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Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study

The aim of this proof-of-concept study was to evaluate if trained dogs could discriminate between sweat samples from symptomatic COVID-19 positive individuals (SARS-CoV-2 PCR positive) and those from asymptomatic COVID-19 negative individuals. The study was conducted at 2 sites (Paris, France, and B...

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Autores principales: Grandjean, Dominique, Sarkis, Riad, Lecoq-Julien, Clothilde, Benard, Aymeric, Roger, Vinciane, Levesque, Eric, Bernes-Luciani, Eric, Maestracci, Bruno, Morvan, Pascal, Gully, Eric, Berceau-Falancourt, David, Haufstater, Pierre, Herin, Gregory, Cabrera, Joaquin, Muzzin, Quentin, Gallet, Capucine, Bacqué, Hélène, Broc, Jean-Marie, Thomas, Leo, Lichaa, Anthony, Moujaes, Georges, Saliba, Michele, Kuhn, Aurore, Galey, Mathilde, Berthail, Benoit, Lapeyre, Lucien, Capelli, Anthoni, Renault, Steevens, Bachir, Karim, Kovinger, Anthony, Comas, Eric, Stainmesse, Aymeric, Etienne, Erwan, Voeltzel, Sébastien, Mansouri, Sofiane, Berceau-Falancourt, Marlène, Dami, Aimé, Charlet, Lary, Ruau, Eric, Issa, Mario, Grenet, Carine, Billy, Christophe, Tourtier, Jean-Pierre, Desquilbet, Loïc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728218/
https://www.ncbi.nlm.nih.gov/pubmed/33301539
http://dx.doi.org/10.1371/journal.pone.0243122
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author Grandjean, Dominique
Sarkis, Riad
Lecoq-Julien, Clothilde
Benard, Aymeric
Roger, Vinciane
Levesque, Eric
Bernes-Luciani, Eric
Maestracci, Bruno
Morvan, Pascal
Gully, Eric
Berceau-Falancourt, David
Haufstater, Pierre
Herin, Gregory
Cabrera, Joaquin
Muzzin, Quentin
Gallet, Capucine
Bacqué, Hélène
Broc, Jean-Marie
Thomas, Leo
Lichaa, Anthony
Moujaes, Georges
Saliba, Michele
Kuhn, Aurore
Galey, Mathilde
Berthail, Benoit
Lapeyre, Lucien
Capelli, Anthoni
Renault, Steevens
Bachir, Karim
Kovinger, Anthony
Comas, Eric
Stainmesse, Aymeric
Etienne, Erwan
Voeltzel, Sébastien
Mansouri, Sofiane
Berceau-Falancourt, Marlène
Dami, Aimé
Charlet, Lary
Ruau, Eric
Issa, Mario
Grenet, Carine
Billy, Christophe
Tourtier, Jean-Pierre
Desquilbet, Loïc
author_facet Grandjean, Dominique
Sarkis, Riad
Lecoq-Julien, Clothilde
Benard, Aymeric
Roger, Vinciane
Levesque, Eric
Bernes-Luciani, Eric
Maestracci, Bruno
Morvan, Pascal
Gully, Eric
Berceau-Falancourt, David
Haufstater, Pierre
Herin, Gregory
Cabrera, Joaquin
Muzzin, Quentin
Gallet, Capucine
Bacqué, Hélène
Broc, Jean-Marie
Thomas, Leo
Lichaa, Anthony
Moujaes, Georges
Saliba, Michele
Kuhn, Aurore
Galey, Mathilde
Berthail, Benoit
Lapeyre, Lucien
Capelli, Anthoni
Renault, Steevens
Bachir, Karim
Kovinger, Anthony
Comas, Eric
Stainmesse, Aymeric
Etienne, Erwan
Voeltzel, Sébastien
Mansouri, Sofiane
Berceau-Falancourt, Marlène
Dami, Aimé
Charlet, Lary
Ruau, Eric
Issa, Mario
Grenet, Carine
Billy, Christophe
Tourtier, Jean-Pierre
Desquilbet, Loïc
author_sort Grandjean, Dominique
collection PubMed
description The aim of this proof-of-concept study was to evaluate if trained dogs could discriminate between sweat samples from symptomatic COVID-19 positive individuals (SARS-CoV-2 PCR positive) and those from asymptomatic COVID-19 negative individuals. The study was conducted at 2 sites (Paris, France, and Beirut, Lebanon), followed the same training and testing protocols, and involved six detection dogs (three explosive detection dogs, one search and rescue dog, and two colon cancer detection dogs). A total of 177 individuals were recruited for the study (95 symptomatic COVID-19 positive and 82 asymptomatic COVID-19 negative individuals) from five hospitals, and one underarm sweat sample per individual was collected. The dog training sessions lasted between one and three weeks. Once trained, the dog had to mark the COVID-19 positive sample randomly placed behind one of three or four olfactory cones (the other cones contained at least one COVID-19 negative sample and between zero and two mocks). During the testing session, a COVID-19 positive sample could be used up to a maximum of three times for one dog. The dog and its handler were both blinded to the COVID-positive sample location. The success rate per dog (i.e., the number of correct indications divided by the number of trials) ranged from 76% to 100%. The lower bound of the 95% confidence interval of the estimated success rate was most of the time higher than the success rate obtained by chance after removing the number of mocks from calculations. These results provide some evidence that detection dogs may be able to discriminate between sweat samples from symptomatic COVID-19 individuals and those from asymptomatic COVID-19 negative individuals. However, due to the limitations of this proof-of-concept study (including using some COVID-19 samples more than once and potential confounding biases), these results must be confirmed in validation studies.
