A bibliometric analysis of the application of procalcitonin in patients in the intensive care unit.

Background: Patients in the intensive care unit (ICU) often have serious infections, and anti-infection treatment is vital for these patients. Procalcitonin (PCT) is often used to identify bacterial infections and monitor the effectiveness of anti-infection treatments. This study aims to analyze the current research hotspots of the application of PCT in ICU patients, and to suggest future research directions.

Methods: The Science Citation Index Expanded (SCI-EXPANDED) database in the Web of Science Core Collection (WOSCC) was used as the data source to search literature from 1995 to February 6, 2021. The search strategy was subject term = procalcitonin AND Web of Science categories = Critical Care Medicine. Using CiteSpace software, literature on the application of PCT in ICU patients was analyzed.

Results: A total of 1,243 papers, including 665 (53.5%) original articles, 87 (7.0%) reviews, 93 (7.5%) letters, 297 (23.9%) conference abstracts, and 101 (8.1%) other articles, were analyzed. The citation frequency was 40,442, the h-index was 96, and the average number of citations per item was 32.54. Research was mainly from the United States, Germany, France, and Spain, amongst others. The research institutions were mainly Univ Basel Hosp, Univ Pittsburgh, and Univ Hosp Geneva. Authors including Schuetz P made more contributions. Critical Care Medicine, Intensive Care Medicine, and Critical Care were important journals in this field of research. The keywords with the highest frequency were PCT, sepsis, and infection, and the more central ones were PCT, inflammation, septic shock, and C-reactive protein. The keywords with the strongest citation bursts were PCT, cytokine, and serum.

Conclusions: Papers are mainly published in critical care medical journals. The countries, institutions, and authors that carry out research are relatively limited. The current hot spots are still inflammation, infection, and shock, especially the management and prognosis prediction of critically ill patients.