Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objective: To develop tools for predicting velopharyngeal competence (VPC) based on auditory-perceptual assessment and its correlation with objective measures of velopharyngeal orifice area.
Design: Methodological study.
Participants And Methods: Sixty-two patients with repaired cleft palate, aged 6 to 45 years, underwent aerodynamic evaluation by means of the pressure-flow technique and audiovisual recording of speech samples. Three experienced speech-language pathologists analysed the speech samples by rating the following resonance, visual, and speech variables: hypernasality, audible nasal air emission, nasal turbulence, weak pressure consonants, facial grimacing, active nonoral errors, and overall velopharyngeal competence. The correlation between the perceptual speech variables and velopharyngeal orifice area estimates was analysed with Spearman's correlation coefficient. Two statistical models (discriminant and exploratory) were used to predict VPC based on the orifice area estimates. Sensitivity and specificity analyses were performed to verify the clinical applicability of the models.
Results: There was a strong correlation between VPC (based on the orifice area estimates) and each speech variable. Both models showed 88.7% accuracy in predicting VPC. The sensitivity and specificity for the discriminant model were 92.3% and 97.2%, respectively, and 96.2% and 94.4% for the exploratory model.
Conclusion: Two predictor models based on ratings of resonance, visual, and speech variables and a simple calculation of a composite variable, SOMA (Eng. "sum"), were developed and found to be efficient in predicting VPC defined by orifice estimates categories based on aerodynamic measurements. Both tools may contribute to the diagnosis of velopharyngeal dysfunction in clinical practice.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1177/10556656221149516 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!