An observational study in Hypotension During Surgery, sponsored by Samsung Medical Center. Recruiting at 1 site in South Korea. Open to participants aged 19 Years and older. Per ClinicalTrials.gov, last updated 2025-05-15.
Sponsored by Samsung Medical Center · Observational
The goal of this prospective observational study is to externally validate the prediction algorithm using non-invasive monitoring device for intraoperative hypotension. The main question it aims to answer is: Does the prediction algorithm predict intraoperative hypotension effectively?
The hypotension that occurs during surgery is associated with the poor prognosis of patients after surgery. Previous studies have reported that even a short period of time of hypotension increases the risk of postoperative complications such as kidney injury. If anesthesiologists can predict intraoperative hypotension in advance, they can prevent or minimize the damage.
Recently, there are many reports on medical artificial intelligence models that predict the intraoperative hypotension. Among them, the Hypotension Prediction Index (HPI) model has already been commercialized and used in clinical practice. However, HPI has limitations in that it is necessary to perform invasive techniques (arterial cannulation) or to use dedicated equipment at high cost. However, since many of the general anesthesia are performed without invasive monitoring devices, the use of HPI medical devices is subject to considerable restrictions.
The investigators have reported the prediction algorithm for intraoperative hypotension using five non-invasive monitoring devices commonly used in general anesthesia: 1) blood pressure (NBP, number), 2) electrocardiogram (ECG, waveform), 3) end-oxygen saturation waveform (PPG, waveform), 4) end-stage carbon dioxide waveform (ETCO2, waveform), and 5) an anesthesia depth (BIS, number) By conducting a retrospective external validation process using public clinical data from other institutions (tertiary hospital in Korea), the final model was able to have good predictability with an Area Under the Receiver-Operating Characteristic Curve (AUROC) value of 0.917.
However, investigators did not externally validate that algorithm through a prospective designed study. This study intends to externally validate the "hypertension prediction model during surgery using non-invasive monitoring device", which has already reported It is expected that the usefulness and limitations of the prediction model can be evaluated again, and the model can be advanced based on the results.
Samsung Medical Center is the lead sponsor of 1,005 studies on the registry; 148 are open to participants now.
Of its 7 completed or terminated interventional studies of FDA-regulated products, 1 (14%) have results posted.
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The patients who undergoing general anesthesia with five non-invasive monitoring device (non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and Bispectral Index)
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Exclusion Criteria:
All participants are enrolled in single group.
Diagnostic Test: Prediction algorithm for intraoperative hypotension
All participants will receive five non-invasive monitoring during their surgery. Data from these monitoring device will be put into the prediction algorithm.
Value of the Area Under the Receiver-Operating Characteristic curve analysis
The area under the receiver operating characteristic curve is a measurement of how well a prediction model can predict intraoperative hypotension. It is used to assess the performance of algorithm.
Time frame: 5 minutes before the occurrence of hypotension during general anesthesia
Plan to share: No
Started Apr 2025 (actual). Primary completion is estimated for Dec 2025, 8 months after the start.
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