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1.
Surg Innov ; 29(5): 671-673, 2022 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34530668

RESUMO

Chest tubes in patients who have undergone pulmonary resection with pleural air leak are painful, impair ventilatory mechanics, and increase hospital length of stay and costs. Despite these well-documented concerns, current protocols for chest tube management in this setting are not well supported by evidence. Excessive suction applied to chest tubes has been associated with prolonged air leak due to alveolar over-distension, and most practitioners intuit that suction should be minimized to the lowest level needed to maintain desired pleural apposition. Unfortunately, there is no evidence-based protocol for the establishment of minimal adequate suction. Digital suction devices in current clinical use can identify air leak resolution preventing the delay of chest tube removal but cannot guide suction minimization while an air leak persists. We recently described a monitor of lung expansion in a porcine model of pleural air leak that could detect loss of pleural apposition continuously in real-time based on electrical impedance readings obtained directly from the surface of the lung via chest tube-embedded electrodes. The value of the impedance signal was "in-range" when pleural apposition was present but became abruptly "out-of-range" when pneumothorax due to inadequate suction developed. These findings suggested that a digitally controlled suction pump system could be programmed to recognize the development of pneumothorax and automatically identify and set the minimum level of suction required to maintain pleural apposition. We present here preliminary proof of concept for this system.


Assuntos
Tubos Torácicos , Pneumotórax , Suínos , Animais , Pneumotórax/prevenção & controle , Pneumotórax/diagnóstico , Pneumonectomia/métodos , Sucção/métodos , Drenagem/métodos
4.
J Thorac Cardiovasc Surg ; 166(1): 60-61, 2023 07.
Artigo em Inglês | MEDLINE | ID: mdl-35249762
5.
Semin Thorac Cardiovasc Surg ; 34(2): 417-418, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34004310
6.
JTCVS Tech ; 9: 78-79, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34647065
7.
JTCVS Tech ; 10: 280-281, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34984387
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