In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4<10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.

Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms / Gerkin, R. C.; Ohla, K.; Veldhuizen, M. G.; Joseph, P. V.; Kelly, C. E.; Bakke, A. J.; Steele, K. E.; Farruggia, M. C.; Pellegrino, R.; Pepino, M. Y.; Bouysset, C.; Soler, G. M.; Pereda-Loth, V.; Dibattista, M.; Cooper, K. W.; Croijmans, I.; Di Pizio, A.; Ozdener, M. H.; Fjaeldstad, A. W.; Lin, C.; Sandell, M. A.; Singh, P. B.; Brindha, V. E.; Olsson, S. B.; Saraiva, L. R.; Ahuja, G.; Alwashahi, M. K.; Bhutani, S.; D’Errico, A.; Fornazieri, M. A.; Golebiowski, J.; Dar Hwang, L.; Öztürk, L.; Roura, E.; Spinelli, S.; Whitcroft, K. L.; Faraji, F.; Fischmeister, F. P. S.; Heinbockel, T.; Hsieh, J. W.; Huart, C.; Konstantinidis, I.; Menini, A.; Morini, G.; Olofsson, J. K.; Philpott, C. M.; Pierron, D.; Shields, V. D. C.; Voznessenskaya, V. V.; Albayay, J.; Altundag, A.; Bensafi, M.; Bock, M. A.; Calcinoni, O.; Fredborg, W.; Laudamiel, C.; Lim, J.; Lundström, J. N.; Macchi, A.; Meyer, P.; Moein, S. T.; Santamaría, E.; Sengupta, D.; Rohlfs Dominguez, P.; Yanik, H.; Hummel, T.; Hayes, J. E.; Reed, D. R.; Niv, M. Y.; Munger, S. D.; Parma, V.; Boesveldt, S.; de Groot, J. H. B.; Dinnella, C.; Freiherr, J.; Laktionova, T.; Marino, S.; Monteleone, E.; Nunez-Parra, A.; Abdulrahman, O.; Ritchie, M.; Thomas-Danguin, T.; Walsh-Messinger, J.; Al Abri, R.; Alizadeh, R.; Bignon, E.; Cantone, E.; Paola Cecchini, M.; Chen, J.; Dolors Guàrdia, M.; Hoover, K. C.; Karni, N.; Navarro, M.; Nolden, A. A.; Portillo Mazal, P.; Rowan, N. R.; Sarabi-Jamab, A.; Archer, N. S.; Chen, B.; Di Valerio, E. A.; Feeney, E. L.; Frasnelli, J.; Hannum, M. E.; Hopkins, C.; Klein, H.; Mignot, C.; Mucignat, C.; Ning, Y.; Ozturk, E. E.; Peng, M.; Saatci, O.; Sell, E. A.; Yan, C. H.; Alfaro, R.; Cecchetto, C.; Coureaud, G.; Herriman, R. D.; Justice, J. M.; Kaushik, P. K.; Koyama, S.; Overdevest, J. B.; Pirastu, N.; Ramirez, V. A.; Roberts, S. C.; Smith, B. C.; Cao, H.; Wang, H.; Balungwe Birindwa, P.; Baguma, M.. - In: CHEMICAL SENSES. - ISSN 0379-864X. - 46:(2020), pp. 1-18. [10.1093/chemse/bjaa081]

Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms

Veldhuizen, M. G.;Dibattista, M.;Lin, C.;Menini, A.;Lim, J.;Hummel, T.;Parma, V.;Boesveldt, S.;Marino, S.;Chen, J.;Mucignat, C.;Cecchetto, C.;Cao, H.;
2020-01-01

Abstract

In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4<10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.
2020
46
1
18
Gerkin, R. C.; Ohla, K.; Veldhuizen, M. G.; Joseph, P. V.; Kelly, C. E.; Bakke, A. J.; Steele, K. E.; Farruggia, M. C.; Pellegrino, R.; Pepino, M. Y.; Bouysset, C.; Soler, G. M.; Pereda-Loth, V.; Dibattista, M.; Cooper, K. W.; Croijmans, I.; Di Pizio, A.; Ozdener, M. H.; Fjaeldstad, A. W.; Lin, C.; Sandell, M. A.; Singh, P. B.; Brindha, V. E.; Olsson, S. B.; Saraiva, L. R.; Ahuja, G.; Alwashahi, M. K.; Bhutani, S.; D’Errico, A.; Fornazieri, M. A.; Golebiowski, J.; Dar Hwang, L.; Öztürk, L.; Roura, E.; Spinelli, S.; Whitcroft, K. L.; Faraji, F.; Fischmeister, F. P. S.; Heinbockel, T.; Hsieh, J. W.; Huart, C.; Konstantinidis, I.; Menini, A.; Morini, G.; Olofsson, J. K.; Philpott, C. M.; Pierron, D.; Shields, V. D. C.; Voznessenskaya, V. V.; Albayay, J.; Altundag, A.; Bensafi, M.; Bock, M. A.; Calcinoni, O.; Fredborg, W.; Laudamiel, C.; Lim, J.; Lundström, J. N.; Macchi, A.; Meyer, P.; Moein, S. T.; Santamaría, E.; Sengupta, D.; Rohlfs Dominguez, P.; Yanik, H.; Hummel, T.; Hayes, J. E.; Reed, D. R.; Niv, M. Y.; Munger, S. D.; Parma, V.; Boesveldt, S.; de Groot, J. H. B.; Dinnella, C.; Freiherr, J.; Laktionova, T.; Marino, S.; Monteleone, E.; Nunez-Parra, A.; Abdulrahman, O.; Ritchie, M.; Thomas-Danguin, T.; Walsh-Messinger, J.; Al Abri, R.; Alizadeh, R.; Bignon, E.; Cantone, E.; Paola Cecchini, M.; Chen, J.; Dolors Guàrdia, M.; Hoover, K. C.; Karni, N.; Navarro, M.; Nolden, A. A.; Portillo Mazal, P.; Rowan, N. R.; Sarabi-Jamab, A.; Archer, N. S.; Chen, B.; Di Valerio, E. A.; Feeney, E. L.; Frasnelli, J.; Hannum, M. E.; Hopkins, C.; Klein, H.; Mignot, C.; Mucignat, C.; Ning, Y.; Ozturk, E. E.; Peng, M.; Saatci, O.; Sell, E. A.; Yan, C. H.; Alfaro, R.; Cecchetto, C.; Coureaud, G.; Herriman, R. D.; Justice, J. M.; Kaushik, P. K.; Koyama, S.; Overdevest, J. B.; Pirastu, N.; Ramirez, V. A.; Roberts, S. C.; Smith, B. C.; Cao, H.; Wang, H.; Balungwe Birindwa, P.; Baguma, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/117572
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