Chiara Vernile

Comorbidity modulates non invasive ventilation-induced changes in breath print of obstructive sleep apnea syndrome patients

IntroductionIn obstructive sleep apnea syndrome (OSAS), exhaled volatile organic compounds (VOCs) change after long-term continuous positive airway pressure (CPAP). The objective of the study was to verify whether changes in VOCs pattern are detectable after the first night of CPAP and to identify correlates, if any, of these changes.MethodsFifty OSAS patients underwent a multidimensional assessment and breath print (BP) analysis through 28 sensors e-nose at baseline and after the first night of CPAP. Boxplots of individual BP evolution after CPAP and groups were compared by ANOVA and Fisher’s exact t. Partial least square discriminant analysis (PLS-DA), with leave-one-out as cross-validation was used to calculate to which extent basal BP could predicts changes in apnea-hypopnea index (AHI).ResultsCPAP was effective in all the patients (delta AHI 35.8 events/h; residual AHI 6.0 events/h). BP dramatically changed after a single-night CPAP and changes conformed to two well-distinguished patterns: pattern C (n = 29), characterized by consonant boxplots, and pattern D (n = 21), with variably discordant boxplots. The average number of comorbid diseases (1.55 [standard deviation, SD 1.0] in group C, 3.14 [SD 1.8] in group D, p < 0.001) and the prevalence of selected comorbidity (diabetes mellitus, metabolic syndrome, and chronic heart failure), were the only features distinguishing groups.ConclusionWe found that BP change after a single night of CPAP largely depends upon comorbidity. Comorbidity likely contributes to phenotypic variability in OSAS population. BP might qualify as a surrogate index of the response to and, later, compliance with CPAP.

Breath-print analysis by e-nose for classifying and monitoring chronic liver disease: A proof-of-concept study

Since the liver plays a key metabolic role, volatile organic compounds in the exhaled breath might change with type and severity of chronic liver disease (CLD). In this study we analysed breath-prints (BPs) of 65 patients with liver cirrhosis (LC), 39 with non-cirrhotic CLD (NC-CLD) and 56 healthy controls by the e-nose. Distinctive BPs characterized LC, NC-CLD and healthy controls, and, among LC patients, the different Child-Pugh classes (sensitivity 86.2% and specificity 98.2% for CLD vs healthy controls, and 87.5% and 69.2% for LC vs NC-CLD). Moreover, the area under the BP profile, derived from radar-plot representation of BPs, showed an area under the ROC curve of 0.84 (95% CI 0.76–0.91) for CLD, of 0.76 (95% CI 0.66–0.85) for LC, and of 0.70 (95% CI 0.55–0.81) for decompensated LC. By applying the cut-off values of 862 and 812, LC and decompensated LC could be predicted with high accuracy (PPV 96.6% and 88.5%, respectively). These results are proof-of-concept that the e-nose could be a valid non-invasive instrument for characterizing CLD and monitoring hepatic function over time. The observed classificatory properties might be further improved by refining stage-specific breath-prints and considering the impact of comorbidities in a larger series of patients.

Multi-Sensor Approach for the Monitoring of Halitosis Treatment via Lactobacillus brevis (CD2)-Containing Lozenges--A Randomized, Double-Blind Placebo-Controlled Clinical Trial.

The aim of this randomized clinical trial was to evaluate whether a recently described multi-sensor approach called BIONOTE® is accurate enough to verify the efficacy of treatment of patients with halitosis. A treatment with Lactobacillus brevis (CD2)–containing lozenges, compared with placebo was tested. The BIONOTE® was compared with traditional techniques used to detect halitosis: OralChroma™ and two calibrated odor judges enrolled for the organoleptic assessments. Twenty patients (10 treated and 10 placebo), suffering from active phase halitosis were included in the study. Treatment consisted of Lactobacillus brevis (CD2)—containing lozenges or placebo, 4 tablets/day for 14 days. t0 was before the beginning of the study; t1 was day 7 and t2 was day 14. The effectiveness of treatment was assessed through: (1) Rosenberg score; (2) Winkel tongue coating index (WTCI) anterior and posterior; (2) OralChroma™; (3) the new developed multi-sensor approach, called BIONOTE® (test technique). Only the WTCI anterior revealed statistically significant changes between t0 and t2 data (p = 0.014) in the treated group. Except for the WTCI anterior, all diagnostic methods revealed the lack of effectiveness for halitosis of a 14-days treatment with Lactobacillus brevis (CD2)–containing lozenges. The BIONOTE® multisensor system seems accurate in addition to OralChroma™ to assess the initial condition of halitosis and its mitigation during treatment.

