Intraoperative HypotensionRL-PRAIS PoCNCT07123675
AI-Assisted Blood Pressure Control During Anesthesia
A study testing Device: AI Clinical Decision Support System in people with Intraoperative Hypotension and Hemodynamic Instability, run by Beijing Tsinghua Chang Gung Hospital at 2 sites in China.
Trial summary
This proof-of-concept randomized controlled trial evaluates a reinforcement learning (RL)-based clinical decision support system for intraoperative hemodynamic management during non-cardiac surgery. Read more about this study
- Who is it for?
- Ages 18 to 85 years
- Conditions the study is for
- Intraoperative Hypotension, Hemodynamic Instability
- What is being tested?
- Device: AI Clinical Decision Support System
- Type of treatment
- Medical device, Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 40 participants
- Where
- 2 sitesChina
- Study dates
- 1 Jun 2026to 15 Dec 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 85 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age 18 to 85 years
- Scheduled for elective non-cardiac surgery
- Receiving intravenous-inhalation combined general anesthesia with tracheal intubation
- ASA physical status I to IV
- Anesthesia maintenance plan includes propofol for continuous sedation, remifentanil for continuous analgesia, and sevoflurane or desflurane for inhalation anesthesia
- Continuous invasive arterial blood pressure monitoring during surgery
- Continuous monitoring of heart rate and Bispectral Index (BIS) during surgery
- Expected surgical duration of at least 2 hours
Who cannot join
- Emergency surgery
- Continuous infusion of remifentanil or propofol for less than 30 minutes during surgery
- Receiving continuous intravenous sedatives other than propofol during the maintenance phase
- Receiving continuous intravenous analgesics other than remifentanil during the maintenance phase
- Inhaled anesthetic maintenance concentration not equal to 0.5 MAC
- Known allergy to propofol or remifentanil
Show all 9Show fewer
- Severe obesity (BMI >= 35 kg/m2)
- Severe cardiovascular disease (NYHA class IV heart failure, unstable angina, or recent myocardial infarction within 30 days)
- Participation in another interventional clinical trial within 30 days
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China2 sites
Peking University People's Hospital
Beijing, Beijing Municipality, 100044
Yi Feng, MD, +8618975802249, 1810301235@pku.edu.cn
Beijing Tsinghua Changgung Hospital
Beijing, Beijing Municipality, 102218
Zheng Zhang, MD, 18801238359, 18756235568@163.com
About this study
Official title: A Dual-Center, Randomized, Controlled, Proof-of-Concept Trial to Evaluate an AI-Based Decision Support System for Intraoperative Blood Pressure Management
This proof-of-concept randomized controlled trial evaluates a reinforcement learning (RL)-based clinical decision support system for intraoperative hemodynamic management during non-cardiac surgery.
Background: Intraoperative hypotension is common during general anesthesia and is associated with adverse outcomes including acute kidney injury, myocardial injury, and increased mortality. Current hemodynamic management relies on the individual anesthesiologist's clinical judgment, which can vary in consistency and timeliness. An RL-based system that learns optimal vasoactive agent dosing strategies from clinical data may help standardize and improve real-time hemodynamic decision-making.
Read more
Purpose: The primary objective is to evaluate whether the RL-based decision support system can learn intraoperative hemodynamic management decisions comparable to those of experienced anesthesiologists, as measured by the mean absolute error (MAE) between RL-recommended and clinician-executed vasoactive agent doses. The secondary objective is to assess whether RL-guided management improves clinical hemodynamic outcomes, including the time-weighted average of hypotension and the percentage of time with mean arterial pressure within the target range.
Participants: Adult patients (aged 18 to 85 years, ASA I-IV) scheduled for elective non-cardiac surgery under general anesthesia with continuous invasive arterial blood pressure monitoring.
