An interventional study of Assisted Fluid Management and Goal Directed Fluid Therapy (GDT) in Ovarian Cancer, Hemodynamic Instability and Fluid Overload, sponsored by Fondazione Policlinico Universitario Agostino Gemelli IRCCS. Recruiting at 1 site in Italy. Open to female participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-05-11.
Sponsored by Fondazione Policlinico Universitario Agostino Gemelli IRCCS · Not applicable, Interventional, and Treatment
Cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is a complex surgical procedure carried out through laparotomic approach. After CRS-HIPEC morbidity and mortality rates go up to 20%-40% and 3% respectively, and acute kidney injury and pulmonary effusion/oedema are the most frequent postoperative complications.
Intraoperative hypotension and risk of fluid overload are common. Efficient and accurate control of arterial pressure and cardiac output is a major concern during CRS-HIPEC.
The aim of this study is to perform a pilot study describing a hemodynamic management protocol based on artificial intelligence - derived parameters, that allows to implement the standard goal directed therapy (GDT) protocol in term of amount of IOH and stroke volume (SV) optimization.
Specifically, this study aims to test the hypotheses that a hemodynamic protocol based on HPI-AFM monitoring compared to standard GDT helps clinicians reduce IOH during surgery and improve the time "in-target" range of SV index.
The study cohort will be compared to an historical cohort of 50 patients underwent to CRS-HIPEC between 2022 and 2024, managed with an institutional goal directed therapy protocol.
Cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is a complex surgical procedure carried out through laparotomic approach. Intraoperative management represents a challenge for anesthesiologist: hemodynamic instability (due to extremely destructive surgery with fluids shift and blood loss), biochemical abnormalities (worsened by cytotoxic chemotherapic agents peritoneal infusion, with profound metabolic acidosis and electrolytes disturbance), and extreme thermal fluctuations related to the different phases of surgery.
CRS-HIPEC is fraught with significant