Research hotspots and effectiveness of repetitive transcranial magnetic stimulation in stroke rehabilitation

Abstract

Repetitive transcranial magnetic stimulation, as a relatively new type of rehabilitation treatment, is a painless and non-invasive method for altering brain excitability. Repetitive transcranial magnetic stimulation has been widely used in the neurorehabilitation of stroke patients. Here, we used CiteSpace software to visually analyze 315 studies concerning repetitive transcranial magnetic stimulation for stroke rehabilitation from 1999 to 2019, indexed by Web of Science, to clarify the research hotspots in different periods and characterize the gradual process of discovery in this field. We found that four main points were generally accepted: (1) repetitive transcranial magnetic stimulation has a positive effect on motor function recovery in patients with subcortical stroke; (2) it may be more advantageous for stroke patients to receive low-frequency repetitive transcranial magnetic stimulation in the unaffected hemispheres than to receive high-frequency repetitive transcranial magnetic stimulation in affected hemisphere; (3) low-frequency repetitive transcranial magnetic stimulation has become a potential therapeutic tool for patients with non-fluent aphasia after chronic stroke for neurological rehabilitation and language recovery; and (4) there are some limitations to these classic clinical studies, such as small sample size and low test efficiency. Our assessment indicates that prospective, multi-center, large-sample, randomized controlled clinical trials are still needed to further verify the effectiveness of various repetitive transcranial magnetic stimulation programs for the rehabilitation of stroke patients.

Keywords: data visualization; motor recovery; rehabilitation; repetitive transcranial magnetic stimulation; stroke; stroke rehabilitation; transcranial magnetic stimulation.

Figure 1

Top 25 cited journals with the strongest citation bursts among 315 studies published from 1999 to 2019. (1) The Burst journals are the periodicals that were suddenly cited repeatedly at a certain time. (2) The figure shows the 25 most representative Burst journals covered by citations from 1991 to 2019 of 315 studies published from 1999 to 2019. (3) The red block represents a Burst year. The journals (solid line frame) with the earliest Bursts were BRAIN between 2004 and 2007, J NEUROPHYSIOL between 2004 and 2008, and NAT NEUROSCI between 2004 and 2014. Among them, NAT NEUROSCI spent the most time covering the research hotspot. In 2015–2019, the journals (virtual frame) with strong Bursts that appeared later were PLOS ONE and FRONT HUM NEUROSCI. (4) 1991 was the first year that a cited journal appeared. The strength represents the frequency intensity of the cited journal. ‘Begin’ and ‘End’ represent the time when the mutation of the cited journal began and ended, respectively.

Figure 2

Top 10 most cited journals among 315 studies published from 1999 to 2019.

Figure 3

Visualization of dual-map overlays of citing journals and cited journals of 315 studies published from 1999 to 2019. The colored curve indicates the path of citation, which originates from 11 fields of the citing journals on the left and points to 14 fields of the cited journals on the right.

Figure 4

Co-occurrence analysis of web of science categories of the 315 included studies. References are organized by year from left to right, and the color is arranged from cold in 1999 to warm in 2019. The color of the most central citation tree-ring represents the publication year of the reference.

Figure 5

Analysis of cited references in keyword clusters. The color of a cluster block indicates the year in which the co-citation relationship in the cluster first occurred. The occurrence in the blue block is earlier than that in green block, and that in the yellow block is later than that in the green block. By analogy, the size of a node represents the number of citations of a reference, journal, or author, and the color of the line represents the time of the first citation. The citation time color is from 1999 to 2019, from left to right. There are 11 types of clusters (#0–10).

Figure 6

Timeline view of co-citation analysis. (1) The timeline view shows the way that references are co-cited over time. (2) Different years correspond to different colors, and the longer the color line segment, the larger the time span of the citation. (3) The node represents the reference name. Larger nodes indicate higher frequencies of the citations. The lines represent the connections between the references. (4) The longer the color line segment, the larger the time span of the citation. (5) The cluster label on the right is the category of research hotspots involved in the citation.

Figure 7

Cluster of keywords from 315 included studies. The keyword clusters (LLR algorithm) were divided into eight categories (#0–7). Those without ‘#’ are high-frequency keywords.

Figure 8

Frequency of the top 20 keywords.

Figure 9

Top 10 keywords with the strongest citation bursts of the 315 included studies published from 1999 to 2019. “Unaffected hemisphere” was the keyword with the highest burst intensity. The year represents the earliest year of the keyword appearance. The strength stands for the citation strength. ‘Begin’ and ‘End’ represent the start and end time of the mutation, respectively.

Figure 10

Bibliographic coupling of the 315 included studies (cluster #0–12). The 13 categories were obtained via cluster analysis of the coupled references.

Figure 11

Top 6 countries with the strongest citation bursts among the 315 included studies. There are six major burst countries, including the United Kingdom, Germany, the USA, South Korea, and China. A Burst appeared in the United Kingdom from 2004 to 2008 and in China from 2017 to 2019. The year represents the earliest year that a Burst was seen in a country. The strength represents the intensity of the frequency of the country. ‘Begin’ and ‘End’ represent the beginning and ending time of the mutation, respectively.