| Grant number: | 17/01382-5 |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| Start date: | June 01, 2017 |
| End date: | November 30, 2018 |
| Field of knowledge: | Health Sciences - Speech Therapy |
| Agreement: | Coordination of Improvement of Higher Education Personnel (CAPES) |
| Principal Investigator: | Maria Inês Pegoraro Krook |
| Grantee: | Ana Flávia Rodrigues da Silva |
| Host Institution: | Hospital de Reabilitação de Anomalias Craniofaciais (HRAC). Universidade de São Paulo (USP). Bauru , SP, Brazil |
Abstract Objective: Verify the relationship between measures of maxillary arch before primary palatoplasty and the speech results of patients with unilateral cleft lip and palate. Methodology: Patients with operated unilateral cleft lip and palate, whose compose the data base of HRAC/USP Florida Project of HRAC / USP will be included in the present study after the analysis of the following selection criteria: present with speech samples audiorecorded between the ages 4 and 6 years and 3D-digitalized dental casts made pre-primary palatoplasty. The speech samples will be judged by three experienced speech pathologists, for the occurrence of hypernasality (absence and presence with mild, moderate and severe degrees). Also the following measures of the maxillary arch will be made: a) intercanine distance, b) intertuberosity distance, c) anteroposterior length, d) posterior cleft width, d) greater and minor cleft segment, and cleft área. For the analysis of the results, patients will be divided into eight groups, considering the palatal surgical technique (von Langenbeck or Furlow) and the surgeon who has operated that palate (out of four). The intra-rater agreement of the perceptual assessment of nasality based on the recorded samples, and the inter-raters agreement of maxillary arch measures will be calculated using the Intraclass Correlation Coefficient Test (ICC). The comparison between the speech results and the maxillary arch measurements will be performed by multivariate analysis by linear regression. (AU) | |
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