Paradigm shifts in neonatal hypoxic-ischemic encephalopathy therapeutics: a four-decade bibliometric exploration of emerging therapeutic dimensions (1985-2024)

Abstract

Aim: Neonatal hypoxic-ischemic encephalopathy (HIE) remains a significant cause of neonatal morbidity and mortality worldwide, necessitating the exploration of effective therapeutic interventions. Current treatment strategies primarily involve therapeutic hypothermia (TH); however, its efficacy remains inconsistent. Research topics and trends in this area remain unclear as well. This study aimed to identify key research areas, collaboration networks, and emerging trends using bibliometric analysis tools.

Methods: A comprehensive analysis was conducted on 1,165 records from the Web of Science Core Collection (WoSCC) database. Various bibliometric techniques were employed, including coauthor analysis, co-occurrence analysis, co-citation analysis, reference clustering, and topic modeling, to visualize the knowledge structure and research dynamics in the HIE field.

Results: The findings revealed extensive collaboration networks among authors, institutions, and countries, highlighting global efforts to address this critical neonatal condition. Recent trends identified key research areas, including TH, mild systemic hypothermia, oxidative stress, biomarkers and signaling pathways, which are essential for advancing the understanding and treatment of HIE.

Conclusion: This study provides valuable insights into the current TH for neonates with HIE. Future research should focus on optimizing treatment approaches and evaluating long-term efficacy to enhance clinical applications.

Keywords: bibliometric analysis; biomarkers; emerging treatments; hypoxic-ischemic encephalopathy; signaling pathways; therapeutic hypothermia.

Figure 1

Search strategy and analysis flowchart for therapeutic hypothermia in neonatal hypoxic ischemic encephalopathy.

Figure 2

Annual trends in publications and citations. The blue strips represent articles and the red lines represent citations. The horizontal coordinate represents the year, the left vertical coordinate represents the number of articles and the right vertical coordinate represents the total number of citations.

Figure 3

Subject analysis using a double-graph superposition approach. Researches in this area involves many disciplines, showing the characteristics of multi-discipline research.

Figure 4

National co-authorship, institutional co-authorship, co-citation and journal co-citation network analysis. (A) Analysis of national co-authorship networks; (B) institutional co-authorship network analysis; (C) author co-citation network analysis; (D) journal co-citation network analysis.

Figure 5

Co-occurrence cluster network, co-occurrence time dimension network, cluster timeline view and citation burst analysis. (A) Cluster network analysis based on VOSviewer keyword co-occurrence. The size and color of the nodes represent the strength of the relationship between the frequency of keyword occurrence and the research topic. (B) Temporal dimension network analysis of keyword co-occurrence based on VOSviewer. The color of the nodes reflects the research activity of the keywords in different periods. Blue and green represent earlier studies. Red and yellow represent recent research. (C) Citespace keyword clustering timeline view. The redder the clustering label color, the closer the study time is to the present. (D) Citation burst (top 25 keywords).

Figure 6

Citation analysis based on vosviewer. (A,B) Key literature and author network in the field.

Figure 7

Thematic fishbone map and keyword cloud map based on thematic modeling. (A–N) used the LDA algorithm to model the topic of 1,165 articles, identified the 13 best topics, classified the content into four main research directions, and summarized the corresponding English topics for each direction.