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Pendelluft diagnosed from ventilator weaning indexes obtained through bioelectrical impedance tomography: a case report

Overview of attention for article published in Sao Paulo Medical Journal, April 2017
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Title
Pendelluft diagnosed from ventilator weaning indexes obtained through bioelectrical impedance tomography: a case report
Published in
Sao Paulo Medical Journal, April 2017
DOI 10.1590/1516-3180.2016.025514102016
Pubmed ID
Authors

Fabiana Aparecida Lopes, Lidiane Andrade Monteiro de Souza, Juliana Tavares Neves Bernardi, Carlos Eduardo Rocha, Luciana Castilho de Figueiredo, Ana Paula Ragonete dos Anjos Agostini, Desanka Dragosavac, Daniela Cristina dos Santos Faez

Abstract

Today, through major technological advances in diagnostic resources within medicine, evaluation and monitoring of clinical parameters at the patient's bedside in intensive care units (ICUs) has become possible. This case report presents results and interpretations from predictive mechanical ventilation weaning indexes obtained through monitoring using chest electrical bioimpedance tomography. These indexes included maximum inspiratory pressure, maximum expiratory pressure, shallow breathing index and spontaneous breathing test. These were correlated with variations in tidal volume variables, respiratory rate, mean arterial pressure and peripheral oxygen saturation. Regarding the air distribution behavior in the pulmonary parenchyma, the patient showed the pendelluft phenomenon. Pendelluft occurs due to the time constant (product of the airways resistance and compliance) asymmetry between adjacent lung. Bioelectrical impedance tomography can help in weaning from mechanical ventilation, as in the case presented here. Pendelluft was defined as a limitation during the weaning tests.

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The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Student > Bachelor 2 22%
Professor 1 11%
Student > Ph. D. Student 1 11%
Unknown 3 33%
Readers by discipline Count As %
Engineering 2 22%
Nursing and Health Professions 1 11%
Neuroscience 1 11%
Social Sciences 1 11%
Unknown 4 44%