Methodological review uncovers risks of bias in rhinology database research, highlighting the need for study design expertise and platform awareness.
Key Points
To examine methodological pitfalls, unrecognized biases, and analytical limitations associated with the rapid adoption of the TriNetX database platform in rhinology research.
Narrative review of author experiences and methodological analyses of rhinology abstracts presented at the 2026 American Rhinologic Society spring meeting.
Qualitative evaluation of platform-specific features, built-in statistical models, and common confounding biases inherent to large electronic health record networks.
Over 10% of research abstracts at the 2026 American Rhinologic Society spring meeting utilized the TriNetX platform.
Widespread reliance on automated statistical outputs without rigorous consideration of platform logic regularly creates hidden biases and misleading conclusions.
Effective clinical database research requires dedicated interdisciplinary expertise spanning clinical rhinology, formal study design, and platform-specific data limitations.