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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Neurosci.</journal-id>
<journal-title>Frontiers in Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Neurosci.</abbrev-journal-title>
<issn pub-type="epub">1662-453X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnins.2023.1265854</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Neuroscience</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Visual bibliometric analysis of electroacupuncture research in stroke treatment: a 20-year overview</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Chun</surname>
<given-names>Hyonjun</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff2" ref-type="aff"><sup>2</sup></xref>
<xref rid="fn0001" ref-type="author-notes"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2388961/overview"/>
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<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Shin</surname>
<given-names>Woo-Chul</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
<xref rid="fn0001" ref-type="author-notes"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author">
<name>
<surname>Kim</surname>
<given-names>Jong-min</given-names>
</name>
<xref rid="aff4" ref-type="aff"><sup>4</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2421991/overview"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Kim</surname>
<given-names>Hyungsuk</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Cho</surname>
<given-names>Jae-Heung</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Song</surname>
<given-names>Mi-Yeon</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chung</surname>
<given-names>Won-Seok</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
<xref rid="c001" ref-type="corresp"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2387467/overview"/>
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<aff id="aff1"><sup>1</sup><institution>Department of Clinical Korean Medicine, Graduate School, Kyung Hee University</institution>, <addr-line>Seoul</addr-line>, <country>Republic of Korea</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Korean Rehabilitation Medicine, Dong-shin Korean Medicine Hospital</institution>, <addr-line>Seoul</addr-line>, <country>Republic of Korea</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Korean Rehabilitation Medicine, Kyung Hee University Medical Center</institution>, <addr-line>Seoul</addr-line>, <country>Republic of Korea</country></aff>
<aff id="aff4"><sup>4</sup><institution>Department of Oriental Neuropsychiatry, Dong-Seo Medical Center</institution>, <addr-line>Seoul</addr-line>, <country>Republic of Korea</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0002">
<p>Edited by: Qi Wan, Qingdao University, China</p>
</fn>
<fn fn-type="edited-by" id="fn0003">
<p>Reviewed by: Annibale Antonioni, University of Ferrara, Italy; Lu Qi, Shanghai University of Traditional Chinese Medicine, China</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Won-Seok Chung, <email>omdluke@naver.com</email></corresp>
<fn fn-type="equal" id="fn0001">
<p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>10</day>
<month>10</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>17</volume>
<elocation-id>1265854</elocation-id>
<history>
<date date-type="received">
<day>25</day>
<month>07</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>25</day>
<month>09</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2023 Chun, Shin, Kim, Kim, Cho, Song and Chung.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Chun, Shin, Kim, Kim, Cho, Song and Chung</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>Electroacupuncture has been used as a treatment; however, a visual bibliometric analysis has not yet been performed in this field. In this study, we aimed to suggest future research topics and directions related to the field by examining the last 20&#x2009;years of research trends and hotspots of electroacupuncture in stroke.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>We searched the Web of Science database on electroacupuncture as a treatment for stroke published from 2003 to 2022. We analyzed the papers by annual publication, research fields, nations, affiliations, authors, journals, and keywords. VOSviewer software was used to visualize the bibliometric analysis and results. A total of 440 papers were included in the analysis.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>The number of publications has gradually increased every year, and neuroscience has become the most actively studied field. Neural Regeneration Research journal and China had the most publications. Fujian University of Traditional Chinese Medicine, as an affiliated institute, published the most articles. Chen Lidian and Tao Jing presented the largest number of papers, making them the leading contributors in this field. Four clusters were created by analyzing keywords, such as &#x201C;neuroprotection,&#x201D; &#x201C;clinical rehabilitation,&#x201D; &#x201C;neuroplasticity,&#x201D; and &#x201C;pretreatment-induced tolerance&#x201D;.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>This study is the first to analyze the research trends in electroacupuncture as a treatment for stroke using the VOSviewer. It shows the current state of research in the field by visualizing research trends and hotspots. This will help offer reference data for future studies.</p>
</sec>
</abstract>
<kwd-group>
<kwd>stroke</kwd>
<kwd>electroacupuncture</kwd>
<kwd>bibliometric analysis</kwd>
<kwd>Web of Science</kwd>
<kwd>VOSviewer</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="9"/>
<equation-count count="0"/>
<ref-count count="29"/>
<page-count count="12"/>
<word-count count="6376"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Translational Neuroscience</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1.</label>
<title>Introduction</title>
<p>Stroke is classified into several types including ischemic stroke, subarachnoid hemorrhage, and intracerebral hemorrhage. Despite recent improvements in medicine, stroke is one of the leading causes of mortality worldwide (<xref ref-type="bibr" rid="ref5">Feigin et al., 2021</xref>). Additionally, lengthy sequelae of stroke are frequent, contributing to an increase in social costs (<xref ref-type="bibr" rid="ref14">Tsao et al., 2022</xref>) by decreasing the quality of life. Stroke is generally categorized into three stages; acute, sub-acute and chronic stage depending on pathological characteristics and post-stroke period (<xref ref-type="bibr" rid="ref1001">Zhao and Willing, 2018</xref>). Acute stage of ischemic stroke is treated with venous thrombolytics injection or thrombectomy whereas hemorrhagic stroke is treated with controlling hemorrhage and removing hematoma. Since majority of people who have suffered a stroke report significant disability even after appropriate acute treatment, rehabilitation treatment plays a critical role in subacute and chronic stage. Conventionally physical therapy, occupational therapy and speech therapy has been recommended for rehabilitation and management of cardiovascular risk factors such as lowering blood pressure is general principles to prevent secondary stroke (<xref ref-type="bibr" rid="ref2">Campbell and Khatri, 2020</xref>). Despite these conventional medical care, establishment of the optimal rehabilitation intervention has been challenging. Therefore, alternative treatments such as acupuncture, electro-acupuncture and herbal medicine has been gaining attention as a rehabilitation treatment for chronic stage patients.</p>
<p>Traditionally in East Asia, Traditional Chinese Medicine (TCM) has been used for stroke care (<xref ref-type="bibr" rid="ref3">Ceniceros and Brown, 1998</xref> <xref ref-type="bibr" rid="ref23">Zhang et al., 2022</xref>). In the early 19th century, Berlioz from France suggested the clinical application of concurrent use of modern electric therapy and traditional acupuncture and Electroacupuncture (EA) has been used in clinical environment to treat stroke and related disorders since (<xref ref-type="bibr" rid="ref1002">Macdonald, 1993</xref>). Unlike other modality of TCM, EA has the advantage of being standardized by controlling the frequency and intensity of stimulation and has been researched diversely on mechanism and its clinical effect. In animal experiments, EA alleviates ischemic brain damage by regulating apoptosis, inflammation, autophagocytosis, glutamate, mRNA, and other factors (<xref ref-type="bibr" rid="ref20">Xing et al., 2018</xref>). In clinical applications, EA is an effective treatment for stroke symptoms such as dysphagia (<xref ref-type="bibr" rid="ref6">Huang et al., 2020</xref>), pain (<xref ref-type="bibr" rid="ref21">Xu et al., 2020</xref>), aphasia (<xref ref-type="bibr" rid="ref13">Shi et al., 2022</xref>), and urinary incontinence (<xref ref-type="bibr" rid="ref4">Cruz et al., 2022</xref>).</p>
