British journal of anaesthesia
-
Observational Study
Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.
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. ⋯ Machine learning generated several models for predicting fluid responsiveness that were comparable with the haemodynamic response to PLR.