Procedures: Participants will be randomly assigned (1:1) to one of two groups. In the RL-guided group, the anesthesiologist will receive real-time vasoactive agent dosing recommendations from the decision support system displayed on a bedside screen; the anesthesiologist retains full clinical autonomy over all final decisions. In the standard care group, the anesthesiologist will manage hemodynamics according to institutional standard practice without input from the system. The patient and the outcomes assessor will be masked to group assignment. Data collection covers the intraoperative period and 30-day postoperative follow-up.
Read the detailed description
Rationale: Intraoperative hypotension, commonly defined as mean arterial pressure (MAP) below 65 mmHg, occurs in up to 60% of patients undergoing general anesthesia and is independently associated with acute kidney injury, myocardial injury, stroke, and 30-day mortality. Current approaches to hemodynamic management are reactive and rely on individual clinician judgment. Machine learning-based prediction systems (e.g., the Hypotension Prediction Index) have shown potential in reducing hypotension burden, but do not provide actionable dosing recommendations. Reinforcement learning (RL) offers a fundamentally different approach: learning optimal sequential decision-making policies from clinical data. The RL-PRAIS system (Reinforcement Learning-based Perioperative Real-time Anesthesia Intelligent System) consists of a Transformer-based patient state encoder and a model-based RL framework (patient model plus policy model) that generates real-time vasoactive agent dosing recommendations.
Hypothesis: The RL-PRAIS system can learn intraoperative hemodynamic management decisions that approximate those of experienced anesthesiologists and, when deployed as a decision support tool, can reduce the burden of intraoperative hypotension compared to standard care.
Study Design: This is a prospective, dual-center, parallel-group, randomized, controlled, proof-of-concept superiority trial. The study follows a four-phase stepwise validation framework: (1) model development using retrospective electronic health records (n = 7,216), (2) retrospective validation (n = 75), (3) prospective deployment study (n = 40), and (4) proof-of-concept randomized controlled trial (n = 40, 20 per arm). This registration covers Phase 4 (the RCT).
Objectives: Primary Objective: To evaluate the concordance between RL-recommended vasoactive agent dosing and attending anesthesiologist-executed dosing, quantified by mean absolute error (MAE) in norepinephrine-equivalent units. Secondary Objectives: To compare intraoperative hemodynamic outcomes between the RL-guided and standard care groups, including time-weighted average of MAP below 65 mmHg (TWA-MAP < 65), percentage of time with MAP in the target range of 65-100 mmHg (MAP TIR), incidence of hypotensive events, cumulative vasoactive agent consumption, MAP variability, and clinician acceptance rate of RL recommendations. Exploratory Objectives: To collect pilot data on 30-day major adverse cardiac or cerebrovascular events (MACCE), acute kidney injury, perioperative myocardial injury, PACU length of stay, hospital length of stay, and 30-day all-cause mortality.
Interventions: Intervention Group (RL-Guided): The RL-PRAIS system provides real-time dosing recommendations for vasoactive agents (norepinephrine, phenylephrine, and ephedrine) based on continuous invasive arterial blood pressure monitoring and patient state features. Recommendations are displayed on a bedside screen at 1-minute intervals. The attending anesthesiologist retains full clinical autonomy and is responsible for all final dosing decisions. Control Group (Standard Care): The anesthesiologist manages intraoperative hemodynamics according to institutional standard practice and clinical judgment, with continuous invasive arterial blood pressure monitoring but without input from the RL-PRAIS system.
Study Population: Adult patients aged 18 to 85 years, ASA physical status I-IV, scheduled for elective non-cardiac surgery under general anesthesia with continuous invasive arterial blood pressure monitoring. Surgery is expected to last at least 2 hours. Key exclusion criteria include emergency surgery, severe obesity (BMI >= 35), and allergy to study-related agents.
Statistical Considerations: The sample size of 40 participants (20 per arm) is designed for a proof-of-concept evaluation, consistent with the benchmarking study (Wang et al., Nature Medicine 2023, RL-DITR, n = 16 in feasibility RCT). The primary analysis will compare MAE between groups using a two-sided paired or independent t-test (or non-parametric equivalent). Secondary hemodynamic outcomes will be compared using the Wilcoxon rank-sum test. Exploratory outcomes will be reported descriptively without formal hypothesis testing.