<p>The bibliometric analysis method uses mathematical and statistical tools, thereby providing an overview of academic research publications and a quantitative analysis of research trends. This method can identify influential publications, authors, journals, affiliations, and countries and analyze and present topics, methods, and influential keywords (<xref ref-type="bibr" rid="ref15">van Eck and Waltman, 2010</xref>). There are bibliometric analyses of EA regarding general diseases from 2011 to 2020 (<xref ref-type="bibr" rid="ref18">Wei et al., 2022</xref>); however, a bibliometric analysis of EA as a treatment for stroke has not yet been conducted. Therefore, in this study, we conducted a bibliometric analysis by year, country, journal, keyword, affiliation, and author of research papers about EA for stroke, which were published in the Web of Science Core Collection Database (WOSCC) in the last 20&#x2009;years. Network properties between studies and research trends were identified. Therefore, we aimed to propose additional future research directions in the field.</p>
</sec>
<sec sec-type="methods" id="sec6">
<label>2.</label>
<title>Methods</title>
<sec id="sec7">
<label>2.1.</label>
<title>Data search</title>
<p>All data were extracted from WOSCC. Research papers published between January 01, 2003, and December 31, 2022, were collected, and data was extracted from articles published between February 20, 2023, and February 27, 2023, based on WOSCC using TS: ([&#x201C;stroke&#x201D; OR &#x201C;infarction&#x201D; OR &#x201C;cerebrovascular accident&#x201D; OR &#x201C;cerebral hemorrhage&#x201D; OR &#x201C;cerebral ischemia&#x201D;] AND [&#x201C;Electroacupuncture&#x201D; OR &#x201C;electro-acupuncture&#x201D; OR &#x201C;electric acupuncture&#x201D;]) as search queries. The results were then converted into text files and organized for further data analysis on March 01, 2023.</p>
<p>A total of 661 papers were extracted during the first data search. Articles and reviews were excluded, and 636 works of literature were selected. Two independent researchers screened the remaining papers by examining each title and abstract. Criteria of inclusion were: (1) Original article (2) Time range: published from 2003 to 2022 (3) research regarding EA as treatment for stroke. Criteria of exclusion were: (1) research regarding encephalopathy other than stroke (dementia, Alzheimer, etc.) (2) EA intervention without penetration of skin (laser acupuncture, transcutaneous electrical nerve stimulation, etc.) (3) article without abstract, book chapters, and editorial meetings (4) retracted or overlapped research. Papers with incomplete text were also excluded, while those with a full text were reviewed. In total, 440 papers were selected for this study (<xref rid="fig1" ref-type="fig">Figure 1</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Flow chart detailing the process of article selection.</p>
</caption>
<graphic xlink:href="fnins-17-1265854-g001.tif"/>
</fig>
<p>Keywords were unified into a single form to enhance the accuracy of our analysis. Full names were used in the author analysis to enhance accuracy (Chen, LD To Chen, Lidian). The affiliation name was unified (fourth military medical university to air force medical university).</p>
</sec>
<sec id="sec8">
<label>2.2.</label>
<title>Data analysis</title>
<p>The screened publications were categorized and analyzed according to the publication year, nation, journal, research institution, author, and affiliation. Data on nation, affiliation, keywords, and authors were analyzed using VOSviewer to visualize the links between categories. Research areas were categorized using the WOSCC algorithm, which considers the characteristics of the journal. Each article was sorted into one to six research areas (<xref ref-type="bibr" rid="ref11">Milojevi&#x0107;, 2020</xref>). To visualize the analysis, layout attraction/repulsion values were adjusted, and settings were differentiated by category for clearer visualization.</p>
</sec>
</sec>
<sec sec-type="results" id="sec9">
<label>3.</label>
<title>Results</title>
<sec id="sec10">
<label>3.1.</label>
<title>Published year</title>
<p>In 2003, four papers were published, but in 2022, 53 papers were published. This result shows that the number of publications has increased from 27 in the year 2019 to 55 in 2020. The number of papers published doubled, and highest number of publications, 55, were in 2020, constituting 12.5% of all papers over 20&#x2009;years (<xref rid="fig2" ref-type="fig">Figure 2</xref>).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Annual trends of article publications.</p>
</caption>
<graphic xlink:href="fnins-17-1265854-g002.tif"/>
</fig>
</sec>
<sec id="sec11">
<label>3.2.</label>
<title>Research field</title>
<p>Most papers were published in the field of neuroscience (36.6%), followed by Complementary Medicine (26.8%), Cell Biology (14.5%), and Medicine Research Experimental (14.31%) (<xref rid="tab1" ref-type="table">Table 1</xref>). Among published papers, 294 papers were pre-clinical model and 45 papers were clinical trials. The remaining 101 researches were reviews.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Distribution of publications on electroacupuncture for stroke by research fields.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Categories</th>
<th align="center" valign="top">Record count (<italic>n</italic>)</th>
<th align="center" valign="top">% (of 440)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">Neurosciences</td>
<td align="center" valign="middle">161</td>
<td align="char" valign="middle" char=".">36.6</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="left" valign="middle">Integrative Complementary Medicine</td>
<td align="center" valign="middle">118</td>
<td align="char" valign="middle" char=".">26.8</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">Cell Biology</td>
<td align="center" valign="middle">64</td>
<td align="char" valign="middle" char=".">14.5</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">Medicine Research Experimental</td>
<td align="center" valign="middle">63</td>
<td align="char" valign="middle" char=".">14.3</td>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="left" valign="middle">Clinical Neurology</td>
<td align="center" valign="middle">42</td>
<td align="char" valign="middle" char=".">9.5</td>
</tr>
<tr>
<td align="left" valign="middle">6</td>
<td align="left" valign="middle">Medicine General Internal</td>
<td align="center" valign="middle">36</td>
<td align="char" valign="middle" char=".">8.2</td>
</tr>
<tr>
<td align="left" valign="middle">7</td>
<td align="left" valign="middle">Biochemistry Molecular Biology</td>
<td align="center" valign="middle">20</td>
<td align="char" valign="middle" char=".">4.5</td>
</tr>
<tr>
<td align="left" valign="middle">8</td>
<td align="left" valign="middle">Multidisciplinary Sciences</td>
<td align="center" valign="middle">11</td>
<td align="char" valign="middle" char=".">2.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Oncology</td>
<td align="center" valign="middle">11</td>
<td align="char" valign="middle" char=".">2.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Pharmacology Pharmacy</td>
<td align="center" valign="middle">11</td>
<td align="char" valign="middle" char=".">2.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Rehabilitation</td>
<td align="center" valign="middle">11</td>
<td align="char" valign="middle" char=".">2.5</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec12">
<label>3.3.</label>
<title>Journals</title>
<p>Among the 440 papers, Neural Regeneration Research had the highest number of publications (10.9%). Evidence-Based Complementary and Alternative Medicine had the second most published papers (9.5%), followed by Acupuncture in Medicine (4.1%) and Medicine (3.2%) (<xref rid="tab2" ref-type="table">Table 2</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Journals with the most publications on electroacupuncture for stroke.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Journals</th>
<th align="center" valign="top">Record Count (<italic>n</italic>)</th>
<th align="center" valign="top">% (of 440)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">Neural Regeneration Research</td>
<td align="center" valign="middle">48</td>
<td align="char" valign="middle" char=".">10.9</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="left" valign="middle">Evidence-Based Complementary and Alternative Medicine</td>
<td align="center" valign="middle">42</td>
<td align="char" valign="middle" char=".">9.5</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">Acupuncture in Medicine</td>
<td align="center" valign="middle">18</td>
<td align="char" valign="middle" char=".">4.1</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">Medicine</td>
<td align="center" valign="middle">14</td>
<td align="char" valign="middle" char=".">3.2</td>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="left" valign="middle">Journal of Traditional Chinese Medicine</td>
<td align="center" valign="middle">12</td>
<td align="char" valign="middle" char=".">2.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Neural Plasticity</td>
<td align="center" valign="middle">12</td>
<td align="char" valign="middle" char=".">2.7</td>
</tr>
<tr>
<td align="left" valign="middle">7</td>
<td align="left" valign="middle">Neurological Research</td>
<td align="center" valign="middle">11</td>
<td align="char" valign="middle" char=".">2.5</td>
</tr>
<tr>
<td align="left" valign="middle">8</td>
<td align="left" valign="middle">BMC Complementary Medicine and Therapies</td>
<td align="center" valign="middle">9</td>
<td align="char" valign="middle" char=".">2.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Brain Research</td>
<td align="center" valign="middle">9</td>
<td align="char" valign="middle" char=".">2.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">International Journal of Molecular Medicine</td>
<td align="center" valign="middle">9</td>
<td align="char" valign="middle" char=".">2.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Trials</td>
<td align="center" valign="middle">9</td>
<td align="char" valign="middle" char=".">2.0</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec13">
<label>3.4.</label>
<title>Countries</title>
<p>China published 374 papers, accounting for 85% of the 440 papers, and published the most number of research articles. The following nations were South Korea (8.4%), the United States (6.1%), and Taiwan (4.1%) (<xref rid="tab3" ref-type="table">Table 3</xref>).</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Countries with the most publications on electroacupuncture for stroke.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Countries</th>
<th align="center" valign="top">Record count (<italic>n</italic>)</th>
<th align="center" valign="top">% (of 440)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">Peoples R China</td>
<td align="center" valign="middle">374</td>
<td align="char" valign="middle" char=".">85.0</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="left" valign="middle">South Korea</td>
<td align="center" valign="middle">37</td>
<td align="char" valign="middle" char=".">8.4</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">USA</td>
<td align="center" valign="middle">27</td>
<td align="char" valign="middle" char=".">6.1</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">Taiwan</td>
<td align="center" valign="middle">18</td>
<td align="char" valign="middle" char=".">4.1</td>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="left" valign="middle">Australia</td>
<td align="center" valign="middle">6</td>
<td align="char" valign="middle" char=".">1.4</td>
</tr>
<tr>
<td align="left" valign="middle">6</td>
<td align="left" valign="middle">England</td>
<td align="center" valign="middle">4</td>
<td align="char" valign="middle" char=".">0.9</td>
</tr>
<tr>
<td align="left" valign="middle">7</td>
<td align="left" valign="middle">Canada</td>
<td align="center" valign="middle">3</td>
<td align="char" valign="middle" char=".">0.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Japan</td>
<td align="center" valign="middle">3</td>
<td align="char" valign="middle" char=".">0.7</td>
</tr>
<tr>
<td align="left" valign="middle">9</td>
<td align="left" valign="middle">Austria</td>
<td align="center" valign="middle">2</td>
<td align="char" valign="middle" char=".">0.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">France</td>
<td align="center" valign="middle">2</td>
<td align="char" valign="middle" char=".">0.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Germany</td>
<td align="center" valign="middle">2</td>
<td align="char" valign="middle" char=".">0.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Singapore</td>
<td align="center" valign="middle">2</td>
<td align="char" valign="middle" char=".">0.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Thailand</td>
<td align="center" valign="middle">2</td>
<td align="char" valign="middle" char=".">0.5</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>First, countries that published more than five papers were analyzed using the VOSviewer program, and three clusters were defined. The first cluster comprises China and Australia, the second cluster comprises USA and Taiwan, and third cluster includes South Korea (<xref rid="fig3" ref-type="fig">Figure 3A</xref>).</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p><bold>(A)</bold> A visualization of the network between countries which published on electroacupuncture for stroke. <bold>(B)</bold> A visualization of countries which published on electroacupuncture for stroke distinguished by average publication year. <bold>(C)</bold> A visualization of countries which published on electroacupuncture for stroke distinguished by average citations.</p>
</caption>
<graphic xlink:href="fnins-17-1265854-g003.tif"/>
</fig>
<p>Subsequently, research papers from each country were distinguished based on the average publication year. As the average publication year increased, nodes were visualized in blue, and as they became more recent, they were visualized in red (<xref rid="fig3" ref-type="fig">Figure 3B</xref>).</p>
<p>Finally, the average citation count of the publications from each country was analyzed. Fewer cited country nodes were visualized in blue and more cited nodes were visualized in red (<xref rid="fig3" ref-type="fig">Figure 3C</xref>).</p>
</sec>
<sec id="sec14">
<label>3.5.</label>
<title>Affiliated institution</title>
<p>The analysis by affiliation showed that Fujian University of Traditional Chinese Medicine produced the highest number of studies (9.5%), followed by Guangzhou University of Chinese Medicine (7.7%), Air Force Military Medical University (5.9%), Tianjin University of Traditional Chinese Medicine (5.2%), and Fudan University (4.8%) (<xref rid="tab4" ref-type="table">Table 4</xref>).</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Institutions and their number of publications.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Affiliations</th>
<th align="center" valign="top">Record count (<italic>n</italic>)</th>
<th align="center" valign="top">% (of 440)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">Fujian University of Traditional Chinese Medicine</td>
<td align="center" valign="middle">42</td>
<td align="char" valign="middle" char=".">9.5</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="left" valign="middle">Guangzhou University of Chinese Medicine</td>
<td align="center" valign="middle">34</td>
<td align="char" valign="middle" char=".">7.7</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">Air Force Military Medical University</td>
<td align="center" valign="middle">26</td>
<td align="char" valign="middle" char=".">5.9</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">Tianjin University of Traditional Chinese Medicine</td>
<td align="center" valign="middle">23</td>
<td align="char" valign="middle" char=".">5.2</td>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="left" valign="middle">Fudan University</td>
<td align="center" valign="middle">21</td>
<td align="char" valign="middle" char=".">4.8</td>
</tr>
<tr>
<td align="left" valign="middle">6</td>
<td align="left" valign="middle">Shanghai University of Traditional Chinese Medicine</td>
<td align="center" valign="middle">20</td>
<td align="char" valign="middle" char=".">4.5</td>
</tr>
<tr>
<td align="left" valign="middle">7</td>
<td align="left" valign="middle">Nanjing University of Chinese Medicine</td>
<td align="center" valign="middle">19</td>
<td align="char" valign="middle" char=".">4.3</td>
</tr>
<tr>
<td align="left" valign="middle">8</td>
<td align="left" valign="middle">China Medical University Taiwan</td>
<td align="center" valign="middle">17</td>
<td align="char" valign="middle" char=".">3.9</td>
</tr>
<tr>
<td align="left" valign="middle">9</td>
<td align="left" valign="middle">Beijing University of Chinese Medicine</td>
<td align="center" valign="middle">16</td>
<td align="char" valign="middle" char=".">3.6</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Kyung Hee University</td>
<td align="center" valign="middle">16</td>
