Bibliometric Analysis of Research on the Comorbidity of Pain and Inflammation

Objectives. To provide a comprehensive review on the global scientific research status of comorbid pain and inflammation from 1981 to 2019 and capture its subsequent development trends. Data Sources. The primary database chosen to collect publications on comorbid pain and inflammation research from 1981 to 2019 was the Web of Science (WOS). Core of the search strategy was the key word “pain” and the key word “inflammation” in the medical subject headings’ major field. Study Selection. All articles retrieved were included in the bibliometric analysis. Data Extraction. We used CiteSpace to analyze publication outputs, subject categories, distribution by country/institution/journal, and other types of information. Then, knowledge base, hot issues, and future development directions were explained. Data Synthesis. A total of 2887 papers met the inclusion criteria in our research. Linear regression analysis results showed that the publications of studies of comorbid pain and inflammation significantly increased ( P < 0.001 ) and have grown about 192 times in 40 years. The countries with the most outputs were the USA (886 publications), China (375 publications), and England (236 publications). Besides, Harvard University was the most prolific institution with 730 publications and 6646 citations. In accordance with the subject categories of WOS, neurosciences (31.832%), pharmacology/pharmacy (18.427%), and clinical neurology (15.206%) were the main research areas of these 2887 papers. Conclusions. The current study reveals that research on comorbid pain and inflammation has gradually become more extensive worldwide since 1981, and neuropathic pain was the most popular study type. Most of our research output in this field came from countries in Europe and North America, although some Asian countries showed promising performance.

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Research Contributions of CCS Haryana Agricultural University, Hisar : A Bibliometric Analysis

DESIDOC Journal of Library & Information Technology ◽

10.14429/djlit.38.5.13188 ◽

2018 ◽

Vol 38 (5) ◽

pp. 334

Author(s):

Anil Kumar Siwach ◽

Seema Parmar

Keyword(s):

Bibliometric Analysis ◽

Research Output ◽

International Level ◽

Publication Trends ◽

Major Subject ◽

Subject Categories ◽

International Collaborations ◽

Prolific Authors ◽

Fourth Position ◽

Highly Cited

<span>CCS Haryana Agricultural University (CCSHAU) is among the top ten agricultural universities of India according to ICAR ranking 2016-17. The present study has been undertaken to find out the publication trends in this university during 2001-2015. The study mainly focus on year-wise research output, major subject categories, national and international collaborations, top journals for publications, most prolific authors, citations pattern and highly cited papers of CCSHAU. The results indicate that among the top ten agricultural universities of India, CCSHAU stands at fourth position in terms of publications and sixth position in terms of citations. It has collaborated with many institutions at national and international level in its research publications.</span>

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Bibliometric Analysis on the Comorbidity of Anxiety and Pain

10.21203/rs.3.rs-37237/v1 ◽

2020 ◽

Author(s):

Cheng-Cheng Wu ◽

Hao-Yu Hu ◽

Xue-Qiang Wang

Keyword(s):

Bibliometric Analysis ◽

Dental Anxiety ◽

Linear Regression Analysis ◽

The United States ◽

Future Research ◽

Clinical Neurology ◽

Bibliometric Method ◽

Pain Research ◽

General Aspects ◽

Research Frontiers

Abstract Background: Pain is commonly associated with psychological variables, such as anxiety and depression. However, only a few studies statistically analyzed the global trends and conducted a review through the bibliometric method. Purpose: This work aimed to analyze the general aspects of scientific studies worldwide on the comorbid of anxiety and pain research between 2000 and 2019. Methods: Published papers on the comorbid of anxiety and pain from the last 2 decades were retrieved from the Web of Science core collection. To assess whether the percentage statistically decreased or increased over time by using IBM SPSS Statistics 22.0. Results: A total of 1,329 papers met the inclusion criteria. The trend of annual publications presented a significant growth from 2000 to 2019 (P<0.001) by linear regression analysis. Clinical Neurology, Neurosciences, and Anesthesiology of subject categories had superior quality and were recognized as mainstream on comorbid anxiety and pain research. The United States (416, 30.85%) and the University of Washington (23, 1.73%) were the most prolific and high-quality country and institution, respectively. Postoperative pain (11.81%) and headache (11.14%) were the hottest topic among researchers. Music, distraction, adult, dental anxiety, and preoperative anxiety were emerging hotspots and could be regarded as research frontiers. Conclusions: Bibliometric analysis of the comorbidity of anxiety and pain and provides insights into research countries, institutions, authors, and core journal, visual, hot topics, overall tendency, and research frontiers that will aid in exploring hidden valuable field for future research.

