Predicting Intraoperative Hypotension: An Intraoperative Case Report-Predicting Intraoperative Hypotension: An Intraoperative Case Report

Predicting Intraoperative Hypotension: An Intraoperative Case Report

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Intraoperative hypotension (IOH) is a prevalent issue during surgeries, especially noncardiac ones, defined by a mean arterial pressure (MAP) below 65 mm Hg for over a minute. It's linked to serious postoperative complications, including acute kidney injury, myocardial damage, stroke, and mortality. Traditional methods rely on post-occurrence treatment, but new technology offers proactive management opportunities.<br /><br />This article explores advanced hemodynamic monitoring technologies, especially a Hypotension Prediction Index (HPI) system combined with the HemoSphere platform, to anticipate and manage IOH before it develops into a clinical crisis. The HPI uses machine learning to analyze arterial waveforms, providing early warning and enabling anesthesiologists to address potential causes like decreased contractility, preload issues, and afterload deficiencies. The effectiveness of these newer interventions is compared to absolute MAP thresholds, which are easier to maintain than the traditional relative thresholds based on individual preoperative norms.<br /><br />A case report details a 74-year-old patient undergoing pancreaticoduodenectomy, demonstrating the technology's application. Here, high HPI scores indicated impending hypotension before clinical signs were apparent, allowing for timely intervention. The case highlighted decreased contractility from deep anesthesia levels, which was corrected with ephedrine. The situation underscored the potential benefit of acting on early warnings from the HPI system, which might have prevented the drop in blood pressure entirely.<br /><br />The article stresses the transition from reactive to proactive management of IOH thanks to advancements in predictive tech like HPI. While some anesthesiologists may initially hesitate to treat based on predictive warnings, increased adoption and familiarity may enhance their trust in these tools and ultimately improve patient outcomes by reducing the incidence and severity of IOH.

Keywords

intraoperative hypotension

Hypotension Prediction Index

hemodynamic monitoring

arterial waveforms

machine learning

HemoSphere platform

anesthesia management

proactive intervention

patient outcomes

predictive technology