A Case of Unilateral Vocal Fold Paralysis Caused by Ortner’s Syndrome

Park, Sang Hoo; Park, Heon Soo; Bae, Woo Yong; Lee, Dong Kun

doi:10.22469/jkslp.2019.30.2.139

Cited by 1 publication

(1 citation statement)

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“…22 Differences in s/z ratios have been found with impaired power source for voicing. 23 -25 Differences in flow, GFI and s/z ratios have already been demonstrated between diagnoses of UVFP, BVFP, and presbylarynges. 5 Aging changes (primarily bowing) have been observed in the non-paretic vocal fold in some UVFP patients over 60 years of age.…”

Section: Introductionmentioning

confidence: 97%

Predicting Airflow from Measures Sensitive to Mid-cord Glottal Gap During the COVID-19 Pandemic

Niermeyer

Diao

Bielamowicz

et al. 2023

Ann Otol Rhinol Laryngol

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Objectives: To determine if trans-laryngeal airflow, important in assessing vocal function in paresis/paralysis and presbylarynges patients with mid-cord glottal gaps, could be predicted by other measures sensitive to mid-cord glottal gap size but with smaller risks of spreading COVID-19, and if any patient factors need consideration. Methods: Four populations were: unilateral vocal fold paresis/paralysis (UVFP, 148), aging and UVFP (UVFP plus aging, 22), bilateral vocal fold paresis/paralysis without airway obstruction (BVFP, 49), and presbylarynges (66). Five measures were selected from the initial clinic visit: mean airflow from repeated /pi/ syllables, longer of 2 /s/ and 2 /z/ productions, higher of 2 cepstral peak prominence smoothed for vowel /a/ (CPPSa), and Glottal Function Index (GFI). S/Z ratios were computed. Stepwise regression models used 3 measures and 5 patient factors (age, sex, etiology, diagnosis, and potentially impaired power source for voicing) to predict airflow. Results: Log-transformations were required to normalize distributions of airflow and S/Z ratio. The final model revealed age, sex, impaired power source, log-transformed S/Z ratio, and GFI predicted log-transformed airflow ( R2 = .275, F[5,278] = 21.1; P < .001). Conclusions: The amount of variance explained by the model was not high, suggesting adding other predictive variables to the model might increase the variance explained.

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