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

LARYNGEAL physiology; GLOTTIS; STATISTICS; RESEARCH evaluation; CONFIDENCE intervals; PARALYSIS; HUMAN voice; RETROSPECTIVE studies; REGRESSION analysis; VOCAL cord diseases; PEARSON correlation (Statistics); DESCRIPTIVE statistics; RESPIRATION; COVID-19 pandemic

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 (R 2 =.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. [ABSTRACT FROM AUTHOR]

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