Login / Signup

Speech patterns and enunciation for encephalopathy determination-A prospective study of hepatic encephalopathy.

Andrew M MoonHannah P KimSarah CookRenee T BlanchardKatarina L HaleyAdam JacksJennifer S ShaferMichael W Fried
Published in: Hepatology communications (2022)
Hepatic encephalopathy (HE) is a complication of cirrhosis that benefits from early diagnosis and treatment. We aimed to characterize speech patterns of individuals with HE to investigate its potential to diagnose and monitor HE. This was a single-center prospective cohort study that included participants with cirrhosis with HE (minimal HE [MHE] and overt HE [OHE]), cirrhosis without HE, and participants without liver disease. Audio recordings of reading, sentence repetition, and picture description tasks were obtained from these groups. Two certified speech-language pathologists assessed speech rate (words per minute) and articulatory precision. An overall severity metric was derived from these measures. Cross-sectional analyses were performed using nonparametric Wilcoxon statistics to evaluate group differences. Change over time in speech measures was analyzed descriptively for individuals with HE. The study included 43 total participants. Speech results differed by task, but the overall pattern showed slower speech rate and less precise articulation in participants with OHE compared to other groups. When speech rate and precision ratings were combined into a single speech severity metric, the impairment of participants with OHE was more severe than all other groups, and MHE had greater speech impairment than non-liver disease controls. As OHE improved clinically, participants showed notable improvement in speech rate. Participants with OHE demonstrated impaired speech rate, precision, and speech severity compared with non-liver disease and non-HE cirrhosis. Participants with MHE had less pronounced impairments. Speech parameters improved as HE clinically improved. Conclusion: These data identify speech patterns that could improve HE diagnosis, grading, and remote monitoring.
Keyphrases
  • hearing loss
  • cross sectional
  • machine learning
  • autism spectrum disorder
  • drug induced
  • deep learning
  • simultaneous determination