<td align="char" valign="middle" char=".">3.6</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>A total of 43 institutions published more than five research papers, which were categorized into nine clusters using the VOSviewer program (<xref rid="fig4" ref-type="fig">Figure 4A</xref>). Cluster 1 comprised 11 institutions, including the Fujian University of Traditional Chinese Medicine and the Air Force Military Medical University. In the second cluster, 10 institutions were included, comprising Tianjin University of Traditional Chinese Medicine and Nanjing University of Chinese Medicine. Cluster 3 comprised seven institutions, including Guangzhou University of Chinese Medicine and Wenzhou Medical University. Cluster 4 included five institutions, including Fudan University and Shanghai University of Traditional Chinese Medicine. Cluster 5 comprised three institutions: Kyung Hee University and Kyung Hee University Hospital. The Chinese Academy of Medical Sciences Peking Union Medical College, Peking Union Medical College, and Peking Union Medical College Hospital were included in cluster 6. Cluster 7 included the China Medical University Hospital Taiwan and China Medical University Taiwan. Cluster 8 included Chongqing Medical University and Southwest Medical University. Pusan National University alone was categorized as Cluster 9.</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p><bold>(A)</bold> A visualization of institutions which published on electroacupuncture for stroke. <bold>(B)</bold> A visualization of institutions which published on electroacupuncture for stroke by average publication year. <bold>(C)</bold> A visualization of institutions which published on electroacupuncture for stroke by average citations.</p>
</caption>
<graphic xlink:href="fnins-17-1265854-g004.tif"/>
</fig>
<p>Second, the published research papers of each affiliation were distinguished based on the average publication year. As the average publication year increased, it was visualized in blue; if it became more recent, it was visualized in yellow (<xref rid="fig4" ref-type="fig">Figure 4B</xref>). Anhui University of Chinese Medicine had the most recent average publication year (2021.20), and The Guangxi University of Chinese Medicine had the oldest average publication year (2011.60).</p>
<p>Finally, the average number of citations of publications from each affiliation was analyzed. The more blue a node, the less frequently it is cited. The more yellow a node, the more frequently it was cited (<xref rid="fig4" ref-type="fig">Figure 4C</xref>). The least cited institution was the Heilongjiang University of Chinese Medicine (4.9) and the most cited institution was the Air Force Military Medical University (37.7).</p>
<p>Analysis by cluster showed that Cluster 5 had the earliest average publication year, and Cluster 8 had the latest. Cluster 9 had the largest average number of citations, and Cluster 3 was the least cited (<xref rid="tab5" ref-type="table">Table 5</xref>).</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Analysis of institution cluster.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top">Occurrence</th>
<th align="center" valign="top">Average publication year</th>
<th align="center" valign="top">Average citations</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Cluster 1</td>
<td align="char" valign="middle" char=".">12.5</td>
<td align="char" valign="middle" char=".">2016.7</td>
<td align="char" valign="middle" char=".">17.6</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 2</td>
<td align="char" valign="middle" char=".">8.9</td>
<td align="char" valign="middle" char=".">2016.6</td>
<td align="char" valign="middle" char=".">13.4</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 3</td>
<td align="char" valign="middle" char=".">12.3</td>
<td align="char" valign="middle" char=".">2017.4</td>
<td align="char" valign="middle" char=".">9.4</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 4</td>
<td align="char" valign="middle" char=".">12.2</td>
<td align="char" valign="middle" char=".">2015.1</td>
<td align="char" valign="middle" char=".">11.3</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 5</td>
<td align="char" valign="middle" char=".">9.0</td>
<td align="char" valign="middle" char=".">2014.1</td>
<td align="char" valign="middle" char=".">12.9</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 6</td>
<td align="char" valign="middle" char=".">9.3</td>
<td align="char" valign="middle" char=".">2017.9</td>
<td align="char" valign="middle" char=".">18.6</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 7</td>
<td align="char" valign="middle" char=".">15.5</td>
<td align="char" valign="middle" char=".">2015.9</td>
<td align="char" valign="middle" char=".">26.3</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 8</td>
<td align="char" valign="middle" char=".">9.5</td>
<td align="char" valign="middle" char=".">2017.5</td>
<td align="char" valign="middle" char=".">12.9</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 9</td>
<td align="char" valign="middle" char=".">13.0</td>
<td align="char" valign="middle" char=".">2016.5</td>
<td align="char" valign="middle" char=".">31.5</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec15">
<label>3.6.</label>
<title>Author</title>
<p>The authors&#x2019; analysis revealed that Chen Lidian (7.7%) and Tao Jing (from Fujian University) published the most papers, followed by Liu Weilin (4.5%), Huang Jia (4.3%), and Xiong Lize (3.9%) from Tongji University (<xref rid="tab6" ref-type="table">Table 6</xref>).</p>
<table-wrap position="float" id="tab6">
<label>Table 6</label>
<caption>
<p>Authors with the most publications on electroacupuncture for stroke.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Rank</th>
<th align="left" valign="top">Author</th>
<th align="center" valign="top">Record count (<italic>n</italic>)</th>
<th align="center" valign="top">% (of 440)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">Chen Lidian</td>
<td align="center" valign="middle">34</td>
<td align="char" valign="middle" char=".">7.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Tao Jing</td>
<td align="center" valign="middle">34</td>
<td align="char" valign="middle" char=".">7.7</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">Liu Weilin</td>
<td align="center" valign="middle">20</td>
<td align="char" valign="middle" char=".">4.5</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">Huang Jia</td>
<td align="center" valign="middle">19</td>
<td align="char" valign="middle" char=".">4.3</td>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="left" valign="middle">Xiong Lize</td>
<td align="center" valign="middle">17</td>
<td align="char" valign="middle" char=".">3.9</td>
</tr>
<tr>
<td align="left" valign="middle">6</td>
<td align="left" valign="middle">Wang Qiang</td>
<td align="center" valign="middle">16</td>
<td align="char" valign="middle" char=".">3.6</td>
</tr>
<tr>
<td align="left" valign="middle">7</td>
<td align="left" valign="middle">Choi Byung-Tae</td>
<td align="center" valign="middle">13</td>
<td align="char" valign="middle" char=".">3.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Shin Hwa Kyoung</td>
<td align="center" valign="middle">13</td>
<td align="char" valign="middle" char=".">3.0</td>
</tr>
<tr>
<td align="left" valign="middle">9</td>
<td align="left" valign="middle">Lin Ruhui</td>
<td align="center" valign="middle">12</td>
<td align="char" valign="middle" char=".">2.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Xu Nenggui</td>
<td align="center" valign="middle">12</td>
<td align="char" valign="middle" char=".">2.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Yang Shanli</td>
<td align="center" valign="middle">12</td>
<td align="char" valign="middle" char=".">2.7</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>First, those who published more than five papers (65 authors) were analyzed using the VOSviewer program, and 18 clusters were defined. Cluster 1 included 12 authors: Chen Lidian, Tao Jing, and etc. Eight authors, including Xiong Lize and Wang Qiang, were categorized in Cluster 2. Cluster 3 included five authors: Lin Ruhui, Chen Bin, and etc. In Cluster 4, there were five authors: Xu Nenggui, Yi Wei, and etc. Further clusters are visualized in <xref rid="fig5" ref-type="fig">Figure 5A</xref>.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p><bold>(A)</bold> A visualization of authors who published on electroacupuncture for stroke. <bold>(B)</bold> A visualization of authors who published on electroacupuncture for stroke by average publication year. <bold>(C)</bold> A visualization of authors who published on electroacupuncture for stroke by average citations.</p>
</caption>
<graphic xlink:href="fnins-17-1265854-g005.tif"/>
</fig>
