Salivary biomarkers in diabetes mellitus diagnostics: A bibliometric analysis

Diabetes mellitus (DM) is a prevalent chronic disease worldwide, requiring accurate diagnosis and effective treatment for improved patient outcomes. Traditional glucose monitoring methods, such as venous blood sampling and fingertip glucose tests, are invasive and inconvenient. Salivary analysis, being noninvasive, easily accessible, and abundant, offers a promising diagnostic and monitoring alternative for DM. This study systematically assesses the current status and emerging trends of salivary analysis technology in DM research using bibliometric analysis.

This study analyzed 482 publications on DM-related salivary analysis spanning from 1990 to 2023, sourced from the Web of Science Core Collection (WoSCC). Using VOSviewer, CiteSpace, and Pajek for co-occurrence and network visualization, we examined key contributors, influential countries and institutions, prominent journals, and thematic trends within the research domain. These tools enabled a comprehensive understanding of the evolving applications and research focuses of salivary analysis in DM.

From 1990 to 2023, DM-related salivary analysis research has shown a steady annual increase, particularly focusing on biomarkers such as glucose and C-reactive protein (CRP). Significant emphasis has been placed on advancing biosensors for salivary-based glucose monitoring and analyzing inflammatory responses. This study identifies key authors, pivotal research institutions, and central journals contributing to the field, shedding light on emerging trends and current research emphases.

Salivary analysis represents a promising noninvasive approach for the diagnosis, monitoring, and management of DM. Despite the study's focus on data from the WoSCC, the findings provide valuable insights into the current state and future potential of this field. Future research should prioritize the development of advanced portable sensor technologies for salivary glucose monitoring and CRP-based biosensors, which have the potential to predict the progression of type 2 diabetes mellitus through inflammatory biomarkers. These innovations could significantly enhance diagnostic accuracy, patient convenience, and personalized therapeutic strategies in DM management.