Evidence map›Paper›PMID 37822474›Full record

ArticleFrontiers in medicine2023

Sniffing out safety: canine detection and identification of SARS-CoV-2 infection from armpit sweat.

Chris Callewaert, Maria Pezavant, Rony Vandaele, Bart Meeus, Ellen Vankrunkelsven, Phaedra Van Goethem, Alain Plumacker, Benoit Misset, Gilles Darcis, Sonia Piret and 24 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 59% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

34 authors at 12 institutions in 3 countries.

Chris CallewaertCenter for Microbial Ecology and Technology (CMET), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Maria PezavantFaculty of Veterinary Medicine, Clinique Vétérinaire Universitaire (CVU), University of Liège, Liège, Belgium.
Rony VandaeleFederal Police Belgium, Linter, Belgium.
Bart MeeusFederal Police Belgium, Linter, Belgium.
Ellen VankrunkelsvenFederal Police Belgium, Linter, Belgium.
Phaedra Van GoethemFederal Police Belgium, Linter, Belgium.
Alain PlumackerCHU Saint-Pierre Hospital, Brussels, Belgium.
Benoit MissetCHU-Sart-Tilman, Intensive Care Unit, University of Liège, Liège, Belgium.
Gilles DarcisCHU-Sart-Tilman, Infectious Diseases - Internal Medicine, Public Health Sciences, University of Liège, Liège, Belgium.
Sonia PiretCHU-Bruyères, Intensive Care Unit, University of Liège, Liège, Belgium.
Lander De VleeschouwerGeneral Hospital (AZ) Glorieux Hospital, Ronse, Belgium.
Frank StaelensOnze Lieve Vrouwziekenhuis (OLVZ), Aalst, Belgium.
Kristel Van VarenberghOnze Lieve Vrouwziekenhuis (OLVZ), Aalst, Belgium.
Sofie TombeurOnze Lieve Vrouwziekenhuis (OLVZ), Aalst, Belgium.
Anouck OttevaereGeneral Hospital (AZ) Oudenaarde, Oudenaarde, Belgium.
Ilke MontagJan Yperman Hospital, Ypres, Belgium.
Patricia VandecandelaereLaboratory of Clinical Microbiology, Jan Yperman Hospital, Ypres, Belgium.
Stijn JonckheereLaboratory of Clinical Microbiology, Jan Yperman Hospital, Ypres, Belgium.
Linos VandekerckhoveHIV Cure Research Center, Department of Internal Medicine and Pediatrics, Ghent University Hospital, Ghent University, Ghent, Belgium.
Els TobbackDepartment of General Internal Medicine and Infectious Diseases, Ghent University Hospital, Ghent, Belgium.
Gregoire WieersGeneral Internal Medicine, Clinique Saint-Pierre Ottignies, Ottignies, Belgium.
Jean-Christophe MarotGeneral Internal Medicine, Clinique Saint-Pierre Ottignies, Ottignies, Belgium.
Kurt AnseeuwDepartment of Emergency Medicine, ZNA, Antwerp, Belgium.
Leen D'HooreBelgian Defence, Brussels, Belgium.
Sebastiaan TuylsRespiratory Medicine, GasthuisZusters (GZA) Hospital Group, Antwerp, Belgium.
Brecht De TavernierEmergency Medicine and Intensive Care, GasthuisZusters (GZA) Hospital Group, Antwerp, Belgium.
Julie CatteeuwGeneral Hospital (AZ) Jan Palfijn, Ghent, Belgium.
Ali LotfiDepartment of Chemistry, University of Connecticut, Storrs, CT, United States.
Alexey MelnikDepartment of Chemistry, University of Connecticut, Storrs, CT, United States.
Alexander AksenovDepartment of Chemistry, University of Connecticut, Storrs, CT, United States.
Dominique GrandjeanNosaïs Program, Ecole Nationale Vétérinaire d'Alfort (Alfort School of Veterinary Medicine), University Paris-Est, Maisons-Alfort, France.
Miguel StevensVeterinary, Ypres, Belgium.
Frank GasthuysDepartment of Surgery, Anesthesiology and Orthopedics of Large Animals, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.
Hugues GuyotFaculty of Veterinary Medicine, Clinique Vétérinaire Universitaire (CVU), University of Liège, Liège, Belgium.
University of Liège · BEAZ Sint-Jan · BEOnze Lieve Vrouwziekenhuis Hospital · BEUniversity of Connecticut · USGhent University · BEGhent University Hospital · BEGZA Ziekenhuizen Campus Sint-Augustinus · BEZiekenhuisnetwerk Antwerpen Stuivenberg · BECentre Hospitalier Universitaire de Saint-Pierre · BEClinique Saint Pierre · BEÉcole Nationale Vétérinaire d'Alfort · FRUniversity of Namur · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detection dogs were trained to detect SARS-CoV-2 infection based on armpit sweat odor. Sweat samples were collected using cotton pads under the armpits of negative and positive human patients, confirmed by qPCR, for periods of 15-30 min. Multiple hospitals and organizations throughout Belgium participated in this study. The sweat samples were stored at -20°C prior to being used for training purposes. Six dogs were trained under controlled atmosphere conditions for 2-3 months. After training, a 7-day validation period was conducted to assess the dogs' performances. The detection dogs exhibited an overall sensitivity of 81%, specificity of 98%, and an accuracy of 95%. After validation, training continued for 3 months, during which the dogs' performances remained the same. Gas chromatography/mass spectrometry (GC/MS) analysis revealed a unique sweat scent associated with SARS-CoV-2 positive sweat samples. This scent consisted of a wide variety of volatiles, including breakdown compounds of antiviral fatty acids, skin proteins and neurotransmitters/hormones. An acceptability survey conducted in Belgium demonstrated an overall high acceptability and enthusiasm toward the use of detection dogs for SARS-CoV-2 detection. Compared to qPCR and previous canine studies, the detection dogs have good performances in detecting SARS-CoV-2 infection in humans, using frozen sweat samples from the armpits. As a result, they can be used as an accurate pre-screening tool in various field settings alongside the PCR test.

Indexed as

acceptability analysisaxillaCOVID-19detection dogsGC/MS (gas chromatograph/mass spectrometry)odorvaccination

Identifiers

PMID37822474
PMCPMC10563588
OpenAlexW4386894159

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.