Elina Jokiniitty1, Lauri Hokkinen1, Pekka Kumpulainen2, Yrjö Leskinen3, Terho Lehtimäki1,4, Niku Oksala1,2, Antti Roine1. 1. Department of Surgery, Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland. 2. Centre for Vascular Surgery & Interventional Radiology, Tampere University Hospital, Tampere, Finland. 3. Department of Internal Medicine, Tampere University Hospital, Tampere, Finland. 4. Department of Clinical Chemistry, Fimlab Laboratories & Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine & Health Technology, Tampere University.
Abstract
Electronic noses (eNoses) are an emerging class of experimental diagnostic tools. They are based on the detection of volatile organic compounds. Urine is used as sample medium in several publications but neither the effect of chronic kidney disease (CKD) on the analysis nor the potential to detect CKD has been explored. Materials & methods: We utilized an eNose based on field asymmetric ion mobility spectrometry (FAIMS) technology to classify urine samples from CKD patients and controls. Results: We were able to differentiate extremes of kidney function with an accuracy of 81.4%. Conclusion: In this preliminary study, applying eNose technology we were able to distinguish the patients with impaired kidney function from those with normal kidney function.
Electronic noses (eNoses) are an emerging class of experimental diagnostic tools. They are based on the detection of volatile organic compounds. Urine is used as sample medium in several publications but neither the effect of chronic kidney disease (CKD) on the analysis nor the potential to detect CKD has been explored. Materials & methods: We utilized an eNose based on field asymmetric ion mobility spectrometry (FAIMS) technology to classify urine samples from CKDpatients and controls. Results: We were able to differentiate extremes of kidney function with an accuracy of 81.4%. Conclusion: In this preliminary study, applying eNose technology we were able to distinguish the patients with impaired kidney function from those with normal kidney function.
Authors: Jutta E Laiho; Olli H Laitinen; Johannes Malkamäki; Leena Puustinen; Aki Sinkkonen; Juha Pärkkä; Heikki Hyöty Journal: Environ Epidemiol Date: 2022-06-08