<p>The research papers published by each author were then distinguished by average publication year. As the average publication year increased, the authors cluster turned blue. The more recent the average publication year, the more yellow the author cluster (<xref rid="fig5" ref-type="fig">Figure 5B</xref>). Cheng and Jieshi had the oldest average publication year (2007.9), and Yang and Minguang had the most recent (2020.6).</p>
<p>Finally, the average number of publications by each author was determined. Blue indicates that the average number of citations is small. As the node color approached yellow, the average number of citations increased (<xref rid="fig5" ref-type="fig">Figure 5C</xref>). Chen and Shaoyang had the largest average citation value (57.7), whereas Du and Yuzheng had the smallest (1.4).</p>
<p>Analysis of each cluster showed that Cluster 12 had the earliest average publication year (2009.02) and Cluster 18 had the most recent average publication year (2019.06). Cluster 16 had the lowest average number of citations (3.9) and Cluster 7 had the highest average number of citations (32.62) (<xref rid="tab7" ref-type="table">Table 7</xref>).</p>
<table-wrap position="float" id="tab7">
<label>Table 7</label>
<caption>
<p>Analysis of author cluster.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top">Occurrence</th>
<th align="center" valign="top">Average publication year</th>
<th align="center" valign="top">Average citations</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Cluster 1</td>
<td align="char" valign="middle" char=".">13.3</td>
<td align="char" valign="middle" char=".">2016.8</td>
<td align="char" valign="middle" char=".">32.2</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 2</td>
<td align="char" valign="middle" char=".">8.5</td>
<td align="char" valign="middle" char=".">2014.4</td>
<td align="char" valign="middle" char=".">32.6</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 3</td>
<td align="char" valign="middle" char=".">7.4</td>
<td align="char" valign="middle" char=".">2017.3</td>
<td align="char" valign="middle" char=".">19.5</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 4</td>
<td align="char" valign="middle" char=".">7.2</td>
<td align="char" valign="middle" char=".">2016.9</td>
<td align="char" valign="middle" char=".">8.8</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 5</td>
<td align="char" valign="middle" char=".">6.0</td>
<td align="char" valign="middle" char=".">2015.5</td>
<td align="char" valign="middle" char=".">8.1</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 6</td>
<td align="char" valign="middle" char=".">9.3</td>
<td align="char" valign="middle" char=".">2017.5</td>
<td align="char" valign="middle" char=".">17.9</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 7</td>
<td align="char" valign="middle" char=".">10.3</td>
<td align="char" valign="middle" char=".">2016.0</td>
<td align="char" valign="middle" char=".">30.6</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 8</td>
<td align="char" valign="middle" char=".">6.0</td>
<td align="char" valign="middle" char=".">2019.3</td>
<td align="char" valign="middle" char=".">9.7</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 9</td>
<td align="char" valign="middle" char=".">6.3</td>
<td align="char" valign="middle" char=".">2018.8</td>
<td align="char" valign="middle" char=".">20.5</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 10</td>
<td align="char" valign="middle" char=".">5.3</td>
<td align="char" valign="middle" char=".">2012.7</td>
<td align="char" valign="middle" char=".">4.8</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 11</td>
<td align="char" valign="middle" char=".">5.0</td>
<td align="char" valign="middle" char=".">2017.4</td>
<td align="char" valign="middle" char=".">16.8</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 12</td>
<td align="char" valign="middle" char=".">6.5</td>
<td align="char" valign="middle" char=".">2009.0</td>
<td align="char" valign="middle" char=".">21.2</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 13</td>
<td align="char" valign="middle" char=".">5.0</td>
<td align="char" valign="middle" char=".">2016.4</td>
<td align="char" valign="middle" char=".">16.4</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 14</td>
<td align="char" valign="middle" char=".">9.0</td>
<td align="char" valign="middle" char=".">2015.8</td>
<td align="char" valign="middle" char=".">28.4</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 15</td>
<td align="char" valign="middle" char=".">6.0</td>
<td align="char" valign="middle" char=".">2016.0</td>
<td align="char" valign="middle" char=".">23.6</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 16</td>
<td align="char" valign="middle" char=".">5.0</td>
<td align="char" valign="middle" char=".">2017.9</td>
<td align="char" valign="middle" char=".">3.9</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 17</td>
<td align="char" valign="middle" char=".">5.5</td>
<td align="char" valign="middle" char=".">2015.2</td>
<td align="char" valign="middle" char=".">19.3</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 18</td>
<td align="char" valign="middle" char=".">5.0</td>
<td align="char" valign="middle" char=".">2019.6</td>
<td align="char" valign="middle" char=".">11.2</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec16">
<label>3.7.</label>
<title>Keyword</title>
<p>First, 1,616 keywords were mentioned in 440 papers, and 52 keywords that were found more than 15 times were analyzed. Four keyword clusters were defined using the VOSviewer (<xref rid="fig6" ref-type="fig">Figure 6A</xref>).</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p><bold>(A)</bold> A visualization of keywords related to electroacupuncture for stroke. <bold>(B)</bold> A visualization of keywords related to electroacupuncture for stroke by average publication year. <bold>(C)</bold> A visualization of keywords related to electroacupuncture for stroke by average citations.</p>
</caption>
<graphic xlink:href="fnins-17-1265854-g006.tif"/>
</fig>
<p>The keywords were categorized according to the average publication year. As the average publication year increases, the results were visualized in blue. Because the average publication year was recent, it is visualized in yellow (<xref rid="fig6" ref-type="fig">Figure 6B</xref>). Analysis of keywords by average publication year showed that the three most recent keywords were &#x201C;autophagy,&#x201D; &#x201C;systematic review,&#x201D; and &#x201C;cognitive impairment.&#x201D; The three oldest keywords were &#x201C;neural regeneration,&#x201D; &#x201C;cerebral ischemia,&#x201D; and &#x201C;arterial occlusion&#x201D; (<xref rid="tab8" ref-type="table">Table 8</xref>).</p>
<table-wrap position="float" id="tab8">
<label>Table 8</label>
<caption>
<p>The most frequent keywords related to electroacupuncture for stroke from 2003&#x2013;2022.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Cluster</th>
<th align="left" valign="top">Keyword</th>
<th align="center" valign="top">Occurrence</th>
<th align="center" valign="top">Average publication year</th>
<th align="center" valign="top">Average citations</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">Rat</td>
<td align="center" valign="middle">64</td>
<td align="char" valign="middle" char=".">2015.9</td>
<td align="char" valign="middle" char=".">18.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Apoptosis</td>
<td align="center" valign="middle">58</td>
<td align="char" valign="middle" char=".">2016.7</td>
<td align="char" valign="middle" char=".">18.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Mechanism</td>
<td align="center" valign="middle">47</td>
<td align="char" valign="middle" char=".">2018.3</td>
<td align="char" valign="middle" char=".">16.4</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cerebral ischemia reperfusion</td>
<td align="center" valign="middle">29</td>
<td align="char" valign="middle" char=".">2016.0</td>
<td align="char" valign="middle" char=".">24.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Neuroprotection</td>
<td align="center" valign="middle">28</td>
<td align="char" valign="middle" char=".">2015.9</td>
<td align="char" valign="middle" char=".">21.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Oxidative stress</td>
<td align="center" valign="middle">28</td>
<td align="char" valign="middle" char=".">2017.5</td>
<td align="char" valign="middle" char=".">19.8</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Ischemia&#x2013;reperfusion injury</td>
<td align="center" valign="middle">28</td>
<td align="char" valign="middle" char=".">2017.9</td>
<td align="char" valign="middle" char=".">14.9</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Brain injury</td>
