Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractThe human repertoire of odorant receptor genes and pseudogenes    Next AbstractFormation and emission of volatile polonium compound by microbial activity and polonium methylation with methylcobalamin »

Surg Innov


Title:Can Electric Nose Breath Analysis Identify Abdominal Wall Hernia Recurrence and Aortic Aneurysms? A Proof-of-Concept Study
Author(s):Mommers EHH; van Kooten L; Nienhuijs SW; de Vries Reilingh TS; Lubbers T; Mees BME; Schurink GWH; Bouvy ND;
Address:"Maastricht University Medical Center, Maastricht, Netherlands. Catharina Hospital, Eindhoven, Netherlands. Elkerliek Hospital, Helmond, Brabant, Netherlands"
Journal Title:Surg Innov
Year:2020
Volume:20200523
Issue:4
Page Number:366 - 372
DOI: 10.1177/1553350620917898
ISSN/ISBN:1553-3514 (Electronic) 1553-3506 (Print) 1553-3506 (Linking)
Abstract:"Introduction. This pilot study evaluates if an electronic nose (eNose) can distinguish patients at risk for recurrent hernia formation and aortic aneurysm patients from healthy controls based on volatile organic compound analysis in exhaled air. Both hernia recurrence and aortic aneurysm are linked to impaired collagen metabolism. If patients at risk for hernia recurrence and aortic aneurysms can be identified in a reliable, low-cost, noninvasive manner, it would greatly enhance preventive options such as prophylactic mesh placement after abdominal surgery. Methods. From February to July 2017, a 3-armed proof-of-concept study was conducted at 3 hospitals including 3 groups of patients (recurrent ventral hernia, aortic aneurysm, and healthy controls). Patients were measured once at the outpatient clinic using an eNose with 3 metal-oxide sensors. A total of 64 patients (hernia, n = 29; aneurysm, n = 35) and 37 controls were included. Data were analyzed by an automated neural network, a type of self-learning software to distinguish patients from controls. Results. Receiver operating curves showed that the automated neural network was able to differentiate between recurrent hernia patients and controls (area under the curve 0.74, sensitivity 0.79, and specificity 0.65) as well as between aortic aneurysm patients and healthy controls (area under the curve 0.84, sensitivity 0.83, and specificity of 0.81). Conclusion. This pilot study shows that the eNose can distinguish patients at risk for recurrent hernia and aortic aneurysm formation from healthy controls"
Keywords:"*Aortic Aneurysm Breath Tests Electronic Nose *Hernia, Ventral Humans Pilot Projects Aeonose aneurysm electric nose (eNose) hernia recurrence volatile organic compounds (VOC);"
Notes:"MedlineMommers, Elwin H H van Kooten, Lottie Nienhuijs, Simon W de Vries Reilingh, Tammo S Lubbers, Tim Mees, Barend M E Schurink, Geert Willem H Bouvy, Nicole D eng 2020/05/26 Surg Innov. 2020 Aug; 27(4):366-372. doi: 10.1177/1553350620917898. Epub 2020 May 23"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 03-07-2024