Kapsner-Smith Mara R, Díaz-Cádiz Manuel E, Vojtech Jennifer M, Buckley Daniel P, Mehta Daryush D, Hillman Robert E, Tracy Lauren F, Noordzij J Pieter, Eadie Tanya L, Stepp Cara E
Department of Speech & Hearing Sciences, University of Washington, Seattle.
Department of Speech, Language & Hearing Sciences, Boston University, MA.
J Speech Lang Hear Res. 2022 Apr 4;65(4):1349-1369. doi: 10.1044/2021_JSLHR-21-00466. Epub 2022 Mar 10.
This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF).
Demographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:1 case-control groups: individuals with and without nonphonotraumatic vocal hyperfunction (NPVH; = 360) and phonotraumatic vocal hyperfunction (PVH; = 240). Equations from the final models were used to predict group membership in two independent test sets ( = 100 each).
Both CPPS and RFF parameters significantly improved model fits for NPVH and PVH after accounting for demographics. CPPS explained unique variance beyond RFF in both models. RFF explained unique variance beyond CPPS in the PVH model. Final models included CPPS and RFF offset parameters for both NPVH and PVH; RFF onset parameters were significant only in the PVH model. Area under the receiver operating characteristic curve analysis for the independent test sets revealed acceptable classification for NPVH (72%) and good classification for PVH (86%).
A combination of CPPS and RFF parameters showed better discriminative ability than either measure alone for PVH. Clinical cutoff scores for acoustic indices of vocal hyperfunction are proposed for assessment and screening purposes.
本研究考察了结合平滑谐波峰值突出度(CPPS)和相对基频(RFF)的嗓音功能亢进声学指标的判别能力。
将人口统计学、CPPS和RFF参数输入到在两个1:1病例对照小组上训练的逻辑回归模型中:患有和未患有非发声创伤性嗓音功能亢进(NPVH;n = 360)和发声创伤性嗓音功能亢进(PVH;n = 240)的个体。最终模型中的方程用于预测两个独立测试集(每组n = 100)中的组成员身份。
在考虑人口统计学因素后,CPPS和RFF参数均显著改善了NPVH和PVH模型的拟合度。在两个模型中,CPPS解释了RFF之外的独特方差。在PVH模型中,RFF解释了CPPS之外的独特方差。最终模型包括NPVH和PVH的CPPS和RFF偏移参数;RFF起始参数仅在PVH模型中显著。独立测试集的受试者工作特征曲线分析下的面积显示NPVH的分类可接受(72%),PVH的分类良好(86%)。
CPPS和RFF参数的组合对PVH显示出比单独任何一种测量更好的判别能力。提出了嗓音功能亢进声学指标的临床临界值分数用于评估和筛查目的。