Diagnostic reproducibility of the 2018 Classification of Gingival Recessions: Comparing photographic and in‐person diagnoses

As digital diagnostics evolve to facilitate clinical diagnostic measurement, we aimed to assess the effectiveness of intraoral photography for diagnosing gingival recession defects (GRD) according to the 2018 Classification of GRD, compared to traditional clinical examination. Standardized photographs of thirty-four GRD cases were captured. Four masked operators evaluated the same gingival recessions twice in a clinical setting and twice using photographs. Measurement repeatability within and between operators was calculated for both clinical and photographic settings, and the two settings were compared. Continuous measurements such as recession depth and keratinized tissue width, as well as the evaluation of interproximal attachment height (recession type), showed excellent agreement both clinically and photographically. Agreement was lower for gingival thickness and the detectability of tooth anatomical landmarks, such as the cemento-enamel junction and the presence of root steps. Overall, the agreement between chairside and photographic evaluations was generally good, but lower when evaluating tooth anatomical landmarks. The variables composing the 2018 Classification of GRD are reproducible in both clinical and photographic settings, with comparable levels of agreement. However, there was consistently worse agreement for gingival thickness and when evaluating tooth anatomical landmarks.

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Publication Details

Journal
Journal of Periodontology
Published
2024-08-26
DOI
https://doi.org/10.1002/jper.24-0173
Citations
1
Primary Topic
Digital Imaging in Medicine
Type
article
Field-Weighted Citation Impact
0.54
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article

Diagnostic reproducibility of the 2018 Classification of Gingival Recessions: Comparing photographic and in‐person diagnoses

Francesco Cairo, Alessandra Bandel, Giovanpaolo Pini Prato, Debora Franceschi et al.
1 citations
Journal of Periodontology
Digital Imaging in Medicine
0.54
article

Diagnostic reproducibility of the 2018 Classification of Gingival Recessions: Comparing photographic and in‐person diagnoses

Francesco Cairo, Alessandra Bandel, Giovanpaolo Pini Prato, Debora Franceschi, Maria Di Martino, Leandro Chambrone, Riccardo Di Gianfilippo, Walter Castelluzzo, Luigi Barbato, Cláudio Mendes Pannuti
article en
1 citations

Abstract

As digital diagnostics evolve to facilitate clinical diagnostic measurement, we aimed to assess the effectiveness of intraoral photography for diagnosing gingival recession defects (GRD) according to the 2018 Classification of GRD, compared to traditional clinical examination. Standardized photographs of thirty-four GRD cases were captured. Four masked operators evaluated the same gingival recessions twice in a clinical setting and twice using photographs. Measurement repeatability within and between operators was calculated for both clinical and photographic settings, and the two settings were compared. Continuous measurements such as recession depth and keratinized tissue width, as well as the evaluation of interproximal attachment height (recession type), showed excellent agreement both clinically and photographically. Agreement was lower for gingival thickness and the detectability of tooth anatomical landmarks, such as the cemento-enamel junction and the presence of root steps. Overall, the agreement between chairside and photographic evaluations was generally good, but lower when evaluating tooth anatomical landmarks. The variables composing the 2018 Classification of GRD are reproducible in both clinical and photographic settings, with comparable levels of agreement. However, there was consistently worse agreement for gingival thickness and when evaluating tooth anatomical landmarks.

Journal of PeriodontologyVol. 96(5)
Universidade de São Paulo (BR), Universidad El Bosque (CO), University of Michigan (US), Escola Superior de Saúde Egas Moniz (PT), Italian Society of Periodontology and Implantology (IT), University of Florence (IT), University of Pennsylvania (US)
Openalex Percentile: Top 30%
Digital Imaging in Medicine
0.54
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