NeoplasmFOCUS-AFMNCT07314853
Using Artificial Intelligence to Guide Fluid Therapy During Major Cancer Surgery: A Randomized Controlled Trial
A study testing Artificial Intelligence-Assisted Fluid Management and Standard fluid management in people with Neoplasm and Cancer, run by National Cancer Institute, Naples at 1 site in Italy.
Trial summary
The goal of this clinical trial is to learn if using artificial intelligence to guide intravenous fluid therapy during major cancer surgery can help keep blood pressure more stable compared with usual care in adult patients undergoing major cancer surgery. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Neoplasm, Cancer, Hemodynamic (MAP) Stability
- What is being tested?
- Artificial Intelligence-Assisted Fluid Management and Standard fluid management
- Type of treatment
- Injection or infusion
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 176 participants
- Where
- 1 siteItaly
- Study dates
- Feb 2026to Feb 2029
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age ≥ 18 years
- American Society of Anesthesiologists (ASA) Physical Status II-IV
- Undergoing major abdominal oncologic surgery (open or laparoscopic) with an expected duration >2 hours
- Planned invasive arterial pressure monitoring
- Ability to understand and sign informed consent
Who cannot join
- Significant arrhythmias (e.g., persistent atrial fibrillation)
- Severe aortic stenosis
- Emergency surgery
- Sepsis
- End-stage renal disease on dialysis
- Pregnancy
- Impossibility to cannulate the radial artery
- Refusal to participate or refusal of data processing consent
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Italy1 site
IRCCS Istituto Nazionale Tumori "Fondazione G. Pascale"
Naples, 80100
IRCCS Istituto Nazionale Tumori "Fondazione G. Pascale" Cristina Romano, Data Manager, +3909117770626, mc.romano@istitutotumori.na.it
About this study
Official title: Fluid Optimization in Cancer Surgery With AI-Assisted Management - FOCUS-AFM Trial
The goal of this clinical trial is to learn if using artificial intelligence to guide intravenous fluid therapy during major cancer surgery can help keep blood pressure more stable compared with usual care in adult patients undergoing major cancer surgery. The main questions it aims to answer are:
- Does artificial intelligence-guided fluid therapy reduce hypotensive events during surgery?
- Does this approach improve recovery and reduce complications after major cancer surgery?
Read more
Researchers will compare artificial intelligence-guided fluid therapy with standard fluid management to see if the artificial intelligence-guided approach provides better support during surgery.
Participants will:
- Undergo major cancer surgery under general anesthesia
- Receive either artificial intelligence-guided fluid management or standard fluid management during surgery
- Be monitored during and after surgery as part of routine clinical care
- Be followed after surgery to assess recovery and possible complications
Read the detailed description
This multicentre randomized controlled clinical trial evaluates the impact of artificial intelligence-guided intraoperative intravenous fluid therapy on hemodynamic management and postoperative outcomes in adult patients undergoing major abdominal cancer surgery.
Optimal intraoperative fluid therapy is a critical component of anesthetic management during major oncologic surgery. Both inadequate and excessive fluid administration may contribute to hemodynamic instability and postoperative complications. Episodes of intraoperative hypotension have been consistently associated with increased postoperative morbidi ty and mortality, particularly in high-risk surgical populations. Although goal-directed strategies for intraoperative fluid therapy have been proposed, their implementation in routine clinical practice remains heterogeneous and highly operator-dependent.
Advances in artificial intelligence have enabled the development of decision support systems capable of integrating continuous hemodynamic data derived from standard intraoperative monitoring. These systems are designed to assist clinicians by analyzing multiple physiologic variables in real time and providing recommendations for intravenous fluid administration aimed at supporting circulatory stability, while preserving full clinician control over treatment decisions.
In this trial, participants undergoing major abdominal cancer surgery under general anesthesia are randomly assigned to receive either artificial intelligence-guided intravenous fluid therapy or standard intravenous fluid management according to routine clinical practice. Randomization is centralized and stratified by relevant procedural factors. In the intervention group, intravenous fluid administration is supported by an artificial intelligence-based decision support system that continuously analyzes intraoperative hemodynamic data and generates recommendations for fluid challenges. Clinicians are strongly encouraged to follow the system recommendations; however, they retain full responsibility and may accept or override these recommendations based on their clinical judgment. In the control group, intraoperative fluid therapy is managed according to usual clinical practice without artificial intelligence guidance.
Standard perioperative monitoring is applied in both study groups, including continuous invasive arterial blood pressure monitoring. Intraoperative hemodynamic variables, fluid administration, and use of vasoactive medications are recorded prospectively using electronic anesthesia records and monitoring system outputs. Postoperative clinical data are collected during routine inpatient care and scheduled follow-up.
The study focuses on the intraoperative period as a key window during which hemodynamic management may influence postoperative recovery and longer-term outcomes. By evaluating an artificial intelligence-based decision support approach in a randomized multicentre setting, this trial aims to generate evidence on whether technology-assisted intravenous fluid therapy can improve intraoperative management and support better clinical outcomes in patients undergoing major cancer surgery.
