| Literature DB >> 34414977 |
Bonhyuk Goo1, Ha-Na Kim2, Jung-Hyun Kim1, Sang-Soo Nam3.
Abstract
BACKGROUND: There are various treatments for facial nerve palsy, and research into this topic is ongoing. In the present study, we carried out bibliometric and visualized analyses to identify the trends of research into facial nerve palsy treatment.Entities:
Mesh:
Year: 2021 PMID: 34414977 PMCID: PMC8376370 DOI: 10.1097/MD.0000000000026984
Source DB: PubMed Journal: Medicine (Baltimore) ISSN: 0025-7974 Impact factor: 1.817
Figure 1Annual publication trend of research into facial nerve palsy treatment in Search 1, conducted from inception to December 27, 2020.
Figure 2Annual publication trend of research into facial nerve palsy treatment in Search 2, conducted from inception to December 27, 2020.
Most common subject areas and journals in Search 1.
| Rank | Subject Area | Articles (n), % of All Articles (1609) | Rank | Journal Title | Articles (n), % of all articles (1609) |
| 1 | Medicine | n = 1522, 77.6% | 1 |
| n = 48, 3.0% |
| 2 | Neuroscience | n = 143, 7.3% | 2 |
| n = 43, 2.7% |
| 3 | Biochemistry, Genetics and Molecular Biology | n = 56, 2.9% | 3 |
| n = 40, 2.5% |
| 4 | Health Professions | n = 51, 2.6% | 4 |
| n = 37, 2.3% |
| 5 | Dentistry | n = 48, 2.4% | 5 |
| n = 33, 2.1% |
| 6 | Pharmacology, Toxicology and Pharmaceutics | n = 25, 1.3% | 6 |
| n = 23, 1.4% |
| 7 | Engineering | n = 22, 1.1% | 7 |
| n = 18, 1.1% |
| 8 | Immunology and Microbiology | n = 17, 0.9% | 8 |
| n = 14, 0.9% |
| 9 | Nursing | n = 12, 0.6% | 9 |
| n = 13, 0.8% |
| 10 | Social Sciences | n = 11, 0.5% | 10 |
| n = 12, 0.7% |
Most productive countries in Search 1.
| Country | Frequency (n) | % (of 1609) | |
| 1 | United States | 268 | 16.7 |
| 2 | Japan | 214 | 13.3 |
| 3 | China | 190 | 11.8 |
| 4 | United Kingdom | 87 | 5.4 |
| 5 | South Korea | 73 | 4.5 |
| 6 | Turkey | 70 | 4.4 |
| 7 | Germany | 67 | 4.2 |
| 8 | India | 56 | 3.5 |
| 9 | Italy | 48 | 3.0 |
| 10 | Brazil | 40 | 2.5 |
| 11 | Canada | 40 | 2.5 |
Most productive countries in Search 2.
| Country | Frequency | % (of 223) | |
| 1 | China | 86 | 38.6 |
| 2 | United States | 39 | 17.5 |
| 3 | South Korea | 16 | 7.2 |
| 4 | Italy | 9 | 4.0 |
| 5 | Turkey | 9 | 4.0 |
| 6 | United Kingdom | 9 | 4.0 |
| 7 | Japan | 7 | 3.1 |
| 8 | Canada | 6 | 2.7 |
| 9 | India | 5 | 2.2 |
| 10 | Brazil | 4 | 1.8 |
| 11 | Taiwan | 4 | 1.8 |
Most productive institutions in Search 1.
| Institutions | Frequency (n) | % (of 1609) | |
| 1 | Kyung Hee University | 25 | 1.6 |
| 2 | Yamagata University Faculty of Medicine | 17 | 1.1 |
| 3 | Sichuan University | 14 | 0.9 |
| 4 | Chengdu University of Traditional Chinese Medicine | 13 | 0.8 |
| 5 | Ehime University School of Medicine | 13 | 0.8 |
| 6 | University of Toronto | 13 | 0.8 |
| 7 | Harvard Medical School | 12 | 0.7 |
| 8 | Sapienza University of Rome | 12 | 0.7 |
| 9 | Amsterdam UMC - University of Amsterdam | 11 | 0.7 |
| 10 | University of Dundee | 11 | 0.7 |
| 11 | Capital Medical University | 11 | 0.7 |
| 12 | Radboud University Nijmegen Medical Centre | 10 | 0.6 |
| 13 | West China School of Medicine/West China Hospital of Sichuan University | 10 | 0.6 |
Most productive institutions in Search 2.