<td align="center" valign="middle">25</td>
<td align="char" valign="middle" char=".">2016.4</td>
<td align="char" valign="middle" char=".">15.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Inhibition</td>
<td align="center" valign="middle">24</td>
<td align="char" valign="middle" char=".">2015.5</td>
<td align="char" valign="middle" char=".">21.3</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Neural regeneration</td>
<td align="center" valign="middle">24</td>
<td align="char" valign="middle" char=".">2013.7</td>
<td align="char" valign="middle" char=".">8.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Neuron</td>
<td align="center" valign="middle">22</td>
<td align="char" valign="middle" char=".">2014.9</td>
<td align="char" valign="middle" char=".">12.9</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Autophagy</td>
<td align="center" valign="middle">19</td>
<td align="char" valign="middle" char=".">2019.8</td>
<td align="char" valign="middle" char=".">18.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Hippocampus</td>
<td align="center" valign="middle">19</td>
<td align="char" valign="middle" char=".">2014.8</td>
<td align="char" valign="middle" char=".">15.2</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Inflammation</td>
<td align="center" valign="middle">18</td>
<td align="char" valign="middle" char=".">2017.8</td>
<td align="char" valign="middle" char=".">21.4</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Reperfusion injury</td>
<td align="center" valign="middle">17</td>
<td align="char" valign="middle" char=".">2017.8</td>
<td align="char" valign="middle" char=".">13.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Nerve regeneration</td>
<td align="center" valign="middle">16</td>
<td align="char" valign="middle" char=".">2017.2</td>
<td align="char" valign="middle" char=".">11.6</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cerebral ischemia&#x2013;reperfusion injury</td>
<td align="center" valign="middle">15</td>
<td align="char" valign="middle" char=".">2018.4</td>
<td align="char" valign="middle" char=".">18.1</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Protect</td>
<td align="center" valign="middle">15</td>
<td align="char" valign="middle" char=".">2018.5</td>
<td align="char" valign="middle" char=".">10.3</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="left" valign="middle">Electroacupuncture</td>
<td align="center" valign="middle">285</td>
<td align="char" valign="middle" char=".">2016.0</td>
<td align="char" valign="middle" char=".">17.2</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Acupuncture</td>
<td align="center" valign="middle">178</td>
<td align="char" valign="middle" char=".">2016.5</td>
<td align="char" valign="middle" char=".">16.6</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Stroke</td>
<td align="center" valign="middle">176</td>
<td align="char" valign="middle" char=".">2016.8</td>
<td align="char" valign="middle" char=".">16.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Recovery</td>
<td align="center" valign="middle">49</td>
<td align="char" valign="middle" char=".">2016.7</td>
<td align="char" valign="middle" char=".">11.9</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Stimulation</td>
<td align="center" valign="middle">45</td>
<td align="char" valign="middle" char=".">2015.9</td>
<td align="char" valign="middle" char=".">26.2</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Rehabilitation</td>
<td align="center" valign="middle">36</td>
<td align="char" valign="middle" char=".">2016.5</td>
<td align="char" valign="middle" char=".">17.3</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cognitive impairment</td>
<td align="center" valign="middle">22</td>
<td align="char" valign="middle" char=".">2019.1</td>
<td align="char" valign="middle" char=".">16.9</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Randomized controlled trial</td>
<td align="center" valign="middle">20</td>
<td align="char" valign="middle" char=".">2017.3</td>
<td align="char" valign="middle" char=".">16.4</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Systematic review</td>
<td align="center" valign="middle">17</td>
<td align="char" valign="middle" char=".">2019.2</td>
<td align="char" valign="middle" char=".">20.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cerebral infarction</td>
<td align="center" valign="middle">16</td>
<td align="char" valign="middle" char=".">2016.8</td>
<td align="char" valign="middle" char=".">6.1</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Therapy</td>
<td align="center" valign="middle">16</td>
<td align="char" valign="middle" char=".">2018.3</td>
<td align="char" valign="middle" char=".">22.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Acute ischemic stroke</td>
<td align="center" valign="middle">15</td>
<td align="char" valign="middle" char=".">2018.4</td>
<td align="char" valign="middle" char=".">11.9</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">Brain</td>
<td align="center" valign="middle">78</td>
<td align="char" valign="middle" char=".">2015.1</td>
<td align="char" valign="middle" char=".">22.4</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Ischemic stroke</td>
<td align="center" valign="middle">60</td>
<td align="char" valign="middle" char=".">2018.5</td>
<td align="char" valign="middle" char=".">15.3</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Model</td>
<td align="center" valign="middle">39</td>
<td align="char" valign="middle" char=".">2017.2</td>
<td align="char" valign="middle" char=".">14.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Ischemia</td>
<td align="center" valign="middle">31</td>
<td align="char" valign="middle" char=".">2014.4</td>
<td align="char" valign="middle" char=".">11.4</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Neurogenesis</td>
<td align="center" valign="middle">29</td>
<td align="char" valign="middle" char=".">2017.0</td>
<td align="char" valign="middle" char=".">16.4</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Neurotrophic factor</td>
<td align="center" valign="middle">22</td>
<td align="char" valign="middle" char=".">2014.9</td>
<td align="char" valign="middle" char=".">25.8</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cerebral artery occlusion</td>
<td align="center" valign="middle">21</td>
<td align="char" valign="middle" char=".">2017.3</td>
<td align="char" valign="middle" char=".">13.3</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Proliferation</td>
<td align="center" valign="middle">19</td>
<td align="char" valign="middle" char=".">2016.7</td>
<td align="char" valign="middle" char=".">17.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cell</td>
<td align="center" valign="middle">18</td>
<td align="char" valign="middle" char=".">2017.3</td>
<td align="char" valign="middle" char=".">15.5</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Angiogenesis</td>
<td align="center" valign="middle">18</td>
<td align="char" valign="middle" char=".">2017.6</td>
<td align="char" valign="middle" char=".">12.8</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Motor recovery</td>
<td align="center" valign="middle">15</td>
<td align="char" valign="middle" char=".">2015.2</td>
<td align="char" valign="middle" char=".">30.3</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">Expression</td>
<td align="center" valign="middle">88</td>
<td align="char" valign="middle" char=".">2016.2</td>
<td align="char" valign="middle" char=".">20.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Cerebral ischemia</td>
<td align="center" valign="middle">78</td>
<td align="char" valign="middle" char=".">2013.8</td>
<td align="char" valign="middle" char=".">22.2</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Artery occlusion</td>
<td align="center" valign="middle">77</td>
<td align="char" valign="middle" char=".">2013.9</td>
<td align="char" valign="middle" char=".">24.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Activation</td>
<td align="center" valign="middle">70</td>
<td align="char" valign="middle" char=".">2016.6</td>
<td align="char" valign="middle" char=".">21.6</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Focal cerebral ischemia</td>
<td align="center" valign="middle">46</td>
<td align="char" valign="middle" char=".">2015.7</td>
<td align="char" valign="middle" char=".">20.7</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Injury</td>
<td align="center" valign="middle">46</td>
<td align="char" valign="middle" char=".">2017.0</td>
<td align="char" valign="middle" char=".">15.2</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Rapid tolerance</td>
<td align="center" valign="middle">27</td>
