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Recent smell loss is the best predictor of COVID-19: a preregistered, cross-sectional study

Authors :
Parma, Valentina
Overdevest, Jonathan B
Peng, Mei
Saatci, Ozlem
Sell, Elizabeth A
Yan, Carol H
Alfaro, Raul
Cecchetto, Cinzia
Coureaud, Gérard
Herriman, Riley D
Justice, Jeb M
Kaushik, Pavan Kumar
Koyama, Sachiko
Pirastu, Nicola
Ning, Yuping
Ramirez, Vicente A
Roberts, S Craig
Smith, Barry C
Cao, Hongyuan
Wang, Hong
Balungwe, Patrick
Baguma, Marius
Hummel, Thomas
Hayes, John E
Reed, Danielle R
Niv, Masha Y
Munger, Steven D
Ozturk, Elif E
Gerkin, Richard C
Ohla, Kathrin
Veldhuizen, Maria Geraldine
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 Ph S
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
Domínguez, Paloma Paloma
Yanık, Hüseyin
Boesveldt, Sanne
de Groot, Jasper H B
Dinnella, Caterina
Freiherr, Jessica
Laktionova, Tatiana
Mariño, Sajidxa
Monteleone, Erminio
Nunez-Parra, Alexia
Abdulrahman, Olagunju
Ritchie, Marina
Thomas-Danguin, Thierry
Walsh-Messinger, Julie
Al Abri, Rashid
Alizadeh, Rafieh
Bignon, Emmanuelle
Cantone, Elena
Cecchini, Maria Paola
Chen, Jingguo
Guàrdia, Maria Dolors
Hoover, Kara C
Karni, Noam
Navarro, Marta
Nolden, Alissa A
Mazal, Patricia Portillo
Rowan, Nicholas R
Sarabi-Jamab, Atiye
Archer, Nicholas S
Chen, Ben
Di Valerio, Elizabeth A
Feeney, Emma L
Frasnelli, Johannes
Hannum, Mackenzie
Hopkins, Claire
Klein, Hadar
Mignot, Coralie
Mucignat, Carla
UCL - (SLuc) Service d'oto-rhino-laryngologie
UCL - SSS/IONS/NEUR - Clinical Neuroscience
Source :
medRxiv : the preprint server for health sciences, (2020)
Publication Year :
2020

Abstract

COVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19. This preregistered, cross-sectional study used 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 singular and cumulative 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 single and cumulative feature models (ROC AUC=0.72), with additional features providing no significant model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ~50% of participants and was best predicted by time since illness onset. As smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (10

Details

Language :
English
Database :
OpenAIRE
Journal :
medRxiv : the preprint server for health sciences, (2020)
Accession number :
edsair.od......1493..c75f6bc3dcee353d21ee130dc4be8a91