Sepsis is a severe systemic condition due to an extreme response of the body to an infection. It is responsible for a significant number of deaths worldwide, and is still difficult to diagnose early. In this study, a system was developed for exhaled breath sampling in mechanically ventilated patients at the intensive care unit (ICU), together with a custom-made electronic nose (e-Nose) device for detecting sepsis in exhaled breath. The diagnostic performance of this system was evaluated in an animal sepsis model. Ten pigs (LPS group) were administered lipopolysaccharide (LPS) to induce a systemic inflammatory response. Nine other pigs received a placebo solution (control group). Exhaled breath samples were collected in NalophanTM bags and stored for temperature and humidity equilibration before e-Nose analysis. Measurements were corrected for the effects of different fractions of inspired oxygen (FiO2) on e-Nose sensors. Two classification models using e-Nose and physiological measurements were developed and compared. One hour after LPS administration, the e-Nose data model with FiO2 correction showed a higher accuracy (76.2% (95% confidence interval (CI) [58.0, 94.2])) than the physiological data model (59.0% (95% CI [39.5, 79.5])), indicating the potential of the early detection of sepsis with an e-Nose.
Development of an E-Nose System for the Early Diagnosis of Sepsis During Mechanical Ventilation: A Porcine Feasibility Study
Robbiani, Stefano;Zanni, Emanuele;Bax, Carmen;Capelli, Laura;Dellaca', Raffaele
2025-01-01
Abstract
Sepsis is a severe systemic condition due to an extreme response of the body to an infection. It is responsible for a significant number of deaths worldwide, and is still difficult to diagnose early. In this study, a system was developed for exhaled breath sampling in mechanically ventilated patients at the intensive care unit (ICU), together with a custom-made electronic nose (e-Nose) device for detecting sepsis in exhaled breath. The diagnostic performance of this system was evaluated in an animal sepsis model. Ten pigs (LPS group) were administered lipopolysaccharide (LPS) to induce a systemic inflammatory response. Nine other pigs received a placebo solution (control group). Exhaled breath samples were collected in NalophanTM bags and stored for temperature and humidity equilibration before e-Nose analysis. Measurements were corrected for the effects of different fractions of inspired oxygen (FiO2) on e-Nose sensors. Two classification models using e-Nose and physiological measurements were developed and compared. One hour after LPS administration, the e-Nose data model with FiO2 correction showed a higher accuracy (76.2% (95% confidence interval (CI) [58.0, 94.2])) than the physiological data model (59.0% (95% CI [39.5, 79.5])), indicating the potential of the early detection of sepsis with an e-Nose.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