- Being tested
- Device: AI Clinical Decision Support System, Procedure: Standard of Care Anesthesia
- Keywords
- Reinforcement Learning, Clinical Decision Support System, Depth of Anesthesia, Artificial Intelligence, Vasoactive Agent Dosing
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Device: AI Clinical Decision Support SystemDevice
An AI-based software system that provides real-time, on-screen recommendations to the anesthesiologist regarding drug administration and adjustments to maintain optimal patient physiological parameter
Procedure: Standard of Care AnesthesiaProcedure or surgery
Standard anesthesia management according to institutional guidelines. The attending anesthesiologist makes all clinical decisions based on their expertise and judgment without input from the investigational AI system.
| Study group | Role | What they receive |
|---|---|---|
| Experimental: RL-Guided Hemodynamic Management | Experimental | Participants in this arm will have their intraoperative hemodynamic management guided by the RL-PRAIS clinical decision support system. The system provides real-time dosing recommendations for vasoactive agents (norepinephrine, phenylephrine, and ephedrine) based on continuous invasive arterial blood pressure monitoring and patient state features. Recommendations are displayed on a bedside screen at 1-minute decision epochs. The attending anesthesiologist retains full clinical autonomy and is responsible for all final dosing decisions. Anesthetic management (propofol, remifentanil, sevoflurane/desflurane) follows institutional standard protocols in both arms. Receives: Device: Device: AI Clinical Decision Support System |
| Active Comparator: Standard Anesthesia Care | Active comparator | Participants in this arm will receive standard-of-care general anesthesia management. The anesthesiologist will make all clinical decisions based on their professional judgment and standard institutional practices, without the aid of the investigational AI system. Receives: Procedure: Procedure: Standard of Care Anesthesia |
What is being measured
The primary outcome is the main question the study is designed to answer.
Mean Absolute Error (MAE) of RL-Recommended Vasoactive Agent Dosing Versus Anesthesiologist-Executed Dosing
The primary outcome is the mean absolute error (MAE) between vasoactive agent doses recommended by the RL-PRAIS system and doses actually administered by the attending anesthesiologist. Vasoactive agents (norepinephrine, phenylephrine, ephedrine) are converted to norepinephrine-equivalent units (NEq, mcg/kg/min). MAE is computed at each 1-minute decision epoch during hemodynamic optimization and averaged across all epochs per patient. Concordance rate is also reported as the proportion of epochs where the RL-recommended dose falls within a clinically acceptable range of the executed dose.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Secondary outcomes (7)
Time-Weighted Average of Mean Arterial Pressure Below 65 mmHg (TWA-MAP < 65 mmHg)
The time-weighted average of hypotension during the hemodynamic optimization period, calculated as the area under the MAP threshold of 65 mmHg (depth in mmHg multiplied by duration in minutes) divided by the total hemodynamic optimization time (minutes). This composite metric integrates both the severity and duration of intraoperative hypotension. Continuous invasive arterial blood pressure data sampled at 5-second intervals are used for calculation via the trapezoidal rule. A lower value indicates better hemodynamic management.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Percentage of Time with MAP in Target Range (MAP TIR 65-100 mmHg)
The proportion of total hemodynamic optimization time during which mean arterial pressure remains within the target range of 65 to 100 mmHg, expressed as a percentage. A higher percentage indicates more stable hemodynamic control.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Incidence of Intraoperative Hypotensive Events
The number of discrete hypotensive events per patient, defined as episodes where MAP falls below 65 mmHg for at least 1 minute continuously. An event is considered terminated when MAP returns to 65 mmHg or above for at least 1 minute.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
TWA-MAP Below 60 mmHg and Below 55 mmHg
Time-weighted average of MAP below 60 mmHg and below 55 mmHg, calculated using the same method as TWA-MAP < 65 mmHg but with lower thresholds. These metrics capture moderate and severe intraoperative hypotension, respectively.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Cumulative Vasoactive Agent Consumption
Total cumulative dose of all vasoactive agents administered during the hemodynamic optimization period, converted to norepinephrine-equivalent units (NEq, mcg/kg). This metric serves as a safety indicator to assess whether RL-guided management leads to excessive or reduced pharmacological intervention compared to standard care.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Mean Arterial Pressure Variability
Coefficient of variation (CV) of mean arterial pressure during the hemodynamic optimization period, calculated as the standard deviation of MAP divided by the mean MAP, expressed as a percentage. A lower CV indicates more stable hemodynamic control.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Clinician Acceptance Rate of RL Recommendations (Experimental Arm Only)
The proportion of RL-PRAIS dosing recommendations that are accepted and executed by the attending anesthesiologist without modification, expressed as a percentage of total recommendation epochs. Partial acceptance (dose modification in the recommended direction) is recorded separately.