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Exploring the knowledge domain of earthquake prediction based on bibliometric analysis and text mining

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-212442 ◽

2021 ◽

pp. 1-17

Author(s):

Xiaorong He

Keyword(s):

Text Mining ◽

Bibliometric Analysis ◽

Earthquake Prediction ◽

Citation Index ◽

Knowledge Domain ◽

Scientific Publications ◽

Main Research ◽

Detection Techniques ◽

Subject Categories ◽

Earthquake Research

Earthquake prediction is one of the important themes of earthquake research, and it is also a very difficult scientific problem in the world. In this study, a bibliometric analysis is conducted on the scientific publications about earthquake prediction indexed in SCIE (Science Citation Index Expanded) and SSCI (Social Sciences Citation Index) databases during the past two decades (1998–2017). The subject categories, annual and journal distributions, leading countries/regions and institutions are investigated in this field. The main research topics are identified through text mining method. The research trends are explored by keyword co-occurrence analysis and bursting keywords detection techniques. The results of this study are helpful for scholars in this field to find the knowledge structure and important participants. It is also helpful for scholars to seize the current research hotspots and future development trends in this field.

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Geriatric Research in Saudi Arabia: A Bibliometric Analysis

Journal of Advances in Medicine and Medical Research ◽

10.9734/jammr/2019/v31i1230336 ◽

2020 ◽

pp. 1-9

Author(s):

Sultan H. Alamri

Keyword(s):

Saudi Arabia ◽

Bibliometric Analysis ◽

Research Output ◽

Psychosocial Health ◽

Maximum Efficiency ◽

Medical Subject Headings ◽

High Quality Research ◽

Cross Sectional ◽

Mesh Terms ◽

Geriatric Research

Background: This bibliometric analysis was performed to assess the research trends and productivity from Saudi Arabia in the field of geriatrics. Methods: In this descriptive study, we collected bibliometric data for manuscripts published from Saudi Arabia between the year 1980 to June 2018. Data were retrieved from PubMed; Embase; MEDLINE; CINAHL and Google Scholar using the Medical Subject Headings (MeSH) terms: “Saudi”, “Elder”, “Older”, “Gerontology”, “Seniors”, “Senility” “Geriatric” and “Ageing”. The number of published papers overall and citations per paper were also collected. Results: From the publications analyzed between the year 1980 to June 2018, 91% of the articles were published between the years 2000 -2018, indicating the major contribution from Saudi Arabia in the field of geriatric research has been in the recent 20 years. In total, 34 publications were retrieved, of which, 85% were cross-sectional studies, with 66% of the studies carried out in hospitals or primary health care centers. The sub-topics with maximum number of publications included mental health, musculoskeletal health, and socio-gerontology. The most cited publications were related to the topics of depression, psychosocial health and osteoporosis. Conclusions: Despite the recent increase in geriatric research in Saudi Arabia, the research output and quality of publications were low and did not address commonly seen geriatrics health conditions such as dementia, delirium and polypharmacy. More high quality research directed to address common geriatrics conditions is needed to better inform decision making. Building research capacities, enhancement of infrastructure, and provision of adequate support from funding bodies are required interventions to enable geriatric research in Saudi Arabia to operate at a maximum efficiency.

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Bibliometric Analysis of Research on the Comorbidity of Cancer and Pain (Preprint)

10.2196/preprints.19259 ◽

2020 ◽

Author(s):

Cheng-Cheng Wu ◽

Yi-Zu Wang ◽

Hao-Yu Hu ◽

Xue-Qiang Wang

Keyword(s):