| Institutions | Frequency (n) | % (of 223) | |
| 1 | Chengdu University of Traditional Chinese Medicine | 11 | 4.9 |
| 2 | Sichuan University | 9 | 4.0 |
| 3 | Kyung Hee University | 7 | 3.1 |
| 4 | Harvard Medical School | 6 | 2.7 |
| 5 | Anhui University of Chinese Medicine | 5 | 2.2 |
| 6 | University of Michigan, Ann Arbor | 5 | 2.2 |
| 7 | Sichuan Provincial People's Hospital | 5 | 2.2 |
| 8 | West China School of Medicine/West China Hospital of Sichuan University | 5 | 2.2 |
| 9 | Fudan University | 4 | 1.8 |
| 10 | Shanghai University of Traditional Chinese Medicine | 4 | 1.8 |
| 11 | Capital Medical University | 4 | 1.8 |
| 12 | Sapienza University of Rome | 4 | 1.8 |
| 13 | General Hospital of People's Liberation Army | 4 | 1.8 |
Most productive authors in Search 1.
| Authors | Frequency (n) | % (of 1609) | |
| 1 | Yeo SG (Kyung Hee University, South Korea) | 16 | 1.0 |
| 2 | Aoyagi M (Yamagata University, Japan) | 14 | 0.9 |
| 3 | Guntinas-Lichius O (Jena University Hospital, Germany) | 13 | 0.8 |
| 4 | Hato N (Ehime University School of Medicine, Japan) | 13 | 0.8 |
| 5 | Murakami S (Nagoya City University, Japan) | 13 | 0.8 |
| 6 | Yanagihara N (Ehime University School of Medicine, Japan) | 13 | 0.8 |
| 7 | Daly F (Frontier Science (Scotland) Ltd, United Kingdom) | 12 | 0.7 |
| 8 | Byun JY (Kyung Hee University, South Korea) | 11 | 0.7 |
| 9 | Inamura H (Yamagata University, Japan) | 11 | 0.7 |
| 10 | Park MS (Kyung Hee University, South Korea) | 11 | 0.7 |
Most productive authors in Search 2.
| Authors | Frequency (n) | % (of 223) | |
| 1 | Li C (Anhui University of Chinese Medicine, China) | 5 | 2.2 |
| 2 | Li Y (Chengdu University of Traditional Chinese Medicine, China) | 5 | 2.2 |
| 3 | Zhou D. (Sichuan University, China) | 5 | 2.2 |
| 4 | Li N (Sichuan University, China) | 4 | 1.8 |
| 5 | Wu H (Anhui University of Chinese Medicine, China) | 4 | 1.8 |
| 6 | Yang J (First Affiliated Hospital of Anhui University of Chinese Medicine, China) | 4 | 1.8 |
| 7 | He, L (Sichuan University, China) | 3 | 1.3 |
| 8 | Jun HK (Chungnam National University, South Korea) | 3 | 1.3 |
| 9 | Kan H (Anhui University of Chinese Medicine, China) | 3 | 1.3 |
| 10 | Kim DH (Chungnam National University, South Korea) | 3 | 1.3 |
| 11 | Li Y (Chengdu University of Traditional Chinese Medicine, China) | 3 | 1.3 |
| 12 | Li Y (Sichuan Provincial People's Hospital, China) | 3 | 1.3 |
| 13 | Xu C (Anhui University of Chinese Medicine, China) | 3 | 1.3 |
Figure 3Co-occurrence analysis of 316 keywords from the title and abstract in 1609 articles. (A) Mapping of keywords in research into facial nerve palsy treatment; 316 keywords are divided into 4 clusters. (B) Overlaid visualization map by average publication year, with white representing earlier and red representing later.
Figure 4Co-occurrence analysis of 30 keywords from article's keywords in 1609 articles. (A) Mapping of keywords; 30 keywords are divided into 4 clusters. (B) Overlaid visualization map by average publication year, with white representing earlier and red representing later. (C) Overlaid visualization map by average citation count, with blue representing more citations and white representing less.
Figure 5Co-occurrence analysis of 32 keywords from articles’ keywords in 223 articles. (A) Mapping of keywords; 32 keywords are divided into 5 clusters. (B) Overlaid visualization map by average publication year, with white representing earlier and red representing later. (C) Overlaid visualization map by average citation count, with blue representing more citations and white representing less.