Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.

Background: Passive leg raising (PLR) predicts fluid responsiveness in critical illness, although restrictions in mobilising patients often preclude this haemodynamic challenge being used. We investigated whether machine learning applied on transthoracic echocardiography (TTE) data might be used as a tool for predicting fluid responsiveness in critically ill patients.

Methods: We studied, 100 critically ill patients (mean age: 62 yr [standard deviation: 14]) with severe sepsis or septic shock prospectively over 24 months.

Integrated use of bedside lung ultrasound and echocardiography in acute respiratory failure: a prospective observational study in ICU.

Background: It has been suggested that the complementary use of echocardiography could improve the diagnostic accuracy of lung ultrasonography (LUS) in patients with acute respiratory failure (ARF). Nevertheless, the additional diagnostic value of echocardiographic data when coupled with LUS is still debated in this setting. The aim of the current study was to compare the diagnostic accuracy of LUS and an integrative cardiopulmonary ultrasound approach (thoracic ultrasonography [TUS]) in patients with ARF.

Accuracy of ultrasound B-lines score and E/Ea ratio to estimate extravascular lung water and its variations in patients with acute respiratory distress syndrome.

Extravascular lung water (EVLW) could increase by permeability pulmonary oedema, cardiogenic oedema, or both. Transthoracic echocardiography examination of a patient allows quantifying B-lines, originating from water-thickened interlobular septa, and the E/Ea ratio, related to pulmonary capillary wedge pressure. The aim of our study was to assess the correlation and the trending ability between EVLW measured by transpulmonary thermodilution and the B-lines score or the E/Ea ratio in patients with ARDS.