Three Different GHDT ( Goal Hemodynamic Directed Therapy) Strategies for Intraoperative Fluid Management Optimization During Major Abdominal Surgery: A Randomized Controlled Trial

"Traditional management of hemodynamic parameters and intraoperative fluids without the aid of predictive tools based on artificial intelligence.~Possibility of having advanced hemodynamic analysis tools such as SV (stroke volume), SVV (stroke volume variation), PPV (pulse pressure variation), CO (cardiac output).~The anesthetist will decide whether to administer fluids, vasopressors, or other pharmacological interventions to maintain hemodynamic stability basing on clinical hemodynamic parameters derived from pulse contour systems, in accordance with a specific flowchart.~Interventions will be applied when blood pressure decreases, or clinical signs of instability are observed"

"The Hypotension Prediction Index (HPI) is an advanced arterial waveform analysis algorithm that uses machine learning to predict hypotensive episodes (defined as mean arterial pressure \[MAP\] \< 65 mmHg) five minutes in advance, achieving high sensitivity and specificity. This technology is based on patient demographic data (e.g., age, height, weight) and hemodynamic parameters derived from arterial waveform analysis.~* HPI uses demographic information and hemodynamic signals obtained via a radial arterial catheter.~* The signals are analyzed using Edwards Lifesciences' Acumen IQ software, which has been further developed to include prediction of hypotensive episodes.~The algorithm provides a numerical value (0-100) reflecting the risk of imminent hypotension. An HPI value above 85 signals a high likelihood of hypotension.~The system also provides advanced hemodynamic data, including cardiac output, dynamic arterial elastance, dP/dtmax (systolic slope), and stroke volume."

"HPI: Provides a predictive index (from 0 to 100) based on real-time hemodynamic data, indicating the probability of the patient developing a hypotensive episode (MAP \< 65 mmHg) within the next 10-15 minutes.~AFM: In addition to hypotension prediction, continuously monitors parameters such as stroke volume and cardiac output, providing indications for optimal fluid administration. It is programmed to suggest the quantity and the speed of fluid administration based on real-time data and patient conditions.~In conjunction with the HPI system, the AFM suggests administering a specific fluid volume to correct the patient's hemodynamic status.~The AFM uses a predictive algorithm to calculate the patient's response to fluid administration, enabling anesthetists to dynamically adjust therapy.~The AFM system is based on assisted clinical decisions, where anesthetist receive algorithm-based AI recommendations to proactively administer fluids, avoiding the traditional reactive approach."