Wijnberge M, Geerts BF, Hol L, et al. - Given a link of intraoperative hypotension with increased morbidity and mortality, and since a machine learning–derived early warning system for predicting hypotension shortly prior to its occurrence has been built and validated, so, researchers undertook this single-center preliminary unblinded randomized clinical trial to investigate if a reduction in intraoperative hypotension could be achieved with the clinical application of the early warning system together with a hemodynamic diagnostic guidance and treatment protocol. This inquiry was undertaken in a tertiary center in Amsterdam, the Netherlands. Participants were adult patients who were scheduled for elective noncardiac surgery under general anesthesia and having an indication for continuous invasive blood pressure monitoring. Randomly, the participants were allocated to receive either the early warning system (n = 34) or standard care (n = 34), with a target mean arterial pressure of at least 65 mm Hg in both groups. Findings revealed less intraoperative hypotension in relation to the use of a machine learning–derived early warning system vs standard care. For patients who were randomized to the early warning system compared with those receiving standard care, the time-weighted average of hypotension was identified to be 0.10 mm Hg vs 0.44 mm Hg, respectively, a difference that was statistically significant.