HemodynamicSMART FLUIDNCT06871150
Three Different GHDT ( Goal Hemodynamic Directed Therapy) Strategies for Intraoperative Fluid Management Optimization During Major Abdominal Surgery: A Randomized Controlled Trial
A study testing Flotrac sensor, HPI and HPI-AFM in people with Hemodynamic, run by ASST Sette Laghi at 3 sites in Italy.
Trial summary
Major oncological surgery is among the most complex procedures, involving patients with a combination of high-risk factors that can significantly influence immediate postoperative outcomes and quality of life. Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Hemodynamic
- What is being tested?
- Flotrac sensor, HPI and HPI-AFM
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 150 participants
- Where
- 3 sitesItaly
- Study dates
- 2 Mar 2026to 30 Oct 2026
- 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 65 years and older
- All sexes
- No healthy volunteers
- Older adult
Who may be able to join
- Age ≥ 65 years.
- ASA physical status II-III-IV.
- Patients undergoing elective major abdominal oncological surgery.
- Revised Cardiac Index Score ≥ 2.
- Plan to perform the procedure with invasive arterial monitoring.
- Expected surgical time greater than 120 minutes.
Who cannot join
- Emergency or urgent surgeries.
- Severe chronic renal failure (creatinine clearance < 30 ml/min).
- Chronic heart failure (NYHA Class IV).
- Pregnant women.
- Contraindications to pulse contour hemodynamic monitoring.
- Liver surgery.
- Patient refusal.
Trial locations and contacts
3 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Italy3 sites, 3 recruiting
- Recruiting
ASST Papa Giovanni XXIII
Bergamo, Italy, 24127
Alberto Benigni Alberto Benigni, MD, abenigni@asst-pg23.it
Sara Cazzaniga Sara Cazzaniga, MD
- Recruiting
Humanitas Research Hospital
Rozzano, Italy, 20089
Fulvio Nisi Fulvio Nisi, MD, fulvio.nisi@humanitas.it
Federico Piccioni Federico Piccioni, PhD
- Recruiting
University Hospital Varese ASST SetteLaghi
Varese, Italy, 21100
Luca Guzzetti Luca Guzzetti, MD, luca.guzzetti@asst-settelaghi.it
Giovanni Gallone Giovanni Gallone, MD
About this study
Official title: Surgical Management and Advanced Real Time Technologies for Fluid Optimization in Major Abdominal Surgery: A Randomized Controlled Trial
Major oncological surgery is among the most complex procedures, involving patients with a combination of high-risk factors that can significantly influence immediate postoperative outcomes and quality of life. The intraoperative hemodynamic management of these patients represents a crucial challenge: maintaining cardiovascular stability and fluid balance during the surgery is associated with reduced complications, including acute kidney injury, myocardial ischemia, and sepsis. Literature has shown that intraoperative fluid administration guided by specific algorithms can reduce complications and improve patient outcomes.
In recent years, innovations in artificial intelligence (AI) have profoundly changed how hemodynamic variables are managed during surgery. AI enables real-time clinical data processing and offers the possibility to predict imminent hypotension episodes, allowing the medical team to intervene proactively. An example of such technologies is the Hypotension Prediction Index (HPI), which uses a machine learning algorithm to analyze hemodynamic data and predict the risk of hypotension with up to 80% accuracy, up to 10 minutes before it occurs. Therefore, softwares that integrate fluid administration volumes with parameters derived from pulse contour systems are used currently, enabling an analysis of the efficacy of administration of fluid boluses. For example, the Assisted Fluid Management (AFM) software helps the clinician in choosing the timing of fluid administration, determining its effectiveness in terms of fluid responsiveness. This allows to reduce complications related to improper intraoperative fluid management, such as organ damage, and optimize the use of fluids and vasopressor drugs.
Read more
Despite the growing use of AI in surgery, the clinical and economic impact of such technologies is still under study. Advanced intraoperative hemodynamic management tools have been shown to reduce the duration of hypotensive episodes and improve hemodynamic stability. The clinical impact of such monitoring, in terms of complications and length of postoperative stay, could be crucial to recommend their use in high-risk patient cohorts. This aligns with medical literature showing that postoperative complications increase patient-related hospitalization costs. This study aims to explore the utility of combining a Goal-Directed Hemodynamic Therapy (GDHT) protocol with AI software in three different scenarios.
The primary objective of the study is to evaluate if there is a significant difference in intraoperative fluid administration volumes across three different protocols of GDHT supported by AI, in patients undergoing major abdominal oncological surgery.