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spelling pubmed-77282182020-12-16 Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study Grandjean, Dominique Sarkis, Riad Lecoq-Julien, Clothilde Benard, Aymeric Roger, Vinciane Levesque, Eric Bernes-Luciani, Eric Maestracci, Bruno Morvan, Pascal Gully, Eric Berceau-Falancourt, David Haufstater, Pierre Herin, Gregory Cabrera, Joaquin Muzzin, Quentin Gallet, Capucine Bacqué, Hélène Broc, Jean-Marie Thomas, Leo Lichaa, Anthony Moujaes, Georges Saliba, Michele Kuhn, Aurore Galey, Mathilde Berthail, Benoit Lapeyre, Lucien Capelli, Anthoni Renault, Steevens Bachir, Karim Kovinger, Anthony Comas, Eric Stainmesse, Aymeric Etienne, Erwan Voeltzel, Sébastien Mansouri, Sofiane Berceau-Falancourt, Marlène Dami, Aimé Charlet, Lary Ruau, Eric Issa, Mario Grenet, Carine Billy, Christophe Tourtier, Jean-Pierre Desquilbet, Loïc PLoS One Research Article The aim of this proof-of-concept study was to evaluate if trained dogs could discriminate between sweat samples from symptomatic COVID-19 positive individuals (SARS-CoV-2 PCR positive) and those from asymptomatic COVID-19 negative individuals. The study was conducted at 2 sites (Paris, France, and Beirut, Lebanon), followed the same training and testing protocols, and involved six detection dogs (three explosive detection dogs, one search and rescue dog, and two colon cancer detection dogs). A total of 177 individuals were recruited for the study (95 symptomatic COVID-19 positive and 82 asymptomatic COVID-19 negative individuals) from five hospitals, and one underarm sweat sample per individual was collected. The dog training sessions lasted between one and three weeks. Once trained, the dog had to mark the COVID-19 positive sample randomly placed behind one of three or four olfactory cones (the other cones contained at least one COVID-19 negative sample and between zero and two mocks). During the testing session, a COVID-19 positive sample could be used up to a maximum of three times for one dog. The dog and its handler were both blinded to the COVID-positive sample location. The success rate per dog (i.e., the number of correct indications divided by the number of trials) ranged from 76% to 100%. The lower bound of the 95% confidence interval of the estimated success rate was most of the time higher than the success rate obtained by chance after removing the number of mocks from calculations. These results provide some evidence that detection dogs may be able to discriminate between sweat samples from symptomatic COVID-19 individuals and those from asymptomatic COVID-19 negative individuals. However, due to the limitations of this proof-of-concept study (including using some COVID-19 samples more than once and potential confounding biases), these results must be confirmed in validation studies. Public Library of Science 2020-12-10 /pmc/articles/PMC7728218/ /pubmed/33301539 http://dx.doi.org/10.1371/journal.pone.0243122 Text en © 2020 Grandjean et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Grandjean, Dominique
Sarkis, Riad
Lecoq-Julien, Clothilde
Benard, Aymeric
Roger, Vinciane
Levesque, Eric
Bernes-Luciani, Eric
Maestracci, Bruno
Morvan, Pascal
Gully, Eric
Berceau-Falancourt, David
Haufstater, Pierre
Herin, Gregory
Cabrera, Joaquin
Muzzin, Quentin
Gallet, Capucine
Bacqué, Hélène
Broc, Jean-Marie
Thomas, Leo
Lichaa, Anthony
Moujaes, Georges
Saliba, Michele
Kuhn, Aurore
Galey, Mathilde
Berthail, Benoit
Lapeyre, Lucien
Capelli, Anthoni
Renault, Steevens
Bachir, Karim
Kovinger, Anthony
Comas, Eric
Stainmesse, Aymeric
Etienne, Erwan
Voeltzel, Sébastien
Mansouri, Sofiane
Berceau-Falancourt, Marlène
Dami, Aimé
Charlet, Lary
Ruau, Eric
Issa, Mario
Grenet, Carine
Billy, Christophe
Tourtier, Jean-Pierre
Desquilbet, Loïc
Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study
title Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study
title_full Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study
title_fullStr Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study
title_full_unstemmed Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study
title_short Can the detection dog alert on COVID-19 positive persons by sniffing axillary sweat samples? A proof-of-concept study
title_sort can the detection dog alert on covid-19 positive persons by sniffing axillary sweat samples? a proof-of-concept study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728218/
https://www.ncbi.nlm.nih.gov/pubmed/33301539
http://dx.doi.org/10.1371/journal.pone.0243122
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