Measured: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Aug 2025
- Study start1 Jun 2026 (estimated)
- Primary completion1 Jun 2027 (estimated)
- Study completion15 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Intraoperative HypotensionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Tsinghua Chang Gung Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Peking University People's Hospital
- Responsible party
- Principal investigator, Zhifeng Gao, Beijing Tsinghua Chang Gung Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07123675
- Sponsor's protocol ID
- 24444-4-03
- Acronym
- RL-PRAIS PoC
- Status last verified
- Apr 2026
- First submitted
- 8 Aug 2025
- Last updated
- 6 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Dual-Center, Randomized, Controlled, Proof-of-Concept Trial to Evaluate an AI-Based Decision Support System for Intraoperative Blood Pressure Management
- ClinicalTrials.gov ID
- NCT07123675
- Acronym / sponsor ID
- RL-PRAIS PoC / 24444-4-03
- Keywords
- Reinforcement Learning, Clinical Decision Support System, Depth of Anesthesia, Artificial Intelligence, Vasoactive Agent Dosing
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- Beijing Tsinghua Chang Gung HospitalUniversity, hospital or other
- Collaborators
- Peking University People's Hospital
- Study start
- 1 Jun 2026 (estimated)
- Primary completion
- 1 Jun 2027 (estimated)
- Study completion
- 15 Dec 2027 (estimated)
- First posted
- 14 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This proof-of-concept randomized controlled trial evaluates a reinforcement learning (RL)-based clinical decision support system for intraoperative hemodynamic management during non-cardiac surgery.
Background: Intraoperative hypotension is common during general anesthesia and is associated with adverse outcomes including acute kidney injury, myocardial injury, and increased mortality. Current hemodynamic management relies on the individual anesthesiologist's clinical judgment, which can vary in consistency and timeliness. An RL-based system that learns optimal vasoactive agent dosing strategies from clinical data may help standardize and improve real-time hemodynamic decision-making.
Purpose: The primary objective is to evaluate whether the RL-based decision support system can learn intraoperative hemodynamic management decisions comparable to those of experienced anesthesiologists, as measured by the mean absolute error (MAE) between RL-recommended and clinician-executed vasoactive agent doses. The secondary objective is to assess whether RL-guided management improves clinical hemodynamic outcomes, including the time-weighted average of hypotension and the percentage of time with mean arterial pressure within the target range.
Participants: Adult patients (aged 18 to 85 years, ASA I-IV) scheduled for elective non-cardiac surgery under general anesthesia with continuous invasive arterial blood pressure monitoring.
Procedures: Participants will be randomly assigned (1:1) to one of two groups. In the RL-guided group, the anesthesiologist will receive real-time vasoactive agent dosing recommendations from the decision support system displayed on a bedside screen; the anesthesiologist retains full clinical autonomy over all final decisions. In the standard care group, the anesthesiologist will manage hemodynamics according to institutional standard practice without input from the system. The patient and the outcomes assessor will be masked to group assignment. Data collection covers the intraoperative period and 30-day postoperative follow-up.