Screening of Obstructive Sleep Apnea Syndrome by Electronic-Nose Analysis of Volatile Organic Compounds

Obstructive Sleep Apnea Syndrome (OSAS) carries important social and economic implications. Once the suspicion of OSAS has arisen, Polysomnography (PSG) represents the diagnostic gold standard. However, about 45% of people who have undergone PSG are free from OSAS. Thus, efforts should be made to improve the selection of subjects. We verified whether the pattern of Volatile Organic Compounds (VOCs) helps to select patients amenable to PSG. We studied 136 subjects (20 obese non-OSAS, 20 hypoxic OSAS, 20 non-hypoxic OSAS, and 20 non-hypoxic Chronic Obstructive Pulmonary Disease (COPD) vs 56 healthy controls) without any criteria of exclusion for comorbidity to deal with a real-life population. VOCs patterns were analyzed using electronic-nose (e-nose) technology. A Discriminant Analysis (Partial Least Square-Discriminant Analysis) was performed to predict respiratory functions and PSG parameters. E-nose distinguished controls (100% correct classification) from others and identified 60% of hypoxic, and 35% of non-hypoxic OSAS patients. Similarly, it identified 60% of COPD patients. One-by-one group comparison yielded optimal discrimination of OSAS vs controls and of COPD vs controls (100% correct classification). In conclusion, e-nose technology applied to breath-analysis can discriminate non-respiratory from respiratory diseased populations in real-life multimorbid populations and exclude OSAS. If confirmed, this evidence may become pivotal for screening purposes.

Breathprinting of liver diseases

Breath analysis is a non-invasive diagnostic procedure that allows the identification of different diseases from volatile organic compounds (VOCs). These are detected by the electronic nose (e-nose), through an array of gas sensors, whose output consists of a breath fingerprint (breathprint (BP)). The present study aims at determining whether this type of analysis is able to discriminate liver cirrhosis (LC), chronic hepatitis (CH) and to identify the LC stage. This study also aims at analyzing the discriminative and classificatory properties of the e-nose in patients with chronic liver disease (CLD) and at discriminating the different classes of Child-Pugh (CPC) among LC patients. The BIONOTE is the e-nose used is this study, and the exhaled breath collection is performed via Pneumopipe. The results obtained show that this system could be a non-invasive tool for early diagnosis valid for the characterization of liver disease and for the monitoring of liver function through a qualitative analysis of breathprint. Refining stage-specific BP and considering the impact of comorbidities, such as renal failure, in a larger population, might further improve the measure chain classificatory effectiveness.

P0192 : Assessment of liver function by the exhaled breath-print during chronic liver disease

P0191 IFN-FREE REGIMENS OVERCOME THE NEGATIVE EFFECT OF PORTAL HYPERTENSION ON VIROLOGIC RESPONSE AND VIRAL KINETICS IN PATIENTS WITH CIRRHOSIS M. Mandorfer, K. Kozbial, C. Freissmuth, P. Schwabl, A.F. Stattermayer, T. Reiberger, S. Beinhardt, R. Schwarzer, M. Trauner, A. Ferlitsch, H. Hofer, M. Peck-Radosavljevic, P. Ferenci, on behalf of Vienna Hepatic Hemodynamic Lab. Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria E-mail: mattias.mandorfer@meduniwien.ac.at