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


Journal

Quintessence international (Berlin, Germany : 1985)
ISSN: 1936-7163
Titre abrégé: Quintessence Int
Pays: Germany
ID NLM: 0342677

Informations de publication

Date de publication:
28 Nov 2023
Historique:
medline: 29 11 2023
pubmed: 21 7 2023
entrez: 21 7 2023
Statut: ppublish

Résumé

The objective of the study was to assess whether computer-assisted periodontal diagnosis can improve the accuracy and homogeneity of classification results obtained by dental students using the 2017 classification of periodontal diseases. All final year predoctoral dental students from two dental schools were invited to participate in the study. Participants who volunteered for the study were randomly divided into two groups for digital or manual diagnosis, and each participant classified 48 cases. A group of three experienced periodontists provided the reference or gold standard diagnosis. Overall, 27 students completed the evaluation of all cases; 14 students comprised the digital application group and 13 the manual group. The accuracy of the classification results compared with the gold standard committee was 82% for the digital group compared to 50% of the manual group in terms of the extent of gingivitis; 71% vs 56% for the stage of periodontitis; 67% vs 62% for grade of periodontitis; 76% vs 63% for extent of periodontitis; and 43% vs 30% for overall diagnosis accuracy of periodontitis cases respectively. Computer-assisted classification using newly developed software, within the boundaries of this study, was shown to be a sensible support tool for dental practitioners to use when diagnosing periodontal disease. This digital tool can the clinicians' accuracy of diagnosis primarily in the extent and staging of periodontitis.

Identifiants

pubmed: 37477040
pii: 4225983
doi: 10.3290/j.qi.b4225983
doi:

Types de publication

Randomized Controlled Trial Journal Article

Langues

eng

Pagination

792-801

Auteurs

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Classifications MeSH