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用于机械通气期间脓毒症早期诊断的电子鼻系统的开发:一项猪模型可行性研究

Development of an E-Nose System for the Early Diagnosis of Sepsis During Mechanical Ventilation: A Porcine Feasibility Study.

作者信息

Robbiani Stefano, Te Nijenhuis Louwrina H, Specht Patricia A C, Zanni Emanuele, Bax Carmen, Mik Egbert G, Harms Floor A, Weteringen Willem van, Capelli Laura, Dellacà Raffaele L

机构信息

Department of Electronics, Information, and Bioengineering, Politecnico di Milano, 20133 Milano, Italy.

Department of Neonatal and Pediatric Intensive Care, Division of Neonatology, Erasmus MC Sophia Children's Hospital, University Medical Center Rotterdam, 3015 GD Rotterdam, The Netherlands.

出版信息

Sensors (Basel). 2025 May 26;25(11):3343. doi: 10.3390/s25113343.

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 Nalophan bags and stored for temperature and humidity equilibration before e-Nose analysis. Measurements were corrected for the effects of different fractions of inspired oxygen (FiO) 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 FiO 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.

摘要

脓毒症是一种严重的全身性疾病,起因是身体对感染产生的极端反应。它在全球导致大量死亡,且早期诊断仍很困难。在本研究中,开发了一种用于重症监护病房(ICU)机械通气患者的呼气采样系统,以及一种定制的电子鼻设备,用于检测呼气中的脓毒症。该系统的诊断性能在动物脓毒症模型中进行了评估。十头猪(脂多糖组)被给予脂多糖(LPS)以诱导全身性炎症反应。另外九头猪接受安慰剂溶液(对照组)。呼气样本收集在纳洛芬袋中,并在进行电子鼻分析前储存以实现温度和湿度平衡。针对吸入氧不同分数(FiO)对电子鼻传感器的影响对测量值进行了校正。开发并比较了两种使用电子鼻和生理测量值的分类模型。给予LPS一小时后,经FiO校正的电子鼻数据模型显示出比生理数据模型更高的准确率(76.2%(95%置信区间[CI][58.0, 94.2]))(59.0%(95% CI [39.5, 79.5])),这表明电子鼻在脓毒症早期检测方面具有潜力。

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