Integrating Unified Medical Language System and Kleinberg’s Burst Detection Algorithm into Research Topics of Medications for Post-Traumatic Stress Disorder

摘要

Background: The treatment of post-traumatic stress disorder (PTSD) has long beena challenge because the symptoms of PTSD are multifaceted. PTSD is primarily treatedwith psychotherapy and medication, or a combination of psychotherapy and medication. Thepresent study was designed to analyze the literature on medications for PTSD and explorehigh-frequency common drugs and low-frequency burst drugs by burst detection algorithmcombined with Unified Medical Language System (UMLS) and provide references fordeveloping new drugs for PTSD.Methods: Publications related to medications for PTSD from 2010 to 2019 were identifiedthrough PubMed, Web of Science Core Collection, and BIOSIS Previews. SemRep andSemRep semantic result processing system were performed to extract the set of drugconcepts with therapeutic relationship according to the semantic relationship of UMLS.Kleinberg’s burst detection algorithm was applied to calculate the burst weight index ofdrug concepts by a Java-based program. These concepts were sorted according to thefrequency and the burst weight index.Results: Four hundred and fifty-nine treatment-related drug concepts were extracted. Thedrug with the highest burst weight index was “Psilocybine”, a hallucinogen, which was morelikely to be a hotspot for the pharmacotherapy of PTSD. The highest frequency concept was“prazosin”, which was more likely to be the focus of research in the medications for PTSD.Conclusion: The present study assessed the medication-related literature on PTSD treatment, providing a framework of burst words detection-based method, a baseline of information for future research and the new attempt for the discovery of textual knowledge. Thebibliometric analysis based on the burst detection algorithm combined with UMLS hasshown certain feasibility in amplifying the microscopic changes of a specific researchdirection in a field, it can also be used in other aspects of disease and to explore the trendsof various disciplines.