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Use of the Hypotension Prediction Index During Cardiac Surgery
Brian Shin1, Steven A Maler2, Keerthi Reddy3
1University of California, Davis, Department of Anesthesiology and Pain Medicine, Sacramento, CA.
Insights
The hypotension prediction index (HPI) accurately predicted hypotensive events during cardiac surgery with cardiopulmonary bypass. This novel tool demonstrated high sensitivity and specificity in forecasting hypotension, aiding surgical teams.
Area of Science:
- Cardiovascular Anesthesiology
- Intraoperative Hemodynamic Monitoring
- Surgical Risk Assessment
Background:
- The hypotension prediction index (HPI) is a novel algorithm analyzing arterial pressure waveform characteristics.
- Previous studies confirmed HPI's accuracy in predicting hypotension during non-cardiac surgeries.
- The utility of HPI in cardiac surgeries involving cardiopulmonary bypass (CPB) remained unevaluated.
Purpose of the Study:
- To assess the predictive performance of the HPI in patients undergoing cardiac surgery with CPB.
- To determine the sensitivity and specificity of HPI in forecasting hypotensive events during these procedures.
Main Methods:
- A prospective cohort feasibility study was conducted at a single university medical center.
- Adult patients undergoing elective cardiac surgery requiring CPB were enrolled sequentially.
- The HPI monitor was used, with anesthesiologists and surgeons blinded to the real-time output.
Main Results:
- HPI demonstrated a high area under the curve (AUC) for predicting hypotension: 0.90 at 5 minutes, 0.83 at 10 minutes, and 0.83 at 15 minutes prior to the event.
- Sensitivity and specificity for HPI prediction were also high, reaching 84% at a 5-minute lead time.
- These results indicate HPI's robust ability to anticipate hypotensive episodes.
Conclusions:
- The hypotension prediction index (HPI) effectively predicted hypotensive episodes in cardiac surgery patients.
- HPI exhibited high sensitivity and specificity, proving its value as a predictive tool in this complex surgical setting.
- The findings support the potential integration of HPI into routine hemodynamic monitoring during cardiac surgeries.
Objective:
The hypotension prediction index (HPI) is a novel parameter developed by Edwards Lifesciences (Irvine, CA) that is obtained through an algorithm based on arterial pressure waveform characteristics. Past studies have demonstrated its accuracy in predicting hypotensive events in noncardiac surgeries. The authors aimed to evaluate the use of the HPI in cardiac surgeries requiring cardiopulmonary bypass (CPB).
Design:
Prospective cohort feasibility study.
Setting:
Single university medical center.
Participants:
Sequential adult patients undergoing elective cardiac surgeries requiring CPB between October 1, 2018, and December 31, 2018.
Interventions:
HPI monitor was connected to the patient's arterial pressure transducer. Anesthesiologists and surgeons were blinded to the monitor output.
Measurements And Main Results:
HPI values and hypotensive events were recorded before and after CPB. The primary outcomes were the area under the curve (AUC) of the receiver operating characteristic curve, sensitivity, and specificity of HPI predicting hypotension. The AUC, sensitivity, and specificity for HPI lead time to hypotension five minutes before the event were 0.90 (95% confidence interval [CI]: 0.853-0.949), 84% (95% CI: 77.7-90.5), and 84% (95% CI: 70.9-96.8), respectively. Ten minutes before the event AUC, sensitivity, and specificity for HPI lead time to hypotension were 0.83 (95% CI: 0.750-0.905), 79% (95% CI: 69.8-88.1), and 74% (95% CI: 58.8-89.6), respectively. Fifteen minutes before the hypotensive event AUC, sensitivity, and specificity for HPI lead time to hypotension were 0.83 (95% CI: 0.746-0.911), 79% (95% CI: 68.4-89.0), and 74% (95% CI: 58.8-89.6), respectively.
Conclusion:
HPI predicted hypotensive episodes during cardiac surgeries with a high degree of sensitivity and specificity.
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