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. 2022 Jan 20:20:27-32.
doi: 10.3290/j.ohpd.b2572997.

The Decision Tree for Clinical Management of Dentin Hypersensitivity. A Consensus Report

The Decision Tree for Clinical Management of Dentin Hypersensitivity. A Consensus Report

Gianna Maria Nardi et al. Oral Health Prev Dent. .

Abstract

Purpose: To reach a consensus on a consistent strategy to adopt when screening patients for the clinical management of dentin hypersensitivity.

Materials and methods: A panel consisting of members of the Advanced Technology in Oral Hygiene Sciences Academy (ATASIO) was formed to start a review process on dentin hypersensitivity (DH) and subsequently elaborate a decision tree to manage DH, from diagnosis to prognosis. The panel employed the RAND in their deliberations. After an initial systematic literature review, it became evident that a consensually validated protocol for the management of patients affected by dentin hypersensitivity has to be considered mandatory by all dental professionals. However, the outcome of the systematic review made it evident that the treatment options to be provided, as well as their prognosis and timing, had never been defined. The panel produced documents that addressed the topic and were subsequently used to generate a questionnaire. A workshop of expert dental professionals was organised to reach consensus on the main steps of the decision tree. Each member completed the questionnaire independently, and then a panel discussion was held to reach a consensus.

Results: A high level of agreement was reached regarding all the items on the questionnaire, and each of the clinical questions formulated was answered. A clinical decision threshold was created.

Conclusions: The dissemination of the information to a wide dental audience should commence upon publication of this consensus document. The authors hope that this consensus will become a model for the development of a dedicated protocol to manage DH.

Keywords: Italy; consensus; dentin hypersensitivity; diagnosis; prognosis.

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Figures

Fig 1
Fig 1
The RAND procedure.
Fig 2
Fig 2
The decision tree.

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