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

Author:

Denn Sara,Schneck EmmanuelORCID,Jablawi Fidaa,Bender Michael,Schmidt Götz,Habicher Marit,Uhl Eberhard,Sander Michael

Abstract

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.

Funder

Justus-Liebig-Universität Gießen

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Role of artificial intelligence in haemodynamic monitoring;Indian Journal of Anaesthesia;2024-01

2. Tranexamic-acid;Reactions Weekly;2023-04-29

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