Predicting intraoperative hypotension: from hope to hype and back to reality

The analysis of arterial pressure waveforms with machine learning algorithms has been proposed to predict intraoperative hypotension. The ability to forecast arterial hypotension 5-15 min ahead of the fall in blood pressure allows clinicians to be pro-active instead of reactive, and could potentially decrease postoperative morbidity. However, the predictive value of machine learning algorithms has been overestimated due to selection bias in several clinical studies, and they might not be superior to mere observation of arterial pressure. Continuous blood pressure monitoring enables immediate detection of hypotension, and giving fluid, vasopressors or inotropes to patients who are not yet (and might never become) hypotensive based on an algorithm is questionable. Finally, recent prospective interventional studies suggest that reducing intraoperative hypotension does not improve postoperative outcomes.