Development and testing of a mobile application for periodontal diagnosis.


Journal

Journal of clinical and experimental dentistry
ISSN: 1989-5488
Titre abrégé: J Clin Exp Dent
Pays: Spain
ID NLM: 101603132

Informations de publication

Date de publication:
Mar 2022
Historique:
received: 02 01 2022
accepted: 06 02 2022
entrez: 23 3 2022
pubmed: 24 3 2022
medline: 24 3 2022
Statut: epublish

Résumé

The new classification of periodontal diseases introduced a new set of rules for periodontal diagnosis. The objective of this study was to develop and test the implementation of a mobile device application for periodontal diagnosis. An integral algorithm that included periodontal health / related conditions and periodontitis was developed based on the classification of periodontal diseases of 2018. A mobile application for Android implementing the algorithm was developed using the framework MIT App Inventor. Once the app was debugged for glitches and performance of the algorithm, it was tested with 20 voluntary dental students, postgraduate students of periodontology, and professors in an academic setting. Participants were asked to determine the diagnosis of 10 predetermined clinical cases using two strategies: diagnosis based on knowledge and with the PerioSmart app. The results were tabulated, and the concordance rate was calculated. In general, the use of the PerioSmart application had a better concordance rate than diagnosis based on knowledge. In particular, the mobile app was better in determining the type of diagnosis, stage/grade of periodontitis, and with better efficiency. The mobile device application demonstrated efficiency and good concordance rate and therefore can improve the periodontal diagnosis.

Sections du résumé

Background UNASSIGNED
The new classification of periodontal diseases introduced a new set of rules for periodontal diagnosis. The objective of this study was to develop and test the implementation of a mobile device application for periodontal diagnosis.
Material and Methods UNASSIGNED
An integral algorithm that included periodontal health / related conditions and periodontitis was developed based on the classification of periodontal diseases of 2018. A mobile application for Android implementing the algorithm was developed using the framework MIT App Inventor. Once the app was debugged for glitches and performance of the algorithm, it was tested with 20 voluntary dental students, postgraduate students of periodontology, and professors in an academic setting. Participants were asked to determine the diagnosis of 10 predetermined clinical cases using two strategies: diagnosis based on knowledge and with the PerioSmart app. The results were tabulated, and the concordance rate was calculated.
Results UNASSIGNED
In general, the use of the PerioSmart application had a better concordance rate than diagnosis based on knowledge. In particular, the mobile app was better in determining the type of diagnosis, stage/grade of periodontitis, and with better efficiency.
Conclusions UNASSIGNED
The mobile device application demonstrated efficiency and good concordance rate and therefore can improve the periodontal diagnosis.

Identifiants

pubmed: 35317291
doi: 10.4317/jced.59338
pii: 59338
pmc: PMC8916594
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e269-e273

Informations de copyright

Copyright: © 2022 Medicina Oral S.L.

Déclaration de conflit d'intérêts

Conflicts of interest Doctor Botero and Velasquez are full time professors at the Universidad de Antioquia. The rest of the authors have nothing to declare.

Références

Periodontol 2000. 2020 Oct;84(1):14-34
pubmed: 32844416
J Clin Periodontol. 2020 Nov;47(11):1362-1370
pubmed: 32886408
Periodontol 2000. 2020 Oct;84(1):202-214
pubmed: 32844412
Indian J Ophthalmol. 2021 Jun;69(6):1491-1497
pubmed: 34011726
J Periodontol. 2018 Jun;89 Suppl 1:S74-S84
pubmed: 29926944
BMC Med Educ. 2021 Feb 22;21(1):121
pubmed: 33618685
J Periodontol. 2018 Jun;89 Suppl 1:S173-S182
pubmed: 29926951
J Clin Periodontol. 2019 Apr;46(4):398-405
pubmed: 30883878

Auteurs

Luisa-María Sánchez-Otálvaro (LM)

Facultad de Odontología, Universidad de Antioquia, Calle 70 No. 52-21, Medellín-Colombia.

Yesid Jiménez-Rivero (Y)

Sistemas Embebidos e Inteligencia Computacional SISTEMIC, Facultad de Ingeniería. Universidad de Antioquia, Calle 70 No. 52-21, Medellín-Colombia.

Ricardo-Andrés Velasquez (RA)

Facultad de Odontología, Universidad de Antioquia, Calle 70 No. 52-21, Medellín-Colombia.

Javier-Enrique Botero (JE)

Facultad de Odontología, Universidad de Antioquia, Calle 70 No. 52-21, Medellín-Colombia.

Classifications MeSH