METHODS: Cross-sectional analysis of prospectively collected data from 2019-2022.
METHODS: Six cleft treatment centers collected data systematically during routine clinic appointments according to a standardized protocol.
METHODS: 714 English-speaking children and adolescents with non-syndromic cleft lip/palate.
METHODS: Routine multidisciplinary care and systematic outcomes measurement by cleft teams.
METHODS: Speech outcomes included articulatory accuracy measured by Percent Consonants Correct (PCC), velopharyngeal function measured by Velopharyngeal Competence (VPC) Rating Scale (VPC-R), intelligibility measured by caregiver-reported Intelligibility in Context Scale (ICS), and two CLEFT-Q™ surveys, in which patients rate their own speech function and level of speech distress.
RESULTS: 12year-olds exhibited high median PCC scores (91-100%), high frequency of velopharyngeal competency (62.50-100%), and high median Speech Function (80-91) relative to younger peers parsed by phenotype. Patients with bilateral cleft lip, alveolus, and palate reported low PCC scores (51-91%) relative to peers at some ages and low frequency of velopharyngeal competency (26.67%) at 5 years. ICS scores ranged from 3.93-5.0 for all ages and phenotypes. Speech Function and Speech Distress were similar across phenotypes.
CONCLUSIONS: This exploration of speech outcomes demonstrates the current ability of the cleft-specific registry to support cleft research efforts as a source of \"real-world\" data. Further work is focused on developing robust methodology for hypothesis-driven research and causal inference.
方法:对2019-2022年前瞻性收集的数据进行横断面分析。
方法:六个裂隙治疗中心根据标准化方案在常规临床预约期间系统地收集数据。
方法:714患有非综合征性唇腭裂的英语儿童和青少年。
方法:常规的多学科护理和裂隙小组的系统结果测量。
方法:语音结果包括通过辅音正确百分比(PCC)测量的发音准确性,通过咽喉能力(VPC)评定量表(VPC-R)测量咽喉功能,由护理人员报告的上下文量表(ICS)中的清晰度测量的清晰度,和两个CLEFT-Q™调查,患者对自己的言语功能和言语困扰水平进行评分。
结果:12岁儿童的PCC得分中位数较高(91-100%),咽喉能力的高频率(62.50-100%),相对于按表型分析的年轻同龄人,语音功能中位数较高(80-91)。双侧唇裂患者,肺泡,在某些年龄,与同龄人相比,上颚报告的PCC得分较低(51-91%),并且在5年时,喉部能力的频率较低(26.67%)。所有年龄和表型的ICS评分范围为3.93-5.0。不同表型的言语功能和言语障碍相似。
结论:对语音结果的探索表明了裂隙特异性注册表当前支持裂隙研究工作作为“真实世界”数据来源的能力。进一步的工作重点是开发用于假设驱动研究和因果推断的强大方法。