基于机器学习的低血压预测指数指导术中血压管理的研究进展  

Research progress on intraoperative blood pressure management guided by hypotension prediction index based on machine learning

作　　者：许琳涓[1] 李轶[1] 谢建琴[1] XU Linjuan;LI Yi;XIE Jianqin(Department of Anesthesiology,Lanzhou University Second Hospital,Lanzhou 730030,China)

机构地区：[1]兰州大学第二医院麻醉科,730030

出　　处：《临床麻醉学杂志》2024年第9期966-970,共5页Journal of Clinical Anesthesiology

基　　金：甘肃省自然科学基金(22JR5RA1004);兰州大学第二医院“萃英科技创新”计划(CY2020-MS18)。

摘　　要：术中低血压与术后不良预后密切相关。基于机器学习的低血压预测指数(HPI)利用有创和无创血压监测在非心脏和心脏手术中可以预测低血压,使术中血压管理由被动处理转变为预防性的主动控制。HPI的血流动力学管理减少了术中低血压的发生。本文从HPI概述、HPI有创和无创血压监测在手术中的应用以及HPI的局限性等方面进行综述。Intraoperative hypotension is closely associated with postoperative poor prognosis.Machine learning hypotension predictive index(HPI)based on invasive and non-invasive blood pressure monitoring can predict hypotension in non-cardiac and cardiac surgery,which makes blood pressure management from passive processing to preventive active control.Hemodynamic management based on HPI reduces the occurrence of hypotension in surgery.In this artical,the introduction of HPI,the application of HPI invasive and non-invasive blood pressure monitoring in surgery,and the limitations of HPI are reviewed.

关 键 词：机器学习 低血压预测指数 血压管理 

分 类 号：R614[医药卫生—麻醉学]