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Development of a new tool for stage identification of periodontal disease

Grant number: 16/07786-8
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): June 01, 2016
Effective date (End): December 31, 2016
Field of knowledge:Agronomical Sciences - Veterinary Medicine - Animal Clinics and Surgery
Principal Investigator:Marco Antonio Gioso
Grantee:Carla Pantarotto Boni
Host Institution: Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade de São Paulo (USP). São Paulo , SP, Brazil


Periodontal disease (PD) is the most prevalent disorder that affect cats and dogs. It is the damage of the periodontal attachment tissue (protection or support). PD is a chronic disease and during its evolution there is the emergence of several clinical findings, the diagnosis of PD is easily made by inspection of the oral cavity and dental calculus identification.However, measurement of the extent of periodontal lesion is controversial since there is not a simple and standardized method. So staging and grading PD is not easy. The extent of periodontal lesion can be measured by using a periodontal probe which evaluates the attachment loss level. The staging and classification of the PD is made according to the percentage of clinical attachment level loss, high percentages indicate a higher degree of severity of PD. However, periodontal disease causes many clinical signs that this classification system does not consider. Another alternative to determine the extent of periodontal lesion is to evaluate the clinical sings caused by PD during its evolution: for example, the gingiva colour, but this assessment is made subjectively.As a result of the absence of an objective and standardized method in dental practice routine, periodontal disease classification is often dependent on personal impressions. Given these facts, the aim of this project is to create a PD classification system using the parameters evaluated in oral physical examination, therefore be possible to determine the DP staging precisely. In addition to providing a standardized diagnosis, this project has applicability to trace a profile that can be used as a predictive tool for clinical cases of PD.

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