- Conditions
- Neoplasm, Cancer, Hemodynamic (MAP) Stability, Cancer Surgery, Artificial Intelligence (AI), Fluid Therapy DURING SURGERY
- Being tested
- Artificial Intelligence-Assisted Fluid Management, Standard fluid management
- Keywords
- randomized controlled trial, cancer, fluid balance, fluid therapy, artificial intelligence
- Medical subject headings
- Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence-Assisted Fluid ManagementOther
In this intervention, intraoperative intravenous fluid management is supported by an artificial intelligence-based clinical decision support system. The system continuously analyzes real-time hemodynamic data derived from standard intraoperative monitoring and provides recommendations for intravenous fluid administration. Clinicians are strongly encouraged to follow these recommendations but retain full responsibility and may accept or override them based on clinical judgment. The intervention is applied during the intraoperative period only and does not replace standard anesthetic care.
Standard fluid managementOther
In this intervention participants receive intraoperative intravenous fluid therapy managed according to usual clinical practice, without artificial intelligence guidance. Fluid administration is determined by the attending clinician based on standard monitoring and clinical judgment.
| Study group | Role | What they receive |
|---|---|---|
| Standard Fluid Management | Active comparator | Participants receive intraoperative intravenous fluid therapy managed according to usual clinical practice, without artificial intelligence guidance. Fluid administration is determined by the attending clinician based on standard monitoring and clinical judgment. Receives: Other: Standard fluid management |
| AI-Assisted Fluid Management | Experimental | Participants assigned to this arm receive intraoperative intravenous fluid therapy supported by an artificial intelligence-based clinical decision support system. The system analyzes real-time hemodynamic data and provides recommendations for fluid administration. Clinicians are strongly encouraged to follow these recommendations but may accept or override them based on clinical judgment. Receives: Other: Artificial Intelligence-Assisted Fluid Management |
What is being measured
The primary outcome is the main question the study is designed to answer.
Intraoperative Hypotension Burden
The burden of intraoperative hypotension, measured as the time-weighted average (TWA) of intraoperative hypotension, a composite measure that accounts for both the depth and duration of low arterial blood pressure over time. TWA reflects the overall hypotensive burden during surgery by integrating how low blood pressure falls and for how long it remains below predefined thresholds, assessed using continuous invasive blood pressure monitoring
Measured: From induction of anesthesia to the end of surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Jan 2026
- Study startFeb 2026 (estimated)
- Primary completionFeb 2027 (estimated)
- Study completionFeb 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for NeoplasmStudies 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
- 176 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Cancer Institute, Naples
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07314853
- Sponsor's protocol ID
- FOCUS AFM
- Acronym
- FOCUS-AFM
- Status last verified
- Dec 2025
- First submitted
- 18 Dec 2025
- Last updated
- 9 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 9 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Fluid Optimization in Cancer Surgery With AI-Assisted Management - FOCUS-AFM Trial
- ClinicalTrials.gov ID
- NCT07314853
- Acronym / sponsor ID
- FOCUS-AFM / FOCUS AFM
- Conditions
- Neoplasm, Cancer, Hemodynamic (MAP) Stability, Cancer Surgery, Artificial Intelligence (AI), Fluid Therapy DURING SURGERY
- Keywords
- randomized controlled trial, cancer, fluid balance, fluid therapy, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 176 participants (estimated)
- Lead sponsor
- National Cancer Institute, NaplesUniversity, hospital or other
- Study start
- Feb 2026 (estimated)
- Primary completion
- Feb 2027 (estimated)
- Study completion
- Feb 2029 (estimated)
- First posted
- 2 Jan 2026 (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.
The goal of this clinical trial is to learn if using artificial intelligence to guide intravenous fluid therapy during major cancer surgery can help keep blood pressure more stable compared with usual care in adult patients undergoing major cancer surgery. The main questions it aims to answer are:
- Does artificial intelligence-guided fluid therapy reduce hypotensive events during surgery?
- Does this approach improve recovery and reduce complications after major cancer surgery?
Researchers will compare artificial intelligence-guided fluid therapy with standard fluid management to see if the artificial intelligence-guided approach provides better support during surgery.
Participants will:
- Undergo major cancer surgery under general anesthesia
- Receive either artificial intelligence-guided fluid management or standard fluid management during surgery
- Be monitored during and after surgery as part of routine clinical care
- Be followed after surgery to assess recovery and possible complications
Detailed description
This multicentre randomized controlled clinical trial evaluates the impact of artificial intelligence-guided intraoperative intravenous fluid therapy on hemodynamic management and postoperative outcomes in adult patients undergoing major abdominal cancer surgery.
