Work

Hypotension prediction index: comparison between invasive and non-invasive pressure inputs

Year: 2025

Type: article

Abstract: BACKGROUND: 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. METHODS: (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. RESULTS: 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%. CONCLUSION: HPI values and predictive performance were comparable when derived from either invasive or non-invasive pressure inputs. TRIAL REGISTRATION: 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.

Source: BMC Anesthesiology

DOI: 10.1186/s12871-025-03086-y

Authors: Kamron Sarhadi, Justin Hamman, Jorge Avila, Zhongping Jian, Neal W. Fleming

Institutions: University of California, San Francisco, University of California Davis Medical Center, University of California, Davis, Sutter Medical Center, Edwards Lifesciences (United States)

Language: English

Topic: Hemodynamic Monitoring and Therapy

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,190