Trauma
Amanjyot K. Bains, DDS (she/her/hers)
Pediatric dental resident
NYU- Langone pediatric residency San Diego site
San Diego, California, United States
Jacy Stauffer, DMD
Oregon Health & Science University
Portland, Oregon, United States
Daniel J. Kane, DMD, MA
Program Director
NYU Langone Hospitals
Brooklyn, New York, United States
Wai-Yin Chan, DMD
NYU Langone Pediatric Dentistry- San Diego, CA
San Diego, California, United States
Purpose: The objective of the study was to vest a graph database and compile the available evidence on permanent tooth avulsion injuries. It also identified the areas that need further research and could serve as a framework to capture and organize data related to avulsion injuries.
Methods: The study was conducted using a systematic review of the literature to organize evidence-related patterns and outcomes of permanent teeth avulsion in the pediatric population. Medline, PubMed, and Scopus were searched with the following key terms: "Avulsion” , "dental" ,“injury", " in” ,“permanent teeth” with the additional filters for years (2000 to 2021) and language (English). The final inclusion criteria included: age from 0 to 18 years; follow up period of 18 months; and discussion on intervention. The exclusion criteria included meta-analysis studies.
Results: After initial review of 2,453 studies, 32 studies were included (Medline: 24, PubMed: 4, Scopus: 4). In the final review, eight studies qualified for the systematic review and analysis (Medline: 8, PubMed:1 (duplicate study), Scopus: none). Six studies were included(unable to get original data for two studies) for final evidence mapping. A traversal graph of patterns and outcomes was designed. A node-to-node relationship was established and allocated with edge-probabilities reported from the literature. Conclusions: Mapping of clinical patterns and outcomes using traversal graph patterns is a feasible method to define and quantify outcomes for dental avulsion injuries in permanent teeth. It identified areas that need focused research and has the potential to provide predictive knowledge for clinical decision-making.