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Early tooth loss after periodontal diagnosis : development and validation of a clinical decision model

2021-02Contribution to journal Open access
http://hdl.handle.net/10400.26/58718
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Authors

Santos, Francisco
Beato, Frederico
Machado, Vanessa
Proença, Luís
Mendes, José João
Botelho, João

Advisor(s)

Abstract(s)

The aim of this study was to develop and validate a predictive early tooth loss multivariable model for periodontitis patients before periodontal treatment. A total of 544 patients seeking periodontal care at the university dental hospital were enrolled in the study. Teeth extracted after periodontal diagnosis and due to periodontal reasons were recorded. Clinical and sociodemographic variables were analyzed, considering the risk of short-term tooth loss. This study followed the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines for development and validation, with two cohorts considered as follows: 455 patients in the development phase and 99 in the validation phase. As a result, it was possible to compute a predictive model based on tooth type and clinical attachment loss. The model explained 25.3% of the total variability and correctly ranked 98.9% of the cases. The final reduced model area under the curve (AUC) was 0.809 (95% confidence interval (95% CI): 0.629–0.989) for the validation sample and 0.920 (95% CI: 0.891–0.950) for the development cohort. The established model presented adequate prediction potential of early tooth loss due to periodontitis. This model may have clinical and epidemiologic relevance towards the prediction of tooth loss burden.

Description

Keywords

periodontal disease periodontitis early tooth loss predictive model risk factors oral health public health epidemiology

URI

http://hdl.handle.net/10400.26/58718

Pedagogical Context

Citation

Santos F, Beato F, Machado V, Proença L, Mendes JJ, Botelho J. Early Tooth Loss after Periodontal Diagnosis: Development and Validation of a Clinical Decision Model. International Journal of Environmental Research and Public Health. 2021; 18(3):1363. https://doi.org/10.3390/ijerph18031363

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Publisher

MDPI

DOI

10.3390/ijerph18031363

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EM - Artigos Científicos

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