<td align="char" valign="middle" char=".">2014.8</td>
<td align="char" valign="middle" char=".">27.9</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Pretreatment</td>
<td align="center" valign="middle">25</td>
<td align="char" valign="middle" char=".">2015.5</td>
<td align="char" valign="middle" char=".">30.0</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Mouse</td>
<td align="center" valign="middle">20</td>
<td align="char" valign="middle" char=".">2014.6</td>
<td align="char" valign="middle" char=".">20.9</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Receptor</td>
<td align="center" valign="top">18</td>
<td align="char" valign="top" char=".">2014.7</td>
<td align="char" valign="top" char=".">24.8</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Reperfusion</td>
<td align="center" valign="top">17</td>
<td align="char" valign="top" char=".">2014.1</td>
<td align="char" valign="top" char=".">23.0</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Finally, the keywords were sorted by the average number of citations. The smaller the average number of citations, the closer the color is to blue. The larger the average citation, the closer it is to yellow (<xref rid="fig6" ref-type="fig">Figure 6C</xref>). The results of keyword analysis by average citations showed that the three most-cited keywords were &#x201C;motor recovery, pretreatment, and rapid tolerance&#x201D; (see <xref rid="tab8" ref-type="table">Table 8</xref>).</p>
<p>Comparison analysis between each keyword cluster showed that keywords from Cluster 4 had the oldest average publication year but were the most cited. Keywords from the second cluster were the most recent but were the least cited (<xref rid="tab9" ref-type="table">Table 9</xref>).</p>
<table-wrap position="float" id="tab9">
<label>Table 9</label>
<caption>
<p>Analysis of keyword clusters.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top">Occurrence</th>
<th align="center" valign="top">Average publication year</th>
<th align="center" valign="top">Average citations</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Cluster 1</td>
<td align="char" valign="middle" char=".">27.6</td>
<td align="char" valign="middle" char=".">2016.8</td>
<td align="char" valign="middle" char=".">16.7</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 2</td>
<td align="char" valign="middle" char=".">68.6</td>
<td align="char" valign="middle" char=".">2017.3</td>
<td align="char" valign="middle" char=".">16.4</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 3</td>
<td align="char" valign="middle" char=".">31.8</td>
<td align="char" valign="middle" char=".">2016.5</td>
<td align="char" valign="middle" char=".">17.7</td>
</tr>
<tr>
<td align="left" valign="middle">Cluster 4</td>
<td align="char" valign="middle" char=".">46.5</td>
<td align="char" valign="middle" char=".">2015.2</td>
<td align="char" valign="middle" char=".">22.8</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussions" id="sec17">
<label>4.</label>
<title>Discussion</title>
<p>To conduct a bibliometric analysis of EA in patients with stroke, 440 papers published over the last 20&#x2009;years were reviewed. The number of publications has gradually increased annually. In the first 10&#x2009;years, starting from 2003, 89 papers were published, and in the last 10&#x2009;years, 351 papers were published. By 2020, more than 45 papers had been published annually. We believe that this is because EA has been extensively studied and is actively used clinically to treat stroke.</p>
<p>The field of Neurosciences had the most research, followed by the fields of Integrative Complementary Medicine, and Cell Biology. In the field of Neuroscience, research focusing on this mechanism has been actively conducted because of objective and quantitative measurements of the frequency and strength of EA stimulation (<xref ref-type="bibr" rid="ref12">Napadow et al., 2005</xref>).</p>
<p>Neural Regeneration Research journal had the most numerous publications, followed by Evidence-Based Complementary and Alternative Medicine, and Acupuncture in Medicine. The multiplication of studies in neuroscience is reflected by the published journals. EA treatment is a complementary medical method that has been actively studied.</p>
<p>China published the highest number of studies, followed by Korea and the United StatesIt appears that this is proportionally related to the fact that China is the center of worldwide TCM research. Analysis of clusters showed China and Australia, which recently conducted research in this field actively, was included in the same cluster. Australia conducted studies on the use of EA for the sequelae of stroke. In the early stages, the United States and Taiwan conducted highly cited and influential studies. United States has the highest medical expenditure of post stroke care per patient in the world (<xref ref-type="bibr" rid="ref1003">Rajsic et al., 2019</xref>), and in order to lower this social cost, complementary medicine has been actively researched. In the United States, there was early interest in the combination of Western and Eastern rehabilitation techniques to improve the effectiveness of rehabilitation treatment (<xref ref-type="bibr" rid="ref1004">Alexander et al., 2004</xref>). Appropriate intensity and frequency of EA intervention has been reported to show neuroprotection by up-regulation of the blood flow speed in the infarct site (<xref ref-type="bibr" rid="ref1005">Zhou et al., 2011</xref>) and meta-analysis of acupuncture combined with a conventional rehabilitation approach suggested acupuncture provided additional benefit to motor recovery compared to conventional rehabilitation approach alone. However, some clinical studies failed to demonstrate treatment effect of acupuncture/EA on stroke and inconsistency between studies about effect of EA on stroke remains major obstacle to actively apply EA in rehabilitation program for stroke. This may be the reason why research was actively conducted in the United States in the beginning but has been sluggish recently. Although researches on EA have been increased worldwide, international co-operation width and link strength of collaboration between nations were weak. One of the reasons for the lack of international collaboration might be differences in the frequency of use of acupuncture in clinical settings and controversies over the underlying mechanism of acupuncture. In order to facilitate the growth of the field and sustain high-quality work, researchers need to give effort to multi-national interaction and co-operation in the future. By affiliated institution, Fujian University of Traditional Chinese Medicine published the largest number of studies, followed by Guangzhou University of Chinese Medicine and Air Force Military Medical University. Chen Lidian and Tan Jing published the most papers, followed by Liu Weilin. The three most published authors were affiliated with Fujian University of Traditional Chinese Medicine and were included in author cluster 1, studying mainly the neuroprotective mechanism and anti-inflammatory effects (<xref ref-type="bibr" rid="ref7">Lan et al., 2013</xref>) of EA for stroke through animal model experiments. By analyzing the top authors, researchers from the same institution cooperated but lacked collaboration with other institutions, nations, or authors. Additional network composition is needed in the future to increase academic status and diversity.</p>
<p>Keyword analysis was performed to identify the research trends and contents of the published papers. The three oldest keywords by average publication year were &#x201C;neural regeneration, cerebral ischemia, and artery occlusion.&#x201D; In a previous study, an animal model of ischemic stroke created through the middle cerebral artery and internal carotid artery occlusion and reperfusion was used to verify the nerve regeneration effect of EA (<xref ref-type="bibr" rid="ref10">Ma et al., 2020</xref>). The three most recent keywords were &#x201C;autophagy, systematic review, and cognitive impairment.&#x201D; Studies on the neuroprotective and neuroplastic regulatory effects of EA are continuously in progress, and the autophagic effect of EA-related signal transduction pathway regulation is a recent research topic receiving attention. In clinical research, studies on the sequelae of stroke, such as cognitive disorders (<xref ref-type="bibr" rid="ref19">Xie et al., 2022</xref>), depression (<xref ref-type="bibr" rid="ref16">Wang et al., 2021</xref>), and rigidity (<xref ref-type="bibr" rid="ref1">Cai et al., 2017</xref>) are actively being conducted.</p>
