Stein Silva1, Dalinda Ait Aissa, Pierre Cocquet, Lucille Hoarau, Jean Ruiz, Fabrice Ferre, David Rousset, Michel Mora, Arnaud Mari, Olivier Fourcade, Béatrice Riu, Samir Jaber, Bénoît Bataille. 1. From the Critical Care Unit (S.S., D.A.A., L.H., F.F., D.R., A.M., B.R.) and Critical Care and Anaesthesiology Department (S.S., D.A.A., L.H., J.R., F.F., D.R., A.M., O.F., B.R.), University Teaching Hospital of Purpan, Toulouse, France; French National Institute of Health and Medical Research U1214, University Teaching Hospital of Purpan, Toulouse, France (S.S.); Critical Care Unit, Hopital Dieu Hospital, Narbonne, France (P.C., M.M., B.B.); Critical Care Unit, University Cancer Institute Hospital of Toulouse, France (J.R.); and Intensive Care Unit and Transplantation, Department of Anaesthesiology and Critical Care B, Saint Eloi Hospital, Montpellier, France (S.J.).
Abstract
BACKGROUND: Recent studies suggest that isolated sonographic assessment of the respiratory, cardiac, or neuromuscular functions in mechanically ventilated patients may assist in identifying patients at risk of postextubation distress. The aim of the present study was to prospectively investigate the value of an integrated thoracic ultrasound evaluation, encompassing bedside respiratory, cardiac, and diaphragm sonographic data in predicting postextubation distress. METHODS: Longitudinal ultrasound data from 136 patients who were extubated after passing a trial of pressure support ventilation were measured immediately after the start and at the end of this trial. In case of postextubation distress (31 of 136 patients), an additional combined ultrasound assessment was performed while the patient was still in acute respiratory failure. We applied machine-learning methods to improve the accuracy of the related predictive assessments. RESULTS: Overall, integrated thoracic ultrasound models accurately predict postextubation distress when applied to thoracic ultrasound data immediately recorded before the start and at the end of the trial of pressure support ventilation (learning sample area under the curve: start, 0.921; end, 0.951; test sample area under the curve: start, 0.972; end, 0.920). Among integrated thoracic ultrasound data, the recognition of lung interstitial edema and the increased telediastolic left ventricular pressure were the most relevant predictive factors. In addition, the use of thoracic ultrasound appeared to be highly accurate in identifying the causes of postextubation distress. CONCLUSIONS: The decision to attempt extubation could be significantly assisted by an integrative, dynamic, and fully bedside ultrasonographic assessment of cardiac, lung, and diaphragm functions.
BACKGROUND: Recent studies suggest that isolated sonographic assessment of the respiratory, cardiac, or neuromuscular functions in mechanically ventilated patients may assist in identifying patients at risk of postextubation distress. The aim of the present study was to prospectively investigate the value of an integrated thoracic ultrasound evaluation, encompassing bedside respiratory, cardiac, and diaphragm sonographic data in predicting postextubation distress. METHODS: Longitudinal ultrasound data from 136 patients who were extubated after passing a trial of pressure support ventilation were measured immediately after the start and at the end of this trial. In case of postextubation distress (31 of 136 patients), an additional combined ultrasound assessment was performed while the patient was still in acute respiratory failure. We applied machine-learning methods to improve the accuracy of the related predictive assessments. RESULTS: Overall, integrated thoracic ultrasound models accurately predict postextubation distress when applied to thoracic ultrasound data immediately recorded before the start and at the end of the trial of pressure support ventilation (learning sample area under the curve: start, 0.921; end, 0.951; test sample area under the curve: start, 0.972; end, 0.920). Among integrated thoracic ultrasound data, the recognition of lung interstitial edema and the increased telediastolic left ventricular pressure were the most relevant predictive factors. In addition, the use of thoracic ultrasound appeared to be highly accurate in identifying the causes of postextubation distress. CONCLUSIONS: The decision to attempt extubation could be significantly assisted by an integrative, dynamic, and fully bedside ultrasonographic assessment of cardiac, lung, and diaphragm functions.
Authors: Alexis Ferré; Max Guillot; Daniel Lichtenstein; Gilbert Mezière; Christian Richard; Jean-Louis Teboul; Xavier Monnet Journal: Intensive Care Med Date: 2019-03-12 Impact factor: 17.440
Authors: Belaid Bouhemad; Francesco Mojoli; Nicolas Nowobilski; Arif Hussain; Isabelle Rouquette; Pierre- Grégoire Guinot; Silvia Mongodi Journal: Intensive Care Med Date: 2020-01-08 Impact factor: 17.440
Authors: Maurizio Cereda; Yi Xin; Alberto Goffi; Jacob Herrmann; David W Kaczka; Brian P Kavanagh; Gaetano Perchiazzi; Takeshi Yoshida; Rahim R Rizi Journal: Anesthesiology Date: 2019-09 Impact factor: 7.892