Computer-assisted periodontal classification vs manual classification among dental students: a comparative pilot...

Area of Science:

• Dental diagnostics
• Periodontology
• Digital health applications

Background:

• Accurate classification of periodontal diseases is crucial for effective treatment planning.
• Dental students require robust diagnostic tools to master complex classifications like the 2017 periodontal disease criteria.
• Variability in diagnostic accuracy among students necessitates supportive technologies.

Purpose of the Study:

• To evaluate the efficacy of computer-assisted periodontal diagnosis in enhancing diagnostic accuracy and consistency among dental students.
• To compare the performance of a digital diagnostic tool against traditional manual classification methods.
• To assess the impact of technology on the interpretation of the 2017 classification of periodontal diseases.

Main Methods:

• Final year dental students from two institutions were recruited and randomized into digital (computer-assisted) and manual diagnosis groups.
• Participants classified 48 periodontal cases each, with diagnoses validated against a gold standard set by experienced periodontists.
• A newly developed software facilitated computer-assisted diagnosis for one group, while the other used manual methods.

Main Results:

• The computer-assisted group achieved higher accuracy rates across various diagnostic parameters, including extent of gingivitis (82% vs 50%), stage of periodontitis (71% vs 56%), and overall periodontitis diagnosis (43% vs 30%).
• Significant improvements in diagnostic accuracy were observed for the extent and staging of periodontitis when using the digital tool.
• While some parameters showed modest gains (e.g., grade of periodontitis: 67% vs 62%), the digital approach generally outperformed manual classification.

Conclusions:

• Computer-assisted periodontal diagnosis serves as a valuable support tool for dental practitioners, enhancing diagnostic accuracy.
• The digital software demonstrated particular effectiveness in improving the accuracy of periodontitis extent and staging classifications.
• Implementing such technologies can lead to more consistent and precise diagnoses of periodontal diseases in clinical and educational settings.