Esophageal pressure monitoring and its clinical significance in severe blast lung injury

Autor: Shifeng Shao, Zhengbin Wu, Yi Wang, Yaoli Wang, Zhen Wang, Huan Ye, Hui Zhao
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Bioengineering and Biotechnology, Vol 12 (2024)
Druh dokumentu: article
ISSN: 2296-4185
DOI: 10.3389/fbioe.2024.1280679
Popis: BackgroundThe incidence of blast lung injury (BLI) has been escalating annually due to military conflicts and industrial accidents. Currently, research into these injuries predominantly uses animal models. Despite the availability of various models, there remains a scarcity of studies focused on monitoring respiratory mechanics post-BLI. Consequently, our objective was to develop a model for monitoring esophageal pressure (Pes) following BLI using a biological shock tube (BST), aimed at providing immediate and precise monitoring of respiratory mechanics parameters post-injury.MethodsSix pigs were subjected to BLI using a BST, during which Pes was monitored. We assessed vital signs; conducted blood gas analysis, hemodynamics evaluations, and lung ultrasound; and measured respiratory mechanics before and after the inflicted injury. Furthermore, the gross anatomy of the lungs 3 h post-injury was examined, and hematoxylin and eosin staining was conducted on the injured lung tissues for further analysis.ResultsThe pressure in the experimental section of the BST reached 402.52 ± 17.95 KPa, with a peak pressure duration of 53.22 ± 1.69 ms. All six pigs exhibited an anatomical lung injury score ≥3, and pathology revealed classic signs of severe BLI. Post-injury vital signs showed an increase in HR and SI, along with a decrease in MAP (p < 0.05). Blood gas analyses indicated elevated levels of Lac, CO2-GAP, A-aDO2, HB, and HCT and reduced levels of DO2, OI, SaO2, and OER (p < 0.05). Hemodynamics and lung ultrasonography findings showed increased ELWI, PVPI, SVRI, and lung ultrasonography scores and decreased CI, SVI, GEDI, and ITBI (p < 0.05). Analysis of respiratory mechanics revealed increased Ppeak, Pplat, Driving P, MAP, PEF, Ri, lung elastance, MP, Ptp, Ppeak − Pplat, and ΔPes, while Cdyn, Cstat, and time constant were reduced (p < 0.05).ConclusionWe have successfully developed a novel respiratory mechanics monitoring model for severe BLI. This model is reliable, repeatable, stable, effective, and user-friendly. Pes monitoring offers a non-invasive and straightforward alternative to blood gas analysis, facilitating early clinical decision-making. Our animal study lays the groundwork for the early diagnosis and management of severe BLI in clinical settings.
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