Quantitative Research ◽

Linear Regression Analysis ◽

The United States ◽

Clinical Neurology ◽

Common Symptom ◽

Systematic Analysis ◽

Republic Of China ◽

Clinical Observations ◽

Subject Categories ◽

High Prevalence

BACKGROUND Pain is the most common symptom in patients with neoplasm. It is a distressing experience that seriously that destructs the quality of life of patients, with a high prevalence in clinical observations. However, only few studies have applied bibliometric methods to analyze systematic works on the comorbidity of cancer and pain. OBJECTIVE This work aimed to conduct a systematic analysis of the scientific studies worldwide on the comorbidity of cancer and pain in 2010–2019. METHODS The Web of Science databases were searched for publications related to the comorbidity of cancer and pain from 2010 to 2019. RESULTS A total of 3,423 papers met the inclusion criteria in this research. The increase in the quantity of papers presented a significant growth from 2010 to 2019 (P<0.001) by linear regression analysis. The research subject categories of the 3,423 papers mainly concentrated on oncology (28.57%), clinical neurology (25.62%), and healthcare science services (15.89%). The United States had the highest number of published papers, followed by the People’s Republic of China and England. According to scientific statistics, breast cancer (20.36%) was by far the most predominant topic in the papers related to the comorbidity of cancer and pain. CONCLUSIONS This bibliometric research provided a framework for visual and quantitative research to management scholars in favor of exploring potential field related to hot issue and research frontiers.

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Bibliometric study of the global scientific research on pain and disability

10.21203/rs.3.rs-18653/v1 ◽

2020 ◽

Author(s):

Lin-Man Weng ◽

Yi-Li Zheng ◽

Meng-Si Peng ◽

Juan Wang ◽

Rui Wang ◽

...

Keyword(s):

Linear Regression ◽

Linear Regression Analysis ◽

Scientific Research ◽

Research Trend ◽

Future Research ◽

Clinical Neurology ◽

Maximum Output ◽

Microsoft Excel ◽

Evolution And Development ◽

Subject Categories

Abstract Background A growing number of relevant studies on the comorbidity of pain and disability have been published in high-quality journals; however, few studies have analysed quantitatively the characteristics of the topic via bibliometrics. Purpose The study aims to systematically analyze various aspects of global scientific research on pain and disability comorbidity from 1980 to 2019 and determine the global research trend and knowledge structure. Methods A collection of publications on pain and disability comorbidity between 1980 and 2019 was retrieved from the Web of Science Core Collection. CiteSpace, Microsoft Excel 2016, and IBM SPSS Statistics 25 software were used to analyze publication outputs, authors, journals, institutions, countries, subject category, types of pain, references, and keywords. Results We collected a total of 3,570 articles in March 9, 2019. Results indicated that the publication outputs had a significant growth in the recent 40 years via the linear regression model (P<0.001). The journal Pain had the maximum output (178), the most cited frequencies in WoS (15,418), the highest impact factor index in 2017 (5.559), and the highest H-index (68). Linear regression analysis revealed that the tendency of multiple authors’ papers increased significantly (t=8.065, P<0.001). In accordance with the top 20 subject categories, Clinical Neurology was the most productive academic area (1095). With regard to types of pain, low back pain and headache were the most widely concerned with a total of 1,114 publications.Conclusion The study outlines the evolution and development of comorbid pain and disability research, reflects the overall situation and lays the groundwork for future research.

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Questions to the Article of research output and international cooperation among countries during the COVID-19 pandemic (Preprint)

10.2196/preprints.26576 ◽

2020 ◽

Author(s):

Shu-Chun Kuo ◽

Tsair-Wei Chien ◽

Willy Chou

Keyword(s):

Citation Analysis ◽

International Cooperation ◽

Web Of Science ◽

Research Output ◽

Visual Representations ◽

Scientometric Analysis ◽

Medical Subject Headings ◽

Pubmed Central ◽

The Us ◽

Circle Diagram

UNSTRUCTURED We read with great interest the study by Grammes et al. on research output and international cooperation among countries during the COVID-19 pandemic. The paper is a quantitative study using scientometric analysis instead of a qualitative research using citation analysis. A total of 7,185 publications were extracted from Web of Science Core Collection (WoS) with keywords of “covid19 OR covid-19 OR sarscov2 OR sars-cov-2” as of July 4, 2020. We replicated a citation analysis study to extract abstracts from Pubmed Central(PMC) with similar keywords mentioned above and obtained 35,421 articles relevant to COVID-10 matching their corresponding number of citation in PMC. one hundred top-cited atricles were selected and compared on diagrams. Social network analysis combined with citation numbers in articles was performed to analyze international cooperation among countries. The results were shown on a world map instead of the circle diagram in the previous study. A Sankey diagram was applied to highlight entities(e.g., countries, article types, medical subject headings, and journals) with the most citations. Authors from Chian dominated citations in these 100 top-cited articles rather than the US in publications addressed in the previous study. Both visual representations of the world map and Sankey diagram were provided to readers with a better understanding of the research output and international cooperation among countries during the COVID-19 pandemic

