The use of artificial intelligence and machine learning monitoring to safely administer a fluid-restrictive goal-directed treatment protocol to minimize the risk of transfusion during major spine surgery of a Jehovah’s Witness: a case report

Abstract

Background The Hypotension Prediction Index (HPI) displays an innovative monitoring tool which predicts intraoperative hypotension before its onset. Case presentation We report the case of an 84-year-old Caucasian woman undergoing major spinal surgery with no possibility for the transfer of blood products given her status as a Jehovah’s Witness. The hemodynamic treatment algorithm we employed was based on HPI and resulted in a high degree of hemodynamic stability during the surgical procedure. Further, the patient was not at risk for either hypo- or hypervolemia, conditions which might have caused dilution anemia. By using HPI as a tool for patient blood management, it was possible to reduce the incidence of intraoperative hypotension to a minimum. Conclusions In sum, this HPI-based treatment algorithm represents a useful application for the treatment of complex anesthesia and perioperative patient blood management. It is a simple but powerful extension of standard monitoring for the prevention of intraoperative hypotension.

Role of artificial intelligence in haemodynamic monitoring

“…Using pre-operative and intra-operative data, a real-time prediction model for large transfusion during surgery showed high accuracy (AUROC of 0.972 in internal validation and 0.943 in external validation). [ 21 ] This model shows the promise of AI-supported clinical decision-making in surgical settings by enabling early identification of high-risk patients and maybe enabling timely interventions.…”

Technological advancements, digital transformation, and future trends in blood transfusion services

“…Patient blood management (PBM) has played an important role in perioperative management, and an HPI-based treatment algorithm is a useful tool for patient blood management. 29…”