Optimal intraoperative fluid therapy is a critical component of anesthetic management during major oncologic surgery. Both inadequate and excessive fluid administration may contribute to hemodynamic instability and postoperative complications. Episodes of intraoperative hypotension have been consistently associated with increased postoperative morbidi ty and mortality, particularly in high-risk surgical populations. Although goal-directed strategies for intraoperative fluid therapy have been proposed, their implementation in routine clinical practice remains heterogeneous and highly operator-dependent.
Advances in artificial intelligence have enabled the development of decision support systems capable of integrating continuous hemodynamic data derived from standard intraoperative monitoring. These systems are designed to assist clinicians by analyzing multiple physiologic variables in real time and providing recommendations for intravenous fluid administration aimed at supporting circulatory stability, while preserving full clinician control over treatment decisions.
In this trial, participants undergoing major abdominal cancer surgery under general anesthesia are randomly assigned to receive either artificial intelligence-guided intravenous fluid therapy or standard intravenous fluid management according to routine clinical practice. Randomization is centralized and stratified by relevant procedural factors. In the intervention group, intravenous fluid administration is supported by an artificial intelligence-based decision support system that continuously analyzes intraoperative hemodynamic data and generates recommendations for fluid challenges. Clinicians are strongly encouraged to follow the system recommendations; however, they retain full responsibility and may accept or override these recommendations based on their clinical judgment. In the control group, intraoperative fluid therapy is managed according to usual clinical practice without artificial intelligence guidance.
Standard perioperative monitoring is applied in both study groups, including continuous invasive arterial blood pressure monitoring. Intraoperative hemodynamic variables, fluid administration, and use of vasoactive medications are recorded prospectively using electronic anesthesia records and monitoring system outputs. Postoperative clinical data are collected during routine inpatient care and scheduled follow-up.
The study focuses on the intraoperative period as a key window during which hemodynamic management may influence postoperative recovery and longer-term outcomes. By evaluating an artificial intelligence-based decision support approach in a randomized multicentre setting, this trial aims to generate evidence on whether technology-assisted intravenous fluid therapy can improve intraoperative management and support better clinical outcomes in patients undergoing major cancer surgery.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Standard Fluid Management | Active comparator | Other: Standard fluid managementParticipants receive intraoperative intravenous fluid therapy managed according to usual clinical practice, without artificial intelligence guidance. Fluid administration is determined by the attending clinician based on standard monitoring and clinical judgment. |
| AI-Assisted Fluid Management | Experimental | Other: Artificial Intelligence-Assisted Fluid ManagementParticipants assigned to this arm receive intraoperative intravenous fluid therapy supported by an artificial intelligence-based clinical decision support system. The system analyzes real-time hemodynamic data and provides recommendations for fluid administration. Clinicians are strongly encouraged to follow these recommendations but may accept or override them based on clinical judgment. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Age ≥ 18 years
- American Society of Anesthesiologists (ASA) Physical Status II-IV
- Undergoing major abdominal oncologic surgery (open or laparoscopic) with an expected duration >2 hours
- Planned invasive arterial pressure monitoring
- Ability to understand and sign informed consent
Key exclusion criteria (8 listed)
- Significant arrhythmias (e.g., persistent atrial fibrillation)
- Severe aortic stenosis
- Emergency surgery
- Sepsis
- End-stage renal disease on dialysis
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 |
|---|---|---|
| Artificial Intelligence-Assisted Fluid ManagementIn this intervention, intraoperative intravenous fluid management is supported by an artificial intelligence-based clinical decision support system. The system continuously analyzes real-time hemodynamic data derived from standard intraoperative monitoring and provides recommendations for intravenous fluid administration. Clinicians are strongly encouraged to follow these recommendations but retain full responsibility and may accept or override them based on clinical judgment. The intervention is applied during the intraoperative period only and does not replace standard anesthetic care. | Other | AI-Assisted Fluid Management |
| Standard fluid managementIn this intervention participants receive intraoperative intravenous fluid therapy managed according to usual clinical practice, without artificial intelligence guidance. Fluid administration is determined by the attending clinician based on standard monitoring and clinical judgment. | Other | Standard Fluid Management |
Primary outcome
Intraoperative Hypotension Burden
Time frame: From induction of anesthesia to the end of surgery
The burden of intraoperative hypotension, measured as the time-weighted average (TWA) of intraoperative hypotension, a composite measure that accounts for both the depth and duration of low arterial blood pressure over time. TWA reflects the overall hypotensive burden during surgery by integrating how low blood pressure falls and for how long it remains below predefined thresholds, assessed using continuous invasive blood pressure monitoring
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 9 Jan 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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence-Assisted Fluid Management and Standard fluid management in people with Neoplasm and Cancer, run by National Cancer Institute, Naples at 1 site 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 5 inclusion and 8 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 9 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site 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 gilda pasta, MD (+393498369411, g.pasta@istitutotumori.na.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Intraoperative Hypotension Burden (time frame: From induction of anesthesia to the end of 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 9 Jan 2026; AzTrials last refreshed its copy on 29 Oct 2026.