Sarhadi Kamron, Hamman Justin, Avila Jorge, Jian Zhongping, Fleming Neal W
Department of Anesthesia & Perioperative Care, University of California, San Francisco, San Francisco, CA, USA.
Department of Anesthesiology & Pain Medicine, University of California, Davis School of Medicine, 4150 V Street PSSB- Suite1200, Sacramento, CA, 95817-1460, USA.
BMC Anesthesiol. 2025 Apr 29;25(1):221. doi: 10.1186/s12871-025-03086-y.
The Hypotension Prediction Index (HPI) derived using an Acumen™ arterial pressure transducer can decrease the incidence of intraoperative hypotension and possibly decrease perioperative complications. The HPI can also be obtained from the ClearSight™ continuous non-invasive blood pressure monitor. Concurrent comparison of HPI values obtained from these two pressure inputs is limited and additional comparisons could increase clinician confidence in non-invasive hemodynamic monitoring, expand its applications and improve patient outcomes.
Simultaneous hemodynamics were recorded using two HemoSphere monitors with the HPI software and either intra-arterial Acumen (hereinafter invasive) or ClearSight™ (hereinafter non-invasive) pressure inputs. Data collected from the non-invasive system was compared to corresponding invasive, intra-arterial data using Bland-Altman analysis, Spearman correlation, concordance analysis and relative performance with respect to prediction of hypotensive events using ROC analysis and HPI alerts agreement analysis.
6,862 paired data points were available from 36 patients. Bland-Altman comparisons demonstrated a bias of -8.4 (± 23) with limits of agreement from - 53 to 36. The correlation between HPI values was strong with an r value of 0.76 (95%CI:0.75-0.77). Concordance was also strong at 74% (10% exclusion zone). Using ROC analysis, the AUC for prediction of hypotension was similar and at 5 min was 0.883 [0.786,0.953] for the invasive pressure and 0.860 [0.770,0.939] for the non-invasive pressure inputs. At the same time points, the agreement between HPI alerts was high with an accuracy of 86.3%.
HPI values and predictive performance were comparable when derived from either invasive or non-invasive pressure inputs.
The study was approved by the UC Davis Institutional Review Board (IRB #1791102-1) and registered on ClinicalTrials.gov (NCT05025176) before the enrollment of the first patient.
使用Acumen™动脉压力传感器得出的低血压预测指数(HPI)可降低术中低血压的发生率,并可能减少围手术期并发症。HPI也可从ClearSight™连续无创血压监测仪获取。从这两种压力输入获得的HPI值的并行比较有限,更多的比较可能会增加临床医生对无创血流动力学监测的信心,扩大其应用范围并改善患者预后。
使用两台配备HPI软件的HemoSphere监测仪,通过有创动脉Acumen(以下简称有创)或ClearSight™(以下简称无创)压力输入同步记录血流动力学数据。使用Bland-Altman分析、Spearman相关性分析、一致性分析以及使用ROC分析和HPI警报一致性分析预测低血压事件的相对性能,将从无创系统收集的数据与相应的有创动脉数据进行比较。
从36例患者中获得了6862对数据点。Bland-Altman比较显示偏差为-8.4(±23),一致性界限为-53至36。HPI值之间的相关性很强,r值为0.76(95%CI:0.75-0.77)。一致性也很强,为74%(排除区为10%)。使用ROC分析,预测低血压的AUC相似,在5分钟时,有创压力的AUC为0.883[0.786,0.953],无创压力输入的AUC为0.860[0.770,0.939]。在相同时间点,HPI警报之间的一致性很高,准确率为86.3%。
从有创或无创压力输入得出的HPI值和预测性能具有可比性。
该研究经加州大学戴维斯分校机构审查委员会批准(IRB#1791102-1),并在第一名患者入组前在ClinicalTrials.gov上注册(NCT05025176)。