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Can Multisensory Olfactory Training Improve Olfactory Dysfunction Caused by COVID-19?

Gözde FilizSimon BérubéClaudia DemersFrank CloutierAngela ChenValérie PekÉmilie HudonJosiane Bolduc-BéginJohannes Frasnelli
Published in: Multisensory research (2024)
Approximately 30-60% of people suffer from olfactory dysfunction (OD) such as hyposmia or anosmia after being diagnosed with COVID-19; 15-20% of these cases last beyond resolution of the acute phase. Previous studies have shown that olfactory training can be beneficial for patients affected by OD caused by viral infections of the upper respiratory tract. The aim of the study is to evaluate whether a multisensory olfactory training involving simultaneously tasting and seeing congruent stimuli is more effective than the classical olfactory training. We recruited 68 participants with persistent OD for two months or more after COVID-19 infection; they were divided into three groups. One group received olfactory training which involved smelling four odorants (strawberry, cheese, coffee, lemon; classical olfactory training). The other group received the same olfactory stimuli but presented retronasally (i.e., as droplets on their tongue); while simultaneous and congruent gustatory (i.e., sweet, salty, bitter, sour) and visual (corresponding images) stimuli were presented (multisensory olfactory training). The third group received odorless propylene glycol in four bottles (control group). Training was carried out twice daily for 12 weeks. We assessed olfactory function and olfactory specific quality of life before and after the intervention. Both intervention groups showed a similar significant improvement of olfactory function, although there was no difference in the assessment of quality of life. Both multisensory and classical training can be beneficial for OD following a viral infection; however, only the classical olfactory training paradigm leads to an improvement that was significantly stronger than the control group.
Keyphrases
  • virtual reality
  • sars cov
  • randomized controlled trial
  • coronavirus disease
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  • machine learning
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