Visual analysis of sepsis-related acute respiratory distress syndrome based on knowledge graph of VOSviewer and CiteSpace
Objective To analyze the changes of research hotspots in sepsis-related acute respiratory distress syndrome(ARDS)in the past decade.Methods Original articles on sepsis-related ARDS published from January 2014 to June 2024 were retrieved from the Web of Science core database.Visual analysis was conducted using knowledge graph of VOSviewer and CiteSpace.Its research hotspots and evolving trends were focused.At the same time,the relationships between researchers,research institutions,and co-citations were analyzed.The ClinicalTrial.gov website was checked.A cross-sectional analysis of registered relevant studies was conducted.The research objectives and possible results were clarified.Results Over the past 10 years,the numbers of publications on sepsis-related ARDS were increased annually and showed a wide geographical distribution.In total,1,319 articles were included in the bibliometric analysis.The search Kappa consistency is 98％."Acute respiratory distress syndrome,""sepsis,"and"acute lung injury"were the most common keywords.They appeared 736,649,and 415 times,respectively.The total link strengths were 5052,4362,and 3005,respectively."Artificial intelligence"and"endophenotype"also showed a growing trend.Related research topics focused on precision management,model establishment and validation,and potential subtyping identification.A total of 39 related clinical trials have been registered on ClinicalTrial.gov.These trials mainly aimed to provide new ideas and evidence for the diagnosis and treatment of sepsis-related ARDS.It was also expected to provide diagnostic decision-making assistance and establish the predictive models.Conclusions The research focus on sepsis-related ARDS has gradually shifted to the exploration of subtypes and artificial intelligence-assisted decision-making.The registered relevant clinical trials have been gradually completed.It will provide the support for the precision management of the disease.
NETL
NSTL
万方数据
