机械通风
鼻子
败血症
医学
通风(建筑)
重症监护医学
工程类
生物医学工程
外科
内科学
机械工程
作者
Stefano Robbiani,Louwrina H. te Nijenhuis,Patricia A. C. Specht,Emanuele Zanni,Carmen Bax,Egbert G. Mik,Floor A. Harms,Willem van Weteringen,Laura Capelli,Raffaele L. Dellacá
出处
期刊:Sensors
[Multidisciplinary Digital Publishing Institute]
日期:2025-05-26
卷期号:25 (11): 3343-3343
摘要
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.
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