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Towards chronic liver dysfunction self-monitoring: a proof-of-concept study

Contributo in Atti di convegno
Data di Pubblicazione:
2019
Abstract:
The liver is our very own chemical processing plant as it plays a vital role in maintaining the body's metabolic balance. Liver's health is assessed by a group of clinical tests (such as blood tests, ultrasonographic imaging, liver biopsy) most of which are invasive and burdensome for the patients. In the setting of severely scarred liver, toxic substances, such as ammonia, have fewer opportunities to be detoxified. Accumulation of ammonia in the systemic circulation and in the brain may result in Hepatic Encephalopathy (HE), a spectrum of neuropsychiatric abnormalities which entails changes in consciousness, intellectual functions, behavior. Minimal HE has attracted increasing attention, as it does not cause detectable changes in personality or behaviour, but the complex and sustained attention is impaired. Hence, it can be detected only by specific but biased, time-consuming and burdensome examinations, such as blood ammonia levels assessment and neuro-psychological tests. The obstrusivity of the majority of the liver function clinical tests, and, in case of minimal HE, the lack of reliable examinations, are encouraging the scientific community to look for alternative diagnostic methods. For this purpose, the exploitation of a non-invasive technique such as breath analysis, to identify chronic liver disease, discriminate among its degree of severity and detect the onset of HE, could be a step forward for clinical diagnosis. In this paper, we report a proof-of-concept study that aimed at detecting ammonia in the breath of patients suffering from chronic liver disease by means of a low-cost, easy-to-use, gas-sensors based device. Not only, we also aimed at investigating the possibility of discriminating the several severity degree of liver impairment on the basis of the detected ammonia.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Breath analysis; Liver function; Liver disease; Gas sensors; Data analysis; Biomedical Devices
Elenco autori:
D'Acunto, Mario; Germanese, Danila; Colantonio, Sara
Autori di Ateneo:
COLANTONIO SARA
D'ACUNTO MARIO
GERMANESE DANILA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/407248
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/407248/91507/prod_424174-doc_181262.pdf
Pubblicato in:
PROCEEDINGS - IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS
Series
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URL

https://ieeexplore.ieee.org/abstract/document/8969605
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