<p>The published research keyword clusters were categorized according to &#x201C;neuroprotection,&#x201D; &#x201C;clinical rehabilitation,&#x201D; &#x201C;neuroplasticity,&#x201D; and &#x201C;pretreatment-induced tolerance.&#x201D; The first cluster included &#x201C;rat,&#x201D; &#x201C;apoptosis,&#x201D; and &#x201C;mechanism&#x201D; and was categorized as a &#x201C;neuroprotection&#x201D; topic. Neuroprotection focuses on minimizing additional damage of nerve cells after acute brain injury (<xref ref-type="bibr" rid="ref1006">Chamorro et al., 2021</xref>) and EA showed neuroprotective effects against acute brain damage by inducing cell apoptosis, anti-inflammation, and autophagocytosis. As our understandings of the mechanisms and pathology of stroke increases, neuroprotective strategies emerged as hopeful treatment since acute stroke in followed by secondary neuroinflammation and recent studies report neuroinflammation as a key determinant of stroke prognosis (<xref ref-type="bibr" rid="ref1007">Tao et al., 2020</xref>). Nonetheless, there has been no neuroprotective drugs with proven clinical efficacy. EA could display a promising neuroprotective property in stroke individual but additional studies are needed to further elucidate and validate its mechanism and effectiveness. The second cluster consisted of &#x201C;recovery,&#x201D; &#x201C;stimulation,&#x201D; &#x201C;rehabilitation,&#x201D; and &#x201C;cognitive impairment&#x201D; and the topic was categorized as &#x201C;clinical rehabilitation.&#x201D; Timely rehabilitation treatment from the acute stage of stroke seems to lower risk of physical disability and complication. Also, recent clinical research showed that enhanced functional recovery is possible even in the chronic stage of stroke after 6&#x2009;months (<xref ref-type="bibr" rid="ref1001">Zhao and Willing, 2018</xref>). Stroke sequelae include neurological and neuropsychological deficits. A human clinical study reported EA showed improvement of functional impairment of sequelae such as dysphagia (<xref ref-type="bibr" rid="ref6">Huang et al., 2020</xref>) and aphasia (<xref ref-type="bibr" rid="ref13">Shi et al., 2022</xref>) and improved neuropsychiatric sequelae following stroke, such as cognitive impairment and post-stroke depression (<xref ref-type="bibr" rid="ref16">Wang et al., 2021</xref>). In the third cluster, &#x201C;neurogenesis,&#x201D; &#x201C;neurotrophic factor,&#x201D; &#x201C;proliferation,&#x201D; and &#x201C;angiogenesis&#x201D; was included, and the topic was categorized as &#x201C;neuroplasticity.&#x201D; In the sub-acute and chronic stroke brain, voluntary healing occurs and this non-cure healing process happens through brain plasticity (<xref ref-type="bibr" rid="ref1001">Zhao and Willing, 2018</xref>). Neurogenesis, angiogenesis, and synaptic regeneration are important for voluntary neuroplasticity in the brain. Neuroplasticity modifies functional activity by learning through responses to stimulation and plays an important role in functional recovery when impairment occurs because of incomplete nerve cell regeneration. In animal experiments, EA showed regulatory effects on neuroplasticity by accelerating neurogenesis, inducing angiogenesis, and regulating neuroglial cells, such as astrocytes, oligodendrocytes, microglial cells, and neurotrophic factors (<xref ref-type="bibr" rid="ref24">Zhang et al., 2021</xref>). In the fourth cluster, &#x201C;expression,&#x201D; &#x201C;activation,&#x201D; &#x201C;injury,&#x201D; &#x201C;rapid tolerance,&#x201D; and &#x201C;pretreatment&#x201D; keywords were included, and the topic was categorized as &#x201C;pretreatment induced tolerance.&#x201D; EA pretreatment controls the cannabinoid system, oxidative stress, and growth factors and suppresses cell apoptosis, resulting in neuroprotective effects (<xref ref-type="bibr" rid="ref9">Li et al., 2012</xref>). Therefore, EA pretreatment can be used as a preventive and initial treatment strategy for patients at risk of ischemic stroke, and many studies have been conducted to prove this neuroprotective effect (<xref ref-type="bibr" rid="ref17">Wang et al., 2009</xref>). The research included in Cluster 4 focused mainly on verifying the stroke prevention and early neuroprotective mechanisms of EA pretreatment, and there have been almost no clinical studies to date.</p>
<p>Comparing through average publish year, cluster 4 &#x201C;EA pretreatment induced rapid tolerance&#x201D; studies were conducted in the past than the other clusters and also showed high average citation. Cluster 2, a &#x201C;clinical rehabilitation study,&#x201D; had a more recent average publication year, and the average citation rate was lower than that of the other clusters. Overall, animal model studies have mainly been conducted in the past, and we found that human-subject clinical studies have recently increased in animal experiments.</p>
<p>This study has several limitations. First, only the WOSCC was used as the extraction source for the research papers. WOSCC was used in this study because the database provides high quality and globally influential research papers and details of the research papers needed for bibliometric analysis. If other databases from East Asian countries that were actively studying the field were included as research sources, the results would have been more significant, but this study focus on database which is used worldwide. Second, the number and name of each cluster were discussed between two individual researchers and defined because individual subjectivity can intervene in the process of defining its properties, hindering objectivity; however, researchers may have different views. Considering the research trend on EA about stroke, mechanism of EA on neuroplasticity and its consequent motor recovery might be of interest of future research. Despite major advances in understanding pathophysiology and acute phase stroke intervention, not much progress has been made especially in chronic phase. Because timely intervention is crucial in stroke rehabilitation, EA can be a relatively convenient and cost-efficient intervention especially where Conventionally therapy is not readily available. To achieve this, large scale, high-quality, multicenter or multinational clinical trials must be further conducted to adequately measure the proper effect size. Additionally, analysis of the research trends in various TCM treatment methods, such as manual acupuncture, herbal medicine, and pharmacopucture for stroke could be conducted to provide insight into stroke treatment and rehabilitation.</p>
</sec>
<sec sec-type="conclusions" id="sec18">
<label>5.</label>
<title>Conclusion</title>
<p>Using WOSCC as a source, the research trends of 440 papers on EA as a treatment for stroke were analyzed using a bibliometric method, and the results were as follows:</p>
<list list-type="order">
<list-item>
<p>In the last 20&#x2009;years, published studies have gradually increased, and especially between 2019 and 2020, the number has more than doubled, indicating that research has been actively conducted until recently.</p>
</list-item>
<list-item>
<p>Studies have been conducted in the fields of neuroscience and complementary medicine.</p>
</list-item>
<list-item>
<p>China had the largest number of publications, followed by the United States and other East Asian countries, such as South Korea and Taiwan.</p>
</list-item>
<list-item>
<p>Fujian University of Traditional Chinese Medicine published the most research papers, whereas Chen Lidian and Tan Jing published the largest number of studies.</p>
</list-item>
<list-item>
<p>The keyword analysis indicated topics related to &#x201C;neuroprotection,&#x201D; &#x201C;clinical rehabilitation,&#x201D; &#x201C;neuroplasticity,&#x201D; and &#x201C;pretreatment-induced tolerance.&#x201D;</p>
</list-item>
</list>
</sec>
<sec sec-type="data-availability" id="sec19">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="sec20" sec-type="author-contributions">
<title>Author contributions</title>
<p>HC: Conceptualization, Data curation, Formal analysis, Investigation, Writing &#x2013; original draft. W-CS: Resources, Writing &#x2013; review &#x0026; editing. J-mK: Investigation, Writing &#x2013; original draft. HK: Methodology, Software, Writing &#x2013; review &#x0026; editing. J-HC: Supervision, Validation, Writing &#x2013; review &#x0026; editing. M-YS: Supervision, Validation, Writing &#x2013; review &#x0026; editing. W-SC: Conceptualization, Project administration, Supervision, Writing &#x2013; review &#x0026; editing.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="sec21">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.</p>
</sec>
<sec sec-type="COI-statement" id="sec22">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="sec100" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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