Characterization of inflammatory profile by breath analysis in chronic coronary syndromes. Issue 9 (September 2020)

• Record Type: Journal Article
• Authors: Segreti, Andrea; Incalzi, Raffaele Antonelli; Lombardi, Marco; Miglionico, Marco; Nusca, Annunziata; Pennazza, Giorgio; Santonico, Marco; Grasso, Simone; Grigioni, Francesco; Di Sciascio, Germano
• Is Part Of: Journal of cardiovascular medicine. Volume 21:Issue 9(2020:Sep.)
• Publication Date: 2020-09
• Subjects: BIONOTE-V -- chronic coronary syndromes -- electronic nose (e-nose) -- volatile organic compounds; Cardiology -- Periodicals; Cardiovascular system -- Diseases -- Periodicals; Cardiology -- Periodicals; Cardiovascular Diseases -- Periodicals; 616.1005
• DOI: 10.2459/JCM.0000000000001032
• Languages: English
• ISSNs: 1558-2027

Abstract

Abstract : Aims: Exhaled breath contains thousands of volatile organic compounds (VOCs) produced during various metabolic processes both in health and disease. Analysis of breath with electronic nose BIONOTE-V allows modifications of exhaled VOCs to be studied, which are clinically recognized to be a marker for several disorders, including heart failure. New noninvasive tests based on VOCs analysis might be a useful tool for early detection of chronic coronary syndromes (CCS). Methods: Exhaled air was collected and measured in individuals with an indication to perform invasive coronary angiography (ICA). All patients' samples were obtained before ICA. Results: Analysis with BIONOTE-V was performed in a total cohort of 42 patients consecutively enrolled, of whom 19 did not require myocardial revascularization and 23 with indication for myocardial revascularization. BIONOTE-V was able to correctly identify 18 out of 23 patients affected by severe coronary artery disease (sensitivity = 78.3% and specificity = 68.4%). Our predicted model had a tight correlation with SYNTAX score (error of the BIONOTE-V = 15). Conclusion: CCS patients have a distinctive fingerprint of exhaled breath, and analysis by BIONOTE-V has the potential for identifying these patients. Moreover, it seems that this technique can correctly identify patients according to anatomical disease severity at ICA. If the preliminary data of this proof of concept study will be confirmed, this rapid and noninvasive diagnostic tool able to identify CCS might have an impact in routine clinical practice.