Detailed description
Rationale: Intraoperative hypotension, commonly defined as mean arterial pressure (MAP) below 65 mmHg, occurs in up to 60% of patients undergoing general anesthesia and is independently associated with acute kidney injury, myocardial injury, stroke, and 30-day mortality. Current approaches to hemodynamic management are reactive and rely on individual clinician judgment. Machine learning-based prediction systems (e.g., the Hypotension Prediction Index) have shown potential in reducing hypotension burden, but do not provide actionable dosing recommendations. Reinforcement learning (RL) offers a fundamentally different approach: learning optimal sequential decision-making policies from clinical data. The RL-PRAIS system (Reinforcement Learning-based Perioperative Real-time Anesthesia Intelligent System) consists of a Transformer-based patient state encoder and a model-based RL framework (patient model plus policy model) that generates real-time vasoactive agent dosing recommendations.
Hypothesis: The RL-PRAIS system can learn intraoperative hemodynamic management decisions that approximate those of experienced anesthesiologists and, when deployed as a decision support tool, can reduce the burden of intraoperative hypotension compared to standard care.
Study Design: This is a prospective, dual-center, parallel-group, randomized, controlled, proof-of-concept superiority trial. The study follows a four-phase stepwise validation framework: (1) model development using retrospective electronic health records (n = 7,216), (2) retrospective validation (n = 75), (3) prospective deployment study (n = 40), and (4) proof-of-concept randomized controlled trial (n = 40, 20 per arm). This registration covers Phase 4 (the RCT).
Objectives: Primary Objective: To evaluate the concordance between RL-recommended vasoactive agent dosing and attending anesthesiologist-executed dosing, quantified by mean absolute error (MAE) in norepinephrine-equivalent units. Secondary Objectives: To compare intraoperative hemodynamic outcomes between the RL-guided and standard care groups, including time-weighted average of MAP below 65 mmHg (TWA-MAP < 65), percentage of time with MAP in the target range of 65-100 mmHg (MAP TIR), incidence of hypotensive events, cumulative vasoactive agent consumption, MAP variability, and clinician acceptance rate of RL recommendations. Exploratory Objectives: To collect pilot data on 30-day major adverse cardiac or cerebrovascular events (MACCE), acute kidney injury, perioperative myocardial injury, PACU length of stay, hospital length of stay, and 30-day all-cause mortality.
Interventions: Intervention Group (RL-Guided): The RL-PRAIS system provides real-time dosing recommendations for vasoactive agents (norepinephrine, phenylephrine, and ephedrine) based on continuous invasive arterial blood pressure monitoring and patient state features. Recommendations are displayed on a bedside screen at 1-minute intervals. The attending anesthesiologist retains full clinical autonomy and is responsible for all final dosing decisions. Control Group (Standard Care): The anesthesiologist manages intraoperative hemodynamics according to institutional standard practice and clinical judgment, with continuous invasive arterial blood pressure monitoring but without input from the RL-PRAIS system.
Study Population: Adult patients aged 18 to 85 years, ASA physical status I-IV, scheduled for elective non-cardiac surgery under general anesthesia with continuous invasive arterial blood pressure monitoring. Surgery is expected to last at least 2 hours. Key exclusion criteria include emergency surgery, severe obesity (BMI >= 35), and allergy to study-related agents.
