Impact of hypotension prediction index-guided management on intraoperative hypotension and postoperative outcomes in abdominal surgery: A meta-analysis of randomized controlled trials.

BACKGROUND

The Hypotension Prediction Index (HPI) is a machine-learning algorithm designed to predict hypotension. by maintaining mean arterial pressure (MAP) above 65 mmHg. This meta-analysis evaluated whether HPI-guided management improves postoperative outcomes and included post hoc analyses of intraoperative hypotension (IOH) metrics in adults undergoing major abdominal surgery.

METHODS

A comprehensive search of PubMed, EMBASE, and Cochrane databases identified randomized controlled trials comparing HPI-guided management with standard care. Primary outcomes were postoperative complications, acute kidney injury (AKI), perioperative mortality, and hospital length of stay (LOS). Post hoc analyses assessed IOH metrics, including time-weighted average (TWA) of MAP < 65 mmHg, area under the threshold (AUT), total time with MAP < 65 mmHg, and intraoperative fluid use. Meta-analyses were conducted using random-effects models to calculate pooled standardized mean differences (SMDs), odds ratios (ORs), and mean differences (MDs).

RESULTS

Eight trials involving 1534 patients were included. No significant differences were observed for AKI (OR: 0.85; 95% CI: 0.64-1.13), postoperative complications (OR: 1.10; 95% CI: 0.83-1.46), mortality (OR: 0.96; 95% CI: 0.32-2.83), LOS (SMD: -0.15; 95% CI: -0.73 to 0.42), or fluid use (SMD: -0.06; 95% CI: -0.35 to 0.24). HPI reduced TWA MAP < 65 mmHg (SMD: -0.25; MD: -20.5 min), AUT (SMD: -0.83), and total time with MAP < 65 mmHg (SMD: -0.74).

CONCLUSIONS

HPI-guided management did not significantly improve patient-centered outcomes. Post hoc analyses indicated a reduction in IOH metrics, but the clinical relevance of these findings remains uncertain given the lack of blinding and high risk of bias.

REGISTRATION: PROSPERO: CRD42023490654.