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A plea for the development of an universally accepted modular tooth wear evaluation system

Overview of attention for article published in BMC Oral Health, November 2016
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Title
A plea for the development of an universally accepted modular tooth wear evaluation system
Published in
BMC Oral Health, November 2016
DOI 10.1186/s12903-016-0309-6
Pubmed ID
Authors

P. Wetselaar, A. Faris, F. Lobbezoo

Abstract

Tooth wear is considered an increasing oral health problem. Due to its multifactorial nature, recognizing and diagnosing of tooth wear is difficult but nevertheless important. Over the years, a wide variety of evaluation systems has been developed, yet none of them is universally accepted. This has implications for both research and clinical practice. This paper describes an in-depth analysis of four commonly used tooth wear evaluation systems, namely, the Eccles index, the Tooth Wear Index, the Lussi index, and the Basic Erosive Wear Examination. Comparing those systems revealed that despite several similarities, they differ considerably from each other. Notably, all four systems have their specific advantages and disadvantages. However, neither one of them meets all necessary characteristics of a hypothetical, broadly applicable tooth wear evaluation system. In fact, it is not realistic that a single system qualifies for all purposes (for example, diagnosing or monitoring individual patients, performing epidemiological studies, etc.). As a potentially feasible solution for this issue, the development of an evaluation system is recommended that consists of multiple, coherent modules, which cover different purposes.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 7 14%
Student > Master 6 12%
Student > Ph. D. Student 5 10%
Professor > Associate Professor 3 6%
Student > Bachelor 2 4%
Other 6 12%
Unknown 20 41%
Readers by discipline Count As %
Medicine and Dentistry 23 47%
Agricultural and Biological Sciences 2 4%
Engineering 1 2%
Unknown 23 47%