Statistical Considerations: The sample size of 40 participants (20 per arm) is designed for a proof-of-concept evaluation, consistent with the benchmarking study (Wang et al., Nature Medicine 2023, RL-DITR, n = 16 in feasibility RCT). The primary analysis will compare MAE between groups using a two-sided paired or independent t-test (or non-parametric equivalent). Secondary hemodynamic outcomes will be compared using the Wilcoxon rank-sum test. Exploratory outcomes will be reported descriptively without formal hypothesis testing.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Experimental: RL-Guided Hemodynamic Management | Experimental | Device: Device: AI Clinical Decision Support SystemParticipants in this arm will have their intraoperative hemodynamic management guided by the RL-PRAIS clinical decision support system. The system provides real-time dosing recommendations for vasoactive agents (norepinephrine, phenylephrine, and ephedrine) based on continuous invasive arterial blood pressure monitoring and patient state features. Recommendations are displayed on a bedside screen at 1-minute decision epochs. The attending anesthesiologist retains full clinical autonomy and is responsible for all final dosing decisions. Anesthetic management (propofol, remifentanil, sevoflurane/desflurane) follows institutional standard protocols in both arms. |
| Active Comparator: Standard Anesthesia Care | Active comparator | Procedure: Procedure: Standard of Care AnesthesiaParticipants in this arm will receive standard-of-care general anesthesia management. The anesthesiologist will make all clinical decisions based on their professional judgment and standard institutional practices, without the aid of the investigational AI system. |
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (8 listed)
- Age 18 to 85 years
- Scheduled for elective non-cardiac surgery
- Receiving intravenous-inhalation combined general anesthesia with tracheal intubation
- ASA physical status I to IV
- Anesthesia maintenance plan includes propofol for continuous sedation, remifentanil for continuous analgesia, and sevoflurane or desflurane for inhalation anesthesia
Key exclusion criteria (9 listed)
- Emergency surgery
- Continuous infusion of remifentanil or propofol for less than 30 minutes during surgery
- Receiving continuous intravenous sedatives other than propofol during the maintenance phase
- Receiving continuous intravenous analgesics other than remifentanil during the maintenance phase
- Inhaled anesthetic maintenance concentration not equal to 0.5 MAC
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Device: AI Clinical Decision Support SystemAn AI-based software system that provides real-time, on-screen recommendations to the anesthesiologist regarding drug administration and adjustments to maintain optimal patient physiological parameter | Device | Experimental: RL-Guided Hemodynamic Management |
| Procedure: Standard of Care AnesthesiaStandard anesthesia management according to institutional guidelines. The attending anesthesiologist makes all clinical decisions based on their expertise and judgment without input from the investigational AI system. | Procedure or surgery | Active Comparator: Standard Anesthesia Care |
Primary outcome
Mean Absolute Error (MAE) of RL-Recommended Vasoactive Agent Dosing Versus Anesthesiologist-Executed Dosing
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
The primary outcome is the mean absolute error (MAE) between vasoactive agent doses recommended by the RL-PRAIS system and doses actually administered by the attending anesthesiologist. Vasoactive agents (norepinephrine, phenylephrine, ephedrine) are converted to norepinephrine-equivalent units (NEq, mcg/kg/min). MAE is computed at each 1-minute decision epoch during hemodynamic optimization and averaged across all epochs per patient. Concordance rate is also reported as the proportion of epochs where the RL-recommended dose falls within a clinically acceptable range of the executed dose.
7 secondary outcomes
Time-Weighted Average of Mean Arterial Pressure Below 65 mmHg (TWA-MAP < 65 mmHg)
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Percentage of Time with MAP in Target Range (MAP TIR 65-100 mmHg)
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Incidence of Intraoperative Hypotensive Events
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
TWA-MAP Below 60 mmHg and Below 55 mmHg
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Cumulative Vasoactive Agent Consumption
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Mean Arterial Pressure Variability
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Clinician Acceptance Rate of RL Recommendations (Experimental Arm Only)
Time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Apr 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Device: AI Clinical Decision Support System in people with Intraoperative Hypotension and Hemodynamic Instability, run by Beijing Tsinghua Chang Gung Hospital at 2 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 6 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Gao Zhifeng, MD (15801249466, btchgzf@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Mean Absolute Error (MAE) of RL-Recommended Vasoactive Agent Dosing Versus Anesthesiologist-Executed Dosing (time frame: From the onset of hemodynamic optimization (15 minutes after surgical incision) until surgical wound closure). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Apr 2026.