Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis - Erfan Shirmohamadi; Reza Hosseini Dolama; Narjes Mohammadzadeh; Navid Ebrahimi; Negar Ghasemloo (BMC Anesthesiology)
Abstract Background Intraoperative hypotension (IOH), defined as a mean arterial pressure (MAP) below 65 mmHg, is a common complication during surgery and is associated with significant postoperative morbidity, including acute kidney injury, myocardial injury, stroke, and increased mortality. Despite the availability of traditional monitoring techniques, predicting and preventing IOH remains a challenge. The Hypotension Prediction Index (HPI), a machine-learning algorithm developed by Edwards Lifesciences, aims to predict IOH by analyzing real-time arterial waveform data, offering an opportunity for proactive management. Objective This systematic review and meta-analysis evaluate the efficacy of the HPI in predicting and preventing IOH in cardiac and non-cardiac surgeries compared to standard blood pressure monitoring techniques. Methods A comprehensive search was conducted in PubMed, Scopus, Embase, and Web of Science databases for studies published from January 2019 to May 2024. Studies were included if they utilized machine learning algorithms, including HPI, to predict or detect IOH in adult surgical patients. Sensitivity, specificity, area under the curve (AUC), and time-weighted average (TWA) of hypotension were the primary outcomes. Subgroup analyses were performed to evaluate differences between cardiac and non-cardiac surgeries. Meta-analytic methods were applied using random-effects models to account for study variability. Results A total of 22 studies were included, encompassing both cardiac and non-cardiac procedures. The HPI demonstrated an overall sensitivity of 83% and specificity of 83% in predicting IOH. The pooled AUC for all surgeries was 0.90. However, subgroup analysis revealed variability in HPI performance between cardiac and non-cardiac surgeries, with lower diagnostic odds ratios (DOR) in cardiac settings. HPI combined with invasive arterial blood pressure monitoring reduced the TWA of hypotension more effectively than either invasive or non-invasive methods alone. The comparison of HPI and MAP for diagnostic accuracy showed minimal differences across all time frames, with SMD values close to zero. Conclusion Our study shows that the HPI has high sensitivity and specificity in predicting intraoperative hypotension, but its clinical advantage over standard MAP-based monitoring is uncertain. While HPI reduces hypotension duration, this may not improve cardiovascular or renal outcomes. Further independent trials are needed to validate its effectiveness before widespread adoption, and it should be considered alongside simpler interventions like staff education and MAP targeting in the meantime.