m+Medelevator.RU
← Поиск публикаций
The Journal of craniofacial surgery · 2020

Identifying Predictors of Acquired Velopharyngeal Insufficiency in Cleft Lip and Palate Following Maxillary Osteotomy Using Multiple Regression Analyses.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Pereira Valerie J, Tuomainen Jyrki, Hay Norman, Mars Michael, Suchak Archna, Sell Debbie A

Аннотация

BACKGROUND: Maxillary osteotomy is typically undertaken to correct abnormal facial growth in cleft lip and palate. The surgery can cause velopharyngeal insufficiency resulting in hypernasality. This study aims to identify valid predictors of acquired velopharyngeal insufficiency following maxillary osteotomy by using a range of perceptual and instrumental speech investigations and multiple regression.

METHODS: A prospective study was undertaken consisting of a consecutive series of patients with cleft lip and palate (N = 20) undergoing maxillary osteotomy by a single surgeon. Participants were seen at: 0 to 3 months pre-surgery (T1), 3-months (T2), and 12-months (T3) post-surgery. Hypernasality was rated using the cleft audit protocol for speech-augmented (CAPS-A) and visual analog scales, and nasalance was measured on the Nasometer II 6400. For lateral videofluorosopic and nasendoscopic images, visual perceptual ratings and quantitative ratiometric measurements were undertaken. Multiple regression analyses were undertaken to identify predictors.

RESULTS: T3 models with hypernasality as the dependent variable were found to be a good fit and significant (eg, CAPS-A: R2 = 0.920, F(11,7) = 7.303, P = 0.007). Closure ratio (a quantitative ratiometric measurement) and proportion of palate contacting the posterior pharyngeal wall (a visual perceptual rating) were identified as significant predictors for the CAPS-A model (P = 0.030, P = 0.002).

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты