Treatment on patients with spastic cerebral palsy in the past 30 years: A systematic review and bibliometric analysis

Abstract

Background: Over the past 30 years, treatments from different disciplines have been applied to spastic cerebral palsy (SCP). However, few bibliometric studies have been conducted to date. This study explored the knowledge base, emerging hotspots, and future trends related to SCP treatment research using bibliometric analysis.

Methods: Publications on SCP treatment included in the Web of Science Core Collection database between 1990 and 2020 were retrieved, and Medical Subject Headings terms were extracted from PubMed. Online bibliometric analysis website (http://bibliometric.com/), 2 pieces of software called "CiteSpace" and "VOSViewer" were used for quantitative analysis and knowledge map establishment.

Results: A total of 1668 papers were retrieved from 1990 to 2020. The number of publications has increased annually. Developmental Medicine and Child Neurology is the most productive and the highest co-cited journal. The United States has been the largest contributor. Vrije Universiteit Amsterdam ranked first in the number of papers published among institutions that have conducted correlational research. Becher JG and Graham HK should be considered scholars who have made outstanding contributions. The knowledge base of the SCP treatment research field is thoughtfully constructed to promote understanding of the field.

Conclusion: This bibliometric study identified global achievements, research hotspots, and trends of SCP treatment. They provide insights into the research field and valuable information for future scientific research and clinical treatment.

Figure 1.

The annual number of publications. Horizontal coordinate: year; vertical coordinate: number of publications; blue line: annual number of publications.

Figure 2.

Growth trends of the top 10 contributing countries. Horizontal coordinate: year; vertical coordinate: number of publications; color: Country; area of color: number of publications.

Figure 3.

The network of cooperation between countries. Color block: Country; area of color block: number of publications; line between different color blocks: the presence of cooperation.

Figure 4.

The network of keywords co-occurrence. Each circle represents a keyword; the larger the area of the circle; the more often this keyword appears, and the same color between different circles means that these keywords usually appear together, probably on the same research topic, and thus can be defined as a cluster.

Figure 5.

The network of co-citation clusters. Each title is a reference, and the relevance of each title is similar or different in color. The same color indicates high relevance, probably for the same research topic, and thus can be defined as a cluster.

Figure 6.

Top 29 keywords with the strongest citation bursts. Year: the first occurrence of the keyword; strength: the larger the value, the stronger the emergence of the keyword; begin: the start time of the keyword burst; end: the end time of the keyword burst. The blue line represents the time interval and the red line represents the time of the keyword burst.