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Pré-Publication, Document De Travail medRxiv : the preprint server for health sciences Année : 2020

The best COVID-19 predictor is recent smell loss: a cross-sectional study

Richard Gerkin (1) , Kathrin Ohla (2) , Maria Geraldine Veldhuizen (3) , Paule Joseph (4) , Christine Kelly (5) , Alyssa Bakke (6) , Kimberley Steele (4, 7) , Michael Farruggia (8) , Robert Pellegrino (9) , Marta Pepino (10) , Cédric Bouysset (11) , Graciela Soler (12) , Veronica Pereda-Loth (13) , Michele Dibattista (14) , Keiland Cooper (15) , Ilja Croijmans (16) , Antonella Di Pizio (17) , M. Hakan Ozdener (18) , Alexander Fjaeldstad (19) , Cailu Lin (18) , Mari Sandell (20) , Preet Singh (21) , V. Evelyn Brindha (22) , Shannon Olsson (23) , Luis Saraiva (24) , Gaurav Ahuja (25) , Mohammed Alwashahi (26) , Surabhi Bhutani (27) , Anna d'Errico (28) , Marco Fornazieri (29) , Jérôme Golebiowski (11) , Liang-Dar Hwang (30) , Lina Öztürk (3) , Eugeni Roura (30) , Sara Spinelli (31) , Katherine Whitcroft (32) , Farhoud Faraji (27) , Florian Ph.S Fischmeister (33) , Thomas Heinbockel (34) , Julien Hsieh (35) , Caroline Huart (36) , Iordanis Konstantinidis (37) , Anna Menini (38) , Gabriella Morini (39) , Jonas Olofsson (40) , Carl Philpott (41) , Denis Pierron (13) , Vonnie Shields (42) , Vera Voznessenskaya (43) , Javier Albayay (44) , Aytug Altundag (45) , Moustafa Bensafi (46) , María Adelaida Bock (47) , Orietta Calcinoni (48) , William Fredborg (40) , Christophe Laudamiel (49) , Juyun Lim (50) , Johan Lundström (51) , Alberto Macchi (52) , Pablo Meyer (53) , Shima Moein (54) , Enrique Santamaría (55) , Debarka Sengupta (25) , Paloma Paloma Domínguez (56) , Hüseyin Yanik (3) , Thomas Hummel (57) , John Hayes (6) , Danielle Reed (18) , Masha Niv (58) , Steven Munger (59) , Valentina Parma (60)
1 ASU - Arizona State University [Tempe]
2 INM-1 - Institute of Neuroscience and Medicine [Jülich]
3 Mersin University
4 NIH - National Institutes of Health [Bethesda, MD, USA]
5 AbScent
6 Penn State - Pennsylvania State University
7 National Institute of Diabetes and Digestive and Kidney Diseases [Bethesda]
8 Yale University [New Haven]
9 Tennessee State University
10 UIUC - University of Illinois at Urbana-Champaign [Urbana]
11 ICN - Institut de Chimie de Nice
12 Buenos Aires University and GEOG (Grupo de Estudio de Olfato y Gusto)
13 AMIS - Anthropologie Moléculaire et Imagerie de Synthèse
14 UNIBA - Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro
15 UC Irvine - University of California [Irvine]
16 Universiteit Utrecht / Utrecht University [Utrecht]
17 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
18 Monell Chemical Senses Center
19 Regional Hospital West Jutland [Denmark]
20 Helsingin yliopisto = Helsingfors universitet = University of Helsinki
21 UiO - University of Oslo
22 Karunya University
23 TIFR - Tata Institute for Fundamental Research
24 Sidra Medicine [Doha, Qatar]
25 IIIT-Delhi - Indraprastha Institute of Information Technology [New Delhi]
26 SQU - Sultan Qaboos University
27 SDSU - San Diego State University
28 Goethe-University Frankfurt am Main
29 State University of Londrina = Universidade Estadual de Londrina
30 UQ [All campuses : Brisbane, Dutton Park Gatton, Herston, St Lucia and other locations] - The University of Queensland
31 UniFI - Università degli Studi di Firenze = University of Florence = Université de Florence
32 UCL - University College of London [London]
33 Karl-Franzens-Universität Graz
34 Howard University
35 HUG - Geneva University Hospital
36 Cliniques Universitaires Saint-Luc [Bruxelles]
37 Aristotle University of Thessaloniki
38 SISSA / ISAS - Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies
39 UNISG - University of Gastronomic Sciences of Pollenzo
40 Stockholm University
41 UEA - University of East Anglia [Norwich]
42 Towson University [Towson, MD, United States]
43 A.N. Severtsov Institute of Ecology and Evolution
44 Unipd - Università degli Studi di Padova = University of Padua
45 Biruni University
46 CRNL - Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center
47 Public Hospital Barrio Obrero - Hospital General de Barrio Obrero [Asunción, Paraguay]
48 Private practice [Milan]
49 DreamAir Llc
50 OSU - Oregon State University
51 CCK - Cancer Center Karolinska [Karolinska Institutet]
52 Uninsubria - Universitá degli Studi dell’Insubria = University of Insubria [Varese]
53 IBM T.J. Watson Research Center - Computational Biology Center
54 IPM - Institute for Research in Fundamental Sciences [Tehran]
55 IdiSNA - Instituto de Investigación Sanitaria de Navarra [Pamplona, Spain]
56 UEX - Universidad de Extremadura - University of Extremadura
57 TU Dresden - Technische Universität Dresden = Dresden University of Technology
58 HUJ - The Hebrew University of Jerusalem
59 UF - University of Florida [Gainesville]
60 Temple University [Philadelphia]
Christine Kelly
  • Fonction : Auteur
Cédric Bouysset
Cailu Lin
Preet Singh
  • Fonction : Auteur
Jérôme Golebiowski
Lina Öztürk
  • Fonction : Auteur
Eugeni Roura
Jonas Olofsson
Aytug Altundag
  • Fonction : Auteur
Juyun Lim
Hüseyin Yanik
  • Fonction : Auteur
Valentina Parma

Résumé

Background: 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. Methods: 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. Results: 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. Conclusions: 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
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Dates et versions

hal-02979656 , version 2 (27-10-2020)
hal-02979656 , version 1 (16-11-2020)

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Richard Gerkin, Kathrin Ohla, Maria Geraldine Veldhuizen, Paule Joseph, Christine Kelly, et al.. The best COVID-19 predictor is recent smell loss: a cross-sectional study. 2020. ⟨hal-02979656v1⟩
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