Friday, June 23, 2017

A Novel Evidence-Based Periodontal Prognosis Model

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Abstract

Objective

Patients with periodontal disease and the dental professionals responsible for their care want to know which teeth are expected to respond favorably to periodontal treatment and which teeth are likely to be lost in the short and long term. A number of different periodontal prognosis systems have been previously proposed but do not consider important patient-level factors, such as smoking and diabetic control, in the calculation of the expected outcome and often use subjective measures that introduce potential inaccuracies. The aim of this report is to translate the best available evidence on periodontal prognosis into a clinical model to facilitate decision-making and improve patient outcomes.

Methods

Criteria for an ideal prognostic system were proposed and used to assess the previously reported models. With an emphasis on the inclusion of patient-level modifiers (PLMs) and the exclusive use of objective parameters, a new evidence-based model was developed.

Results

This report proposes a new tooth-level prognosis model that uses 9 evidence-based quantifiable parameters to provide a prognosis of secure, doubtful, poor, or irrational to treat. Six tooth-level risk predictors (bone loss:age, pocket depth, furcation involvement, infrabony defects, anatomical factors, and mobility) and 3 PLMs (smoking, diabetes, and bleeding on probing) are used to determine the expected course of disease with specific reference to the suitability of the tooth for future dental treatment.

Conclusions

PLMs must be considered when determining the prognosis of a tooth with periodontal disease. The model proposed in this report is based on the best available evidence for factors affecting tooth survival and has been designed to be as simple and objective as possible to facilitate its adoption in clinical practice. It will be retrospectively and prospectively validated to determine its ability to accurately predict the course of disease.

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