The incidence of velopharyngeal insufficiency and oronasal fistula after primary palatal surgery with Sommerlad intravelar veloplasty: A retrospective study in Isfahan Cleft Care Team.

OBJECTIVES: This study was designed to determine the incidence of velopharyngeal insufficiency (VPI), oronasal fistula development and facial grimace in patients seen by Isfahan Cleft Care Team (ICCT) after primary Sommerlad intravelar veloplasty (SIVV). Furthermore the association of gender, cleft type and age at primary surgery with the incidence of hypernasality and fistula is determined. METHODS: A group of 40 patients with history of cleft palate with or without cleft lip were identified from the records of ICCT between 2011 and 2014. The main outcome measures were the incidence of hypernasality and fistula after primary palate repair with SIVV. Speech recordings were analyzed by consensus by two speech therapists according to the Cleft Audit Protocol for Speech- Augmented (CAPS-A), (Kappa = 82.4). Deciding whether or not to have a fistula was based on the oral examination videos. RESULTS: Severe and moderate hypernasality was observed in 42.5% of patients. Normal resonance and mild/borderline hypernasality was observed in 37.5% and 20% of patients, respectively. The frequency of fistulas was 7.5%. There was a significant association between hypernasality with cleft type and the age at primary surgery (p < 0.05). CONCLUSION: Significant progress has been made in the outcomes of the primary palate surgeries with the SIVV technique compared to the previous study in the ICCT.

Automatic identification of hypernasality in normal and cleft lip and palate patients with acoustic analysis of speech.

Hypernasality is seen in cleft lip and palate patients who had undergone repair surgery as a consequence of velopharyngeal insufficiency. Hypernasality has been studied by evaluation of perturbation, noise measures, and cepstral analysis of speech. In this study, feature extraction and analysis were performed during running speech using six different sentences. Jitter, shimmer, Mel frequency cepstral coefficients, bionic wavelet transform entropy, and bionic wavelet transform energy were calculated. Support vector machines were employed for classification of data to normal or hypernasal. Finally, results of the automatic classification were compared with true labels to find accuracy, sensitivity, and specificity. Accuracy was higher when Mel frequency cepstral coefficients were combined with bionic wavelet transform energy feature. In the best case, accuracy of 85% with sensitivity of 82% and specificity of 85% was obtained. Results prove that acoustic analysis is a reliable method to find hypernasality in cleft lip and palate patients.