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What is the risk of prostate cancer mortality following negative systematic TRUS-guided biopsies? A systematic review

BMJ Open ◽

10.1136/bmjopen-2020-040965 ◽

2020 ◽

Vol 10 (12) ◽

pp. e040965

Author(s):

Sandra Miriam Kawa ◽

Signe Benzon Larsen ◽

John Thomas Helgstrand ◽

Peter Iversen ◽

Klaus Brasso ◽

...

Keyword(s):

Prostate Cancer ◽

Systematic Review ◽

Data Extraction ◽

Specific Antigen ◽

Transrectal Ultrasound ◽

Population Based ◽

Free Text ◽

Medical Subject Headings ◽

Prognostic Information ◽

Prostate Biopsies

ObjectiveTo investigate the risk of prostate cancer-specific mortality (PCSM) following initial negative systematic transrectal ultrasound-guided (TRUS) prostate biopsies.DesignSystematic review.Data sourcesPubMed and Embase were searched using a string combination with keywords/Medical Subject Headings terms and free text in the search builder. Date of search was 13 April 2020.Study selectionStudies addressing PCSM following initial negative TRUS biopsies. Randomised controlled trials and population-based studies including men with initial negative TRUS biopsies reported in English from 1990 until present were included.Data extractionData extraction was done using a predefined form by two authors independently and compared with confirm data; risk of bias was assessed using the Newcastle–Ottawa Scale for cohort studies when applicable.ResultsFour eligible studies were identified. Outcomes were reported differently in the studies as both cumulative incidence and Kaplan-Meier estimates have been used. Regardless of the study differences, all studies reported low estimated incidence of PCSM of 1.8%–5.2% in men with negative TRUS biopsies during the following 10–20 years. Main limitation in all studies was limited follow-up.ConclusionOnly a few studies have investigated the risk of PCSM following initial negative biopsies and all studies included patients before the era of MRI of the prostate. However, the studies point to the fact that the risk of PCSM is low following initial negative TRUS biopsies, and that the level of prostate-specific antigen before biopsies holds prognostic information. This may be considered when advising patients about the need for further diagnostic evaluation.PROSPERO registration numberCRD42019134548.

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SARS-COV-2: SIR Model Limitations and Predictive Constraints

Symmetry ◽

10.3390/sym13040676 ◽

2021 ◽

Vol 13 (4) ◽

pp. 676

Author(s):

Charles Roberto Telles ◽

Henrique Lopes ◽

Diogo Franco

Keyword(s):

Time Series Data ◽

Data Extraction ◽

Sir Model ◽

Series Data ◽

Atmospheric Conditions ◽

Main Research ◽

Outdoor Spaces ◽

Model Equations ◽

Physical Features ◽

Indoor And Outdoor

Background: The main purpose of this research is to describe the mathematical asymmetric patterns of susceptible, infectious, or recovered (SIR) model equation application in the light of coronavirus disease 2019 (COVID-19) skewness patterns worldwide. Methods: The research modeled severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) spreading and dissemination patterns sensitivity by redesigning time series data extraction of daily new cases in terms of deviation consistency concerning variables that sustain COVID-19 transmission. The approach opened a new scenario where seasonality forcing behavior was introduced to understand SARS-COV-2 non-linear dynamics due to heterogeneity and confounding epidemics scenarios. Results: The main research results are the elucidation of three birth- and death-forced seasonality persistence phases that can explain COVID-19 skew patterns worldwide. They are presented in the following order: (1) the environmental variables (Earth seasons and atmospheric conditions); (2) health policies and adult learning education (HPALE) interventions; (3) urban spaces (local indoor and outdoor spaces for transit and social-cultural interactions, public or private, with natural physical features (river, lake, terrain). Conclusions: Three forced seasonality phases (positive to negative skew) phases were pointed out as a theoretical framework to explain uncertainty found in the predictive SIR model equations that might diverge in outcomes expected to express the disease’s behaviour.

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