The study's secondary objectives include:
- Assess the rate of hypotensive episodes in terms of Time-Weighted Average Hypotension (TWAH) across the three groups.
- Analyze the rate of postoperative complications and hospital mortality across the three groups.
- Evaluate the total hospital stay duration and/or the number of days spent in intensive care across the three groups.
The study aims to provide evidence on the clinical efficacy of haemodynamic monitoring technologies currently present in daily practice. The results will allow us to define an optimization of intraoperative haemodynamic management, improving clinical outcomes and optimizing the use of healthcare resources.
Read the detailed description
ASSISTED FLUID MANAGEMENT TECHNOLOGY SOFTWARE The Assisted Fluid Management (AFM) technology, developed by Edwards Lifesciences, is an advanced software designed to assist clinicians in optimizing fluid administration during non-cardiac surgeries. Using arterial pressure waveform analysis, the software evaluates in real-time the patient's response to administered fluids and provides personalized recommendations to achieve specific stroke volume variation targets. Thanks to an algorithm that learns from prior data and the patient's current conditions, the system can predict the effectiveness of a fluid bolus and suggest whether and when to administer it, leaving the clinician with final decision-making control. This combination of automated analysis and clinical flexibility makes it a potentially valuable tool for improving intraoperative fluid management and reducing the complexity of therapeutic decisions.
Will be a randomized controlled trial including patients undergoing major oncological surgery in tertiary care hospitals, with fluid management aligned with the GDHT philosophy.
The analysis will compare three groups:
- FLOTRAC Group: Patients managed using the FLOTRAC technology for intraoperative fluid monitoring and management.
- HPI Group: Patients managed using the Hypotension Prediction Index (HPI) technology.
- HPI-AFM Group: Patients managed using both HPI and AFM technologies for intraoperative fluid management.
The study will be multicentric, involving tertiary care hospitals. This will allow us to collect a sufficiently large and representative sample to ensure statistical validity and generalizability of the results.
Inclusion Criteria:
- Age ≥ 18 years.
- ASA physical status II-III-IV.
- Patients undergoing elective major abdominal oncological surgery.
- Revised Cardiac Index Score ≥ 2.
- Plan to perform the procedure with invasive arterial monitoring.
- Expected surgical time greater than 120 minutes.
Exclusion Criteria:
- Emergency or urgent surgeries.
- Severe chronic renal failure (creatinine clearance < 30 ml/min).
- Chronic heart failure (NYHA Class IV).
- Pregnant women.
- Contraindications to pulse contour hemodynamic monitoring.
- Liver surgery.
- Patient refusal.
Data will be collected in three phases:
- Preoperative: basic demographic and clinical data.
- Intraoperative: hemodynamic parameters and fluid management.
- Postoperative: complications, length of stay, and clinical outcomes.
Data will be analyzed using parametric and non-parametric tests based on the distribution. A multivariate regression model will be used to control for confounding factors.
The study will be conducted in compliance with GDPR regulations. An informed consent will be required from all participants.
- Conditions
- Hemodynamic
- Being tested
- Flotrac sensor, HPI, HPI-AFM
- Keywords
- GHDT, Hypotension prediction, Assisted Fluid Management
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Flotrac sensorDevice
Traditional management of hemodynamic parameters and intraoperative fluids without the aid of predictive tools based on artificial intelligence.
Possibility of having advanced hemodynamic analysis tools such as SV (stroke volume), SVV (stroke volume variation), PPV (pulse pressure variation), CO (cardiac output).
The anesthetist will decide whether to administer fluids, vasopressors, or other pharmacological interventions to maintain hemodynamic stability basing on clinical hemodynamic parameters derived from pulse contour systems, in accordance with a specific flowchart.
Interventions will be applied when blood pressure decreases, or clinical signs of instability are observed
HPIDevice
The Hypotension Prediction Index (HPI) is an advanced arterial waveform analysis algorithm that uses machine learning to predict hypotensive episodes (defined as mean arterial pressure [MAP] < 65 mmHg) five minutes in advance, achieving high sensitivity and specificity. This technology is based on patient demographic data (e.g., age, height, weight) and hemodynamic parameters derived from arterial waveform analysis.
- HPI uses demographic information and hemodynamic signals obtained via a radial arterial catheter.
- The signals are analyzed using Edwards Lifesciences' Acumen IQ software, which has been further developed to include prediction of hypotensive episodes.
The algorithm provides a numerical value (0-100) reflecting the risk of imminent hypotension. An HPI value above 85 signals a high likelihood of hypotension.
The system also provides advanced hemodynamic data, including cardiac output, dynamic arterial elastance, dP/dtmax (systolic slope), and stroke volume.
HPI-AFMDevice
HPI: Provides a predictive index (from 0 to 100) based on real-time hemodynamic data, indicating the probability of the patient developing a hypotensive episode (MAP < 65 mmHg) within the next 10-15 minutes.
AFM: In addition to hypotension prediction, continuously monitors parameters such as stroke volume and cardiac output, providing indications for optimal fluid administration. It is programmed to suggest the quantity and the speed of fluid administration based on real-time data and patient conditions.
In conjunction with the HPI system, the AFM suggests administering a specific fluid volume to correct the patient's hemodynamic status.
The AFM uses a predictive algorithm to calculate the patient's response to fluid administration, enabling anesthetists to dynamically adjust therapy.
The AFM system is based on assisted clinical decisions, where anesthetist receive algorithm-based AI recommendations to proactively administer fluids, avoiding the traditional "reactive" approach.
| Study group | Role | What they receive |
|---|---|---|
| FLOTRAC group | Active comparator | : Patients managed using the FLOTRAC technology for intraoperative fluid monitoring and management. Receives: Device: Flotrac sensor |
| HPI group | Active comparator | Patients managed using the Hypotension Prediction Index (HPI) technology. Receives: Device: HPI |
| HPI-AFM group | Active comparator | .Patients managed using both HPI and AFM technologies for intraoperative fluid management. Receives: Device: HPI-AFM |
What is being measured
The primary outcome is the main question the study is designed to answer.
significant difference in intraoperative fluid administration volumes across three different protocols of GDHT supported by AI, in patients undergoing major abdominal oncological surgery
Measured: From start surgery to end surgery
Secondary outcomes (3)
• Assess the rate of hypotensive episodes in terms of Time-Weighted Average Hypotension (TWAH) across the three groups.
The TWAH (Time-Weighted Average Hypotension) will be calculated for the three groups. This metric evaluates the intensity and duration of hypotensive episodes during the perioperative period or continuous monitoring. It represents the cumulative hypotension burden normalized by the total duration of monitoring or surgery, providing a unified measure of severity.
Measured: From start surgery to end surgery
Postoperative complications and hospital mortality
Analyze the rate of postoperative complications and hospital mortality across the three groups.
Complications will be classified according to the Clavien-Dindo Classification.
Measured: From the end of the surgery to 30 days after discharge
Total hospital stay duration and/or the number of days spent in intensive care
Evaluate the total hospital stay duration and/or the number of days spent in intensive care across the three groups.
Measured: From the end of the surgery to 30 days after discharge
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Mar 2025
- Study start2 Mar 2026 (estimated)
- Primary completion30 Sep 2026 (estimated)
- Study completion30 Oct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HemodynamicStudies 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
- None (open label)
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- ASST Sette Laghi
- Sponsor type
- University, hospital or other
- Collaborators
- Humanitas Research Hospital IRCCS, Rozzano-Milan, A.O. Ospedale Papa Giovanni XXIII
- Responsible party
- Principal investigator, Luca Guzzetti, Ospedale di Circolo - Fondazione Macchi
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06871150
- Sponsor's protocol ID
- 24/2025
- Acronym
- SMART FLUID
- Status last verified
- Mar 2026
- First submitted
- 25 Feb 2025
- Last updated
- 25 Mar 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 25 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Surgical Management and Advanced Real Time Technologies for Fluid Optimization in Major Abdominal Surgery: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT06871150
- Acronym / sponsor ID
- SMART FLUID / 24/2025
- Conditions
- Hemodynamic
- Keywords
- GHDT, Hypotension prediction, Assisted Fluid Management
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- ASST Sette LaghiUniversity, hospital or other
- Collaborators
- Humanitas Research Hospital IRCCS, Rozzano-Milan, A.O. Ospedale Papa Giovanni XXIII
- Study start
- 2 Mar 2026 (estimated)
- Primary completion
- 30 Sep 2026 (estimated)
- Study completion
- 30 Oct 2026 (estimated)
- First posted
- 11 Mar 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.
Major oncological surgery is among the most complex procedures, involving patients with a combination of high-risk factors that can significantly influence immediate postoperative outcomes and quality of life. The intraoperative hemodynamic management of these patients represents a crucial challenge: maintaining cardiovascular stability and fluid balance during the surgery is associated with reduced complications, including acute kidney injury, myocardial ischemia, and sepsis. Literature has shown that intraoperative fluid administration guided by specific algorithms can reduce complications and improve patient outcomes.
In recent years, innovations in artificial intelligence (AI) have profoundly changed how hemodynamic variables are managed during surgery. AI enables real-time clinical data processing and offers the possibility to predict imminent hypotension episodes, allowing the medical team to intervene proactively. An example of such technologies is the Hypotension Prediction Index (HPI), which uses a machine learning algorithm to analyze hemodynamic data and predict the risk of hypotension with up to 80% accuracy, up to 10 minutes before it occurs. Therefore, softwares that integrate fluid administration volumes with parameters derived from pulse contour systems are used currently, enabling an analysis of the efficacy of administration of fluid boluses. For example, the Assisted Fluid Management (AFM) software helps the clinician in choosing the timing of fluid administration, determining its effectiveness in terms of fluid responsiveness. This allows to reduce complications related to improper intraoperative fluid management, such as organ damage, and optimize the use of fluids and vasopressor drugs.
Despite the growing use of AI in surgery, the clinical and economic impact of such technologies is still under study. Advanced intraoperative hemodynamic management tools have been shown to reduce the duration of hypotensive episodes and improve hemodynamic stability. The clinical impact of such monitoring, in terms of complications and length of postoperative stay, could be crucial to recommend their use in high-risk patient cohorts. This aligns with medical literature showing that postoperative complications increase patient-related hospitalization costs. This study aims to explore the utility of combining a Goal-Directed Hemodynamic Therapy (GDHT) protocol with AI software in three different scenarios.
The primary objective of the study is to evaluate if there is a significant difference in intraoperative fluid administration volumes across three different protocols of GDHT supported by AI, in patients undergoing major abdominal oncological surgery.
The study's secondary objectives include:
- Assess the rate of hypotensive episodes in terms of Time-Weighted Average Hypotension (TWAH) across the three groups.
- Analyze the rate of postoperative complications and hospital mortality across the three groups.
- Evaluate the total hospital stay duration and/or the number of days spent in intensive care across the three groups.
The study aims to provide evidence on the clinical efficacy of haemodynamic monitoring technologies currently present in daily practice. The results will allow us to define an optimization of intraoperative haemodynamic management, improving clinical outcomes and optimizing the use of healthcare resources.
Detailed description
ASSISTED FLUID MANAGEMENT TECHNOLOGY SOFTWARE The Assisted Fluid Management (AFM) technology, developed by Edwards Lifesciences, is an advanced software designed to assist clinicians in optimizing fluid administration during non-cardiac surgeries. Using arterial pressure waveform analysis, the software evaluates in real-time the patient's response to administered fluids and provides personalized recommendations to achieve specific stroke volume variation targets. Thanks to an algorithm that learns from prior data and the patient's current conditions, the system can predict the effectiveness of a fluid bolus and suggest whether and when to administer it, leaving the clinician with final decision-making control. This combination of automated analysis and clinical flexibility makes it a potentially valuable tool for improving intraoperative fluid management and reducing the complexity of therapeutic decisions.
Will be a randomized controlled trial including patients undergoing major oncological surgery in tertiary care hospitals, with fluid management aligned with the GDHT philosophy.
The analysis will compare three groups:
- FLOTRAC Group: Patients managed using the FLOTRAC technology for intraoperative fluid monitoring and management.
- HPI Group: Patients managed using the Hypotension Prediction Index (HPI) technology.
- HPI-AFM Group: Patients managed using both HPI and AFM technologies for intraoperative fluid management.
The study will be multicentric, involving tertiary care hospitals. This will allow us to collect a sufficiently large and representative sample to ensure statistical validity and generalizability of the results.
Inclusion Criteria:
- Age ≥ 18 years.
- ASA physical status II-III-IV.
- Patients undergoing elective major abdominal oncological surgery.
- Revised Cardiac Index Score ≥ 2.
- Plan to perform the procedure with invasive arterial monitoring.
- Expected surgical time greater than 120 minutes.
Exclusion Criteria:
- Emergency or urgent surgeries.
- Severe chronic renal failure (creatinine clearance < 30 ml/min).
- Chronic heart failure (NYHA Class IV).
- Pregnant women.
- Contraindications to pulse contour hemodynamic monitoring.
- Liver surgery.
- Patient refusal.
Data will be collected in three phases:
- Preoperative: basic demographic and clinical data.
- Intraoperative: hemodynamic parameters and fluid management.
- Postoperative: complications, length of stay, and clinical outcomes.
Data will be analyzed using parametric and non-parametric tests based on the distribution. A multivariate regression model will be used to control for confounding factors.
The study will be conducted in compliance with GDPR regulations. An informed consent will be required from all participants.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| FLOTRAC group | Active comparator | Device: Flotrac sensor: Patients managed using the FLOTRAC technology for intraoperative fluid monitoring and management. |
| HPI group | Active comparator | Device: HPIPatients managed using the Hypotension Prediction Index (HPI) technology. |
| HPI-AFM group | Active comparator | Device: HPI-AFM.Patients managed using both HPI and AFM technologies for intraoperative fluid management. |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Older adult
Key inclusion criteria (6 listed)
- Age ≥ 65 years.
- ASA physical status II-III-IV.
- Patients undergoing elective major abdominal oncological surgery.
- Revised Cardiac Index Score ≥ 2.
- Plan to perform the procedure with invasive arterial monitoring.
Key exclusion criteria (7 listed)
- Emergency or urgent surgeries.
- Severe chronic renal failure (creatinine clearance < 30 ml/min).
- Chronic heart failure (NYHA Class IV).
- Pregnant women.
- Contraindications to pulse contour hemodynamic monitoring.
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 |
|---|---|---|
| Flotrac sensorTraditional management of hemodynamic parameters and intraoperative fluids without the aid of predictive tools based on artificial intelligence. Possibility of having advanced hemodynamic analysis tools such as SV (stroke volume), SVV (stroke volume variation), PPV (pulse pressure variation), CO (cardiac output). The anesthetist will decide whether to administer fluids, vasopressors, or other pharmacological interventions to maintain hemodynamic stability basing on clinical hemodynamic parameters derived from pulse contour systems, in accordance with a specific flowchart. Interventions will be applied when blood pressure decreases, or clinical signs of instability are observed | Device | FLOTRAC group |
| HPIThe Hypotension Prediction Index (HPI) is an advanced arterial waveform analysis algorithm that uses machine learning to predict hypotensive episodes (defined as mean arterial pressure [MAP] < 65 mmHg) five minutes in advance, achieving high sensitivity and specificity. This technology is based on patient demographic data (e.g., age, height, weight) and hemodynamic parameters derived from arterial waveform analysis. * HPI uses demographic information and hemodynamic signals obtained via a radial arterial catheter. * The signals are analyzed using Edwards Lifesciences' Acumen IQ software, which has been further developed to include prediction of hypotensive episodes. The algorithm provides a numerical value (0-100) reflecting the risk of imminent hypotension. An HPI value above 85 signals a high likelihood of hypotension. The system also provides advanced hemodynamic data, including cardiac output, dynamic arterial elastance, dP/dtmax (systolic slope), and stroke volume. | Device | HPI group |
| HPI-AFMHPI: Provides a predictive index (from 0 to 100) based on real-time hemodynamic data, indicating the probability of the patient developing a hypotensive episode (MAP < 65 mmHg) within the next 10-15 minutes. AFM: In addition to hypotension prediction, continuously monitors parameters such as stroke volume and cardiac output, providing indications for optimal fluid administration. It is programmed to suggest the quantity and the speed of fluid administration based on real-time data and patient conditions. In conjunction with the HPI system, the AFM suggests administering a specific fluid volume to correct the patient's hemodynamic status. The AFM uses a predictive algorithm to calculate the patient's response to fluid administration, enabling anesthetists to dynamically adjust therapy. The AFM system is based on assisted clinical decisions, where anesthetist receive algorithm-based AI recommendations to proactively administer fluids, avoiding the traditional "reactive" approach. | Device | HPI-AFM group |
Primary outcome
significant difference in intraoperative fluid administration volumes across three different protocols of GDHT supported by AI, in patients undergoing major abdominal oncological surgery
Time frame: From start surgery to end surgery
3 secondary outcomes
• Assess the rate of hypotensive episodes in terms of Time-Weighted Average Hypotension (TWAH) across the three groups.
Time frame: From start surgery to end surgery
Postoperative complications and hospital mortality
Time frame: From the end of the surgery to 30 days after discharge
Total hospital stay duration and/or the number of days spent in intensive care
Time frame: From the end of the surgery to 30 days after discharge
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 25 Mar 2026.
- Individual participant dataSharing planned: Yes
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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.
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Flotrac sensor, HPI and HPI-AFM in people with Hemodynamic, run by ASST Sette Laghi at 3 sites in Italy.
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 6 inclusion and 7 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: looking for participants now, as of the sponsor's last update on 25 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Italy. 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 Luca Guzzetti Luca Guzzetti, MD (0039 0332393447, luca.guzzetti@asst-settelaghi.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
significant difference in intraoperative fluid administration volumes across three different protocols of GDHT supported by AI, in patients undergoing major abdominal oncological surgery (time frame: From start surgery to end surgery). 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 25 Mar 2026.