Maloney Brian, Honari Bahman, Polyzois Ioannis
Department of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, University of Dublin, Trinity College, Dublin, Ireland.
Department of Biostatistics, Dublin Dental University Hospital, University of Dublin, Trinity College, Dublin, Ireland.
Clin Exp Dent Res. 2025 Aug;11(4):e70178. doi: 10.1002/cre2.70178.
Periodontal disease is a prevalent condition in the general population. An updated classification system in 2018 introduced major changes to how this disease is classified and has implications for management. Research has demonstrated challenges in reaching periodontal diagnoses with this new system, prompting the need for the development of resources to assist clinicians.
This novel research aims to determine the level of accuracy and reliability in the assignment of case definitions of periodontal diseases according to the 2018 classification using a specialized mobile application.
Newly qualified dentists were recruited and assigned five random cases to classify according to the 2018 classification system. The collected data were analyzed to determine intra- and inter-examiner accuracy and consistency.
The overall accuracy of staging was 84%. The correct grade was assigned in 96% of cases. The extent was accurate in 97%. Localized disease was more reliably diagnosed than generalized forms of the condition. When accounting for stage, grade, and extent, examiners demonstrated 76% accuracy. Inter-examiner agreement was 62.5%.
There was a high level of diagnostic accuracy and consistency in periodontal disease diagnosis when diagnostic software was used as an adjunct to assigning case definitions. Dedicated software like "PerioBrain" has the potential to improve diagnostic accuracy. Further research is warranted to investigate the use of this application in a clinical setting and for didactic teaching of a student cohort.
牙周病在普通人群中普遍存在。2018年更新的分类系统对该疾病的分类方式进行了重大改变，并对治疗产生影响。研究表明，使用这一新系统进行牙周病诊断存在挑战，这促使需要开发资源来协助临床医生。
这项新研究旨在使用一款专门的移动应用程序，确定根据2018年分类法对牙周病病例定义进行分类时的准确性和可靠性水平。
招募新获得资格的牙医，并分配五个随机病例，让他们根据2018年分类系统进行分类。对收集到的数据进行分析，以确定检查者内部和检查者之间的准确性和一致性。
分期的总体准确率为84%。96%的病例被正确分级。范围的准确率为97%。局限性疾病比全身性疾病形式更易于可靠诊断。在考虑分期、分级和范围时，检查者的准确率为76%。检查者之间的一致性为62.5%。
当将诊断软件用作病例定义分类的辅助工具时，牙周病诊断具有较高的诊断准确性和一致性。像“PerioBrain”这样的专用软件有可能提高诊断准确性。有必要进行进一步研究，以调查该应用程序在临床环境中的使用情况以及对学生群体的教学用途。
