Intraoperative hypotension (IOH) is a significant complication that affects surgical patients, potentially leading to adverse outcomes postoperatively. Standard practices involve relying on monitoring devices with low alarm thresholds for blood pressure, which may result in delayed interventions. The Hypotension Prediction Index (HPI) offers a predictive approach by analyzing arterial waveform signals and using complex algorithms to detect potential hypotensive episodes early. Recent observational studies have suggested that HPI's accuracy in predicting hypotension aligns closely with raising the physiological monitor alarm threshold to 73 mmHg. To further investigate this, this study will compare the effects of setting a traditional monitor alarm threshold at 73 mmHg with using HPI to prevent IOH.
In this study, patients will be randomly assigned to two groups. In the HPI group, interventions will be initiated when the HPI value exceeds 85. These interventions will follow a protocol that includes fluid administration, norepinephrine, and dobutamine to prevent hypotension. The control group will have their alarm threshold set at 73 mmHg. For these patients, interventions will be based on stroke volume variation (SVV) and clinical judgment, utilizing fluid and norepinephrine as needed. HPI is an attractive AI-based tool for medical care, but its high cost due to advanced technology raises questions. If its accuracy proves to be similar to simply raising the alarm threshold to 73 mmHg, it may not lead to meaningful changes in clinical practice. The study aims to compare the efficacy of these two methods in reducing the incidence of IOH.