of virtual reality technology in nursing will gradually increase.

Research Trends and Hotspots on Herpes Zoster: A 10-Year Bibliometric Analysis (2012-2021).

PurposeHerpes zoster infection, with its considerable burden to individuals and society, remains a challenge around the world. However, to the knowledge of the authors, little bibliometric quantitative or qualitative analysis has been carried out to evaluate herpes zoster research. This study aimed to use a bibliometric analysis to evaluate current publication trends and hotspots on herpes zoster research worldwide, in order to advance research in this field.MethodsRelevant publications from January 2012 to December 2021 were collected from the Web of Science Core Collection database. Citespace (V5.8.R3) was used to analyze the research points, including publication countries, institutions and authors, cited author, cited reference and their clustering, and keyword co-occurrence, and burst keyword to acquire research trends and hotspots.ResultsA total of 9,259 publications were obtained, with a steady increase in the number of annual publications during the decade. Articles were the main type of publication. The United States is the leading country in this research, and the University of Colorado has the highest influence in this field. Oxman is the most representative author, with a main research interest in herpes zoster vaccines. The top five cited authors' publications focused on herpes zoster vaccines, molecular mechanisms, and postherpetic neuralgia. A co-citation map resulted 19 main clusters, and revealed that vaccines, postherpetic neuralgia, treatments, varicella zoster virus and its mechanisms, and epidemiology of herpes zoster were the current research focus after clustering co-cited publications. Human herpesviruses, antiviral prophylaxis, rheumatoid arthritis, recombinant zoster vaccine, varicella vaccination and postherpetic neuralgia were the top clusters after co-occurrence keywords analysis. Moreover, burst keywords detection showed that the subunit vaccine was the new hotspot in the field of herpes zoster.ConclusionThis bibliometric study defined the overall prospects in the field of herpes zoster and provided valuable instruction for the ongoing research. The keyword “subunit vaccine” indicated that a vaccine for herpes zoster prevention was the hotspot. Efforts to prevent varicella zoster virus infection will be essential to improve herpes zoster outcomes.

Bibliometric and Visualized Analysis of 2011-2020 Publications on Physical Activity Therapy for Diabetes.

BackgroundThis study was designed to investigate the global emerging trends of physical activity therapy for diabetes based on a bibliometric analysis of the publications.MethodsPublication papers from 2011 to 2020 were retrieved from the database of “Web of Science Core Collection” with the topic search. A number of papers, citations, authors, countries, institutions, and references were extracted. CiteSpace was used to analyze co-citation on authors, collaborations between countries and institutions, and detect the emerging trends of burst keywords and references.ResultsA total of 2651 publications were recruited in this study and showed an upward trend of annual publications. Diabetes obesity & metabolism (journal), the United States (country), Harvard University (institution), and Kaku K (author) published the most papers in this research field. “Impaired glucose tolerance” (2011–2012) was the highest strength burst keyword, while “cardiovascular outcome” (2017–2020) was the most burst keyword in the last 5 years. Moreover, “Standards of medical care in diabetes – 2014” was the strongest burst reference.Conclusion“Physical activity therapy for diabetes” has been accepted remarkably over the last 10 years. The keywords of “impaired glucose tolerance,” “Cardiovascular outcome,” “improves glycemic control,” “Self-management,” and exercise type including “Aerobic exercise, muscle strength” may be the latest research frontiers.

Research hotspots and emerging trends of automated peritoneal dialysis: A bibliometric analysis from 2000 to 2020.

The implementation of automated peritoneal dialysis (APD) has considerably increased in many countries. We conducted a bibliometric analysis to evaluate the accumulating studies on APD in the last two decades quantitatively and qualitatively. Publications regarding APD research between 2000 and 2020 were retrieved from the Web of Science Core Collection database by using the index term "automated peritoneal dialysis." CiteSpace, VOSviewer, and an online platform were employed to analyze the number of publications and the collaboration relationships between countries, institutions, authors, and co-cited journals. Cluster analysis and burst keywords detection were performed on co-cited references and keywords, respectively. We obtained a record of 545 publications related to APD in total. The United States was the country that contributes most, and Baxter Healthcare Corporation was the leading institution. Peritoneal Dialysis International was the most active journals in this field. Claudio Ranco was the most productive author, and Simon J Davies ranked the first in the cited authors. Co-cited reference cluster analysis and high frequency keywords showed that survival, ultrafiltration and peritonitis are continuous hot topics. While remote monitoring (RM) and telemedicine may be APD research frontiers according to burst keywords detection. This bibliometric study provides comprehensive overview on the publications of APD over the past two decades. These findings help to identify the hotspots and explore new directions for future research. RM has become an emerging trend in APD field.

Global Research Trends in Gestational Diabetes Mellitus from 2000 to 2020: A Bibliometric Study.

This study analyzed major trends and topics in the field of gestational diabetes mellitus research between 2000 and 2020. Studies that investigated gestational diabetes mellitus published between 2000 and 2020 were retrieved from the Web of Science Core Collection database. Data from the identified studies were analyzed using CiteSpace software. A total of 22,713 publications were retrieved, among which 21,722 publications were included in this scientometric analysis. Clustering analysis revealed 13 themes across all fields. Physical activity is an emerging trend. Co-word analysis showed that subject high-frequency keywords were: risk factor, obesity, insulin resistance, prevalence, and association. Centrality indices identified the most influential keywords to be: body mass index, risk factors, gestational weight gain, and obesity. Burst keywords revealed that there were six research frontier subtopics: i) prediction of adverse neonatal outcomes in gestational diabetes mellitus; ii) postpartum period research - blood glucose levels and insulin resistance; iii) meta-analysis - understanding the best evidence in pregnancy gestational diabetes mellitus; iv) gene expression profiles and DNA methylation in gestational diabetes mellitus; v) biomarkers for predicting higher birth and children weights; and vi) discussion on diagnostic criteria for gestational diabetes mellitus classification. The number of studies on gestational diabetes mellitus is increasing. For two decades, the United States has been the global leader in the number of published studies. Studies on gestational diabetes mellitus are mainly from developed countries, with a few of them being from developing countries. An emerging field of research aims at elucidating the association between physical activity and gestational diabetes mellitus.

Developments in Congenital Scoliosis and Related Research from 1992 to 2021: A Thirty-Year Bibliometric Analysis

Many studies, mainly original articles and reviews, have been reported on congenital scoliosis (CS), but there is a lack of bibliometric analyses. This study aimed to systematically analyze the developments and focuses in CS and related research fields. Data were retrieved from the Web of Science Core Collection database, and the top 100 most-cited studies were analyzed emphatically. The Web of Science Results Analysis and Citation Report was used to analyze different aspects of the literature. CiteSpace was used to analyze the cooperation network, reference co-citation, burst keywords, and burst citations. The final analysis included 749 studies. CS and related research has been rapidly expanding. Several journals have published relevant studies and most-cited studies on this topic. Cooperation was noted among authors, institutions, and countries/regions in multiple instances. Surgical techniques (hemivertebra resection/posterior vertebral column resection/vertical expandable prosthetic titanium rib/double approach/grade 4 osteotomy) was one of the most common research focuses. In addition, research on genetics and molecular biology related to CS has become an emerging trend as a result of advances in basic science. Over time, research on CS and in related fields has gained greater attention and has been expanding continuously, showing a trend toward globalization. We recommend that researchers focus on the progress of surgical techniques, advances in molecular biology and genetics, and characteristics of CS. The top clusters, most-cited articles, and references with the strongest burst citations should be studied further.

International Publication Trends in Low Back Pain Research: A Bibliometric and Visualization Analysis

BackgroundAlthough there is a growing research base on low back pain, the bibliometric literature related to it is deficient. The aim of this study was to conduct a bibliometric and visualization analysis of low back pain and to provide a broad view of the current trends in LBP research and a potential guide in this discipline.MethodsThe authors searched the Web of Science to extract publications regarding low back pain, and found a total of 12,249 publications during a period of 22 years, among which 12,242 were eligible. We classified and analyzed publications such as total citations, average citations per item, H-index, research types, countries/regions, institutions, and journals using standard bibliometric indicators. Bibliometric approaches (VOSviewer1.6.13 and CiteSpace 5.8.3) were also available for gathering information and explore the trends of research.ResultsConspicuously, over the past 22 years, an increasing number of scholars have specialized in the research of LBP, exerting the boom in articles. The largest number of document type was that of articles. Under modern conditions, regional distinction existed in the research of low back pain and developed countries preceded others. Research individuals and institutions were preoccupied by respective aspects. Visualization analysis provided objective information for potential collaborators and cooperative institutions. Furthermore, most burst keywords varied during different periods.ConclusionsThe map of research on LBP obtained by our analysis is expected to help researchers to efficiently and effectively explore LBP.

Visualization and Analysis of Mapping Knowledge Domain of Heterogeneous Traffic Flow.

Mapping knowledge domain (MKD) is an important application in bibliometrics, which is a method of visually presenting and explaining newly developed interdisciplinary scientific fields using data mining, information analysis, scientific measurement, and graphic rendering. This study combines applied mathematics, visual analysis technology, information science, and scientometrics to systematically analyze the development status, research distribution, and future trend of the heterogeneous traffic flow by using the MKD software tools VOSviewer and CiteSpace. Based on the MKD and Bibliometrics approaches, 4709 articles have been studied, which were published by Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) from 2004 to 2021 in the field of heterogeneous traffic flows. Firstly, this paper presents the annual numbers of articles, origin countries, main research organizations, and groups as well as the source journals on heterogeneous traffic flow studies. Then, cocitation analysis is used to divide heterogeneous traffic flow into three main research directions, which include “heterogeneous traffic flow model,” “traffic flow capacity analysis,” and “traffic flow stability analysis.” The keyword cooccurrence analysis is applied to identify five dominant clusters: “modeling and optimization methods,” “traffic flow characteristics analysis,” “driving behavior analysis,” “simulation experiment,” and “policies and barriers.” Finally, burst keywords were studied according to the publication date to present more clearly the change of research focus and direction over time.

Thyroid Diseases During Pregnancy: Bibliometric Analysis of Scientific Publications.

Bibliometric analysis can analyze development trends and predict research hotspots. We used these analyses to better understand the pregnancy-related implications of thyroid diseases. Publications on thyroid diseases during pregnancy from 1926 to hitherto were retrieved based on the Web of Science database. The publications and references, the institutions and countries, the journals, the keywords and citations were analyzed by utilizing VOSviewer, CiteSpace and Cit- NetExplorer. A total of 3310 publications were retrieved and were cited 87913 times. The United States took the dominant position in outputs and collaborations. Harvard University had the most articles 86, which also had the highest h-index 30. Thyroid ranked first with 201 publications and Journal of Clinical Endocrinology Metabolism had the highest h-index 67. Among the 49 burst keywords, "antibody" had the longest burst period from 1991 to 2012, "thyroxine" had the strongest burst strength 16.7026, "hypothyroxinemia" appeared most recently in 2018. The most frequent keyword was "pregnancy" which occurred 1324 times. All the top 98 frequent keywords were clustered into 4 clusters. The citation network visualization was grouped into 8 groups. The research focus of thyroid diseases in pregnancy ranged from clinical thyroid dysfunction to milder thyroid dysfunction. Guidelines published by the American Thyroid Association enacted a crucial purpose in the treatment and development of thyroid diseases during pregnancy. Some randomized controlled studies of unresolved problems and long-term follow-up of offspring may be the direction of future research. In the meantime, bibliometric methods can help scholars choose journals, track research hotspots, and identify the direction or focus of future research.