Prospective Cohort Study of Pheochromocytoma/Paraganglioma
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-99
SponsorPeking Union Medical College Hospital
About this trial
The study will enroll patients scheduled for PPGL removal surgery at Peking Union Medical College Hospital. Before surgery, researchers will use a 6-variable model to predict the patient's risk of experiencing severe blood pressure swings during the operation. During surgery, a real-time early warning tool will be tested for its ability to accurately predict blood pressure changes 60 seconds in advance. The study will also explore the value of continuous glucose monitoring (CGM) in understanding blood pressure fluctuations and evaluate the performance of an artificial intelligence (AI) agent for preoperative anesthesia assessment, comparing its accuracy, consistency, and efficiency against that of human anesthesiologists.
Participation involves no changes to the patient's standard surgical or medical care. It includes collecting clinical data, wearing a CGM sensor from the day before to the day after surgery, and having the preoperative assessment performed by both the AI agent and anesthesiologists.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Age ≥ 18 years.
Diagnosed with pheochromocytoma/paraganglioma by imaging and laboratory tests and scheduled for elective resection.
Planned intraoperative continuous invasive arterial pressure monitoring.
Willing and able to provide written informed consent.
Disqualifiers
Intraoperative hemodynamic data missing ≥20%.
Postoperative histopathology excludes PPGL diagnosis.
Cardiac paraganglioma or metastatic PPGL.
Severe cardiac disease (e.g., severe valvular disease, severe heart failure) that could independently cause intraoperative HDI.
Trial population
Patients diagnosed with pheochromocytoma or paraganglioma scheduled for elective surgical resection at Peking Union Medical College Hospital.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
200 Participants
are grouped into 1 trial groupGroup A: PPGL Resection Cohort
Trial outcomes
Primary outcomes
1
Predictive Model Discrimination (AUROC)
Discriminative ability of the preoperative 6-variable model for predicting severe intraoperative hemodynamic instability (HDI) subtype, assessed by the Area Under the Receiver Operating Characteristic Curve (AUROC).
Time frame
From preoperative assessment up to end of surgerySecondary outcomes
1
Real-time Warning Tool Accuracy - Heart Rate (MAPE)
Accuracy of the intraoperative early warning tool for heart rate, measured by the Mean Absolute Percentage Error (MAPE) between its predicted and actual monitored heart rate values. Unit of Measure: %
Time frame
Intraoperative period2
Real-time Warning Tool Accuracy - Systolic Blood Pressure (MAPE)
Accuracy of the intraoperative early warning tool for blood pressure parameters, measured by the Mean Absolute Percentage Error (MAPE) between its predicted and actual monitored values for systolic blood pressure (SBP). Unit of Measure: %
Time frame
Intraoperative period3
Real-time Warning Tool Accuracy - Diastolic Blood Pressure (MAPE)
Accuracy of the intraoperative early warning tool for blood pressure parameters, measured by the Mean Absolute Percentage Error (MAPE) between its predicted and actual monitored values for diastolic blood pressure (DBP). Unit of Measure: %
Time frame
Intraoperative period4
Predictive Model Calibration
Calibration of the preoperative 6-variable predictive model, assessed by the Hosmer-Lemeshow goodness-of-fit test (p-value), calibration curve, and Brier score. Unit of Measure: p-value (dimensionless), Brier score (dimensionless)
Time frame
From preoperative assessment up to end of surgeryLocations
Sponsors and contacts
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Source ClinicalTrials.gov
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