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, Richard C; Ohla, Kathrin; Veldhuizen, Maria G; Joseph, Paule V; Kelly, Christine E; Bakke, Alyssa J; Steele, Kimberley E; Farruggia, Michael C; Pellegrino, Robert; Pepino, Marta Y; Bouysset, Cédric; Soler, Graciela M; Pereda-Loth, Veronica; Dibattista, Michele; Cooper, Keiland W; Croijmans, Ilja; Di Pizio, Antonella; Ozdener, M Hakan; Fjaeldstad, Alexander W; Lin, Cailu; Sandell, Mari A; Singh, Preet B; Brindha, V Evelyn; Olsson, Shannon B; Saraiva, Luis R; Ahuja, Gaurav; Alwashahi, Mohammed K; Bhutani, Surabhi; D'Errico, Anna; Fornazieri, Marco A; Golebiowski, Jérôme; Hwang, Liang-Dar; Öztürk, Lina; Roura, Eugeni; Spinelli, Sara; Whitcroft, Katherine L; Faraji, Farhoud; Fischmeister, Florian PhS; Heinbockel, Thomas; Hsieh, Julien W; Huart, Caroline; Konstantinidis, Iordanis; Menini, Anna; Morini, Gabriella; Olofsson, Jonas K; Philpott, Carl M; Pierron, Denis; Shields, Vonnie D C; Voznessenskaya, Vera V; Albayay, Javier; Altundag, Aytug; Bensafi, Moustafa; Bock, María Adelaida; Calcinoni, Orietta; Fredborg, William; Laudamiel, Christophe; Lim, Juyun; Lundström, Johan N; Macchi, Alberto; Meyer, Pablo; Moein, Shima T; Santamaría, Enrique; Sengupta, Debarka; Dominguez, Paloma Rohlfs; Yanik, Hüseyin; Hummel, Thomas; Hayes, John E; Reed, Danielle R; Niv, Masha Y; Munger, Steven D; Parma, Valentina. - 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

Menini, Anna;
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, Richard C; Ohla, Kathrin; Veldhuizen, Maria G; Joseph, Paule V; Kelly, Christine E; Bakke, Alyssa J; Steele, Kimberley E; Farruggia, Michael C; Pellegrino, Robert; Pepino, Marta Y; Bouysset, Cédric; Soler, Graciela M; Pereda-Loth, Veronica; Dibattista, Michele; Cooper, Keiland W; Croijmans, Ilja; Di Pizio, Antonella; Ozdener, M Hakan; Fjaeldstad, Alexander W; Lin, Cailu; Sandell, Mari A; Singh, Preet B; Brindha, V Evelyn; Olsson, Shannon B; Saraiva, Luis R; Ahuja, Gaurav; Alwashahi, Mohammed K; Bhutani, Surabhi; D'Errico, Anna; Fornazieri, Marco A; Golebiowski, Jérôme; Hwang, Liang-Dar; Öztürk, Lina; Roura, Eugeni; Spinelli, Sara; Whitcroft, Katherine L; Faraji, Farhoud; Fischmeister, Florian PhS; Heinbockel, Thomas; Hsieh, Julien W; Huart, Caroline; Konstantinidis, Iordanis; Menini, Anna; Morini, Gabriella; Olofsson, Jonas K; Philpott, Carl M; Pierron, Denis; Shields, Vonnie D C; Voznessenskaya, Vera V; Albayay, Javier; Altundag, Aytug; Bensafi, Moustafa; Bock, María Adelaida; Calcinoni, Orietta; Fredborg, William; Laudamiel, Christophe; Lim, Juyun; Lundström, Johan N; Macchi, Alberto; Meyer, Pablo; Moein, Shima T; Santamaría, Enrique; Sengupta, Debarka; Dominguez, Paloma Rohlfs; Yanik, Hüseyin; Hummel, Thomas; Hayes, John E; Reed, Danielle R; Niv, Masha Y; Munger, Steven D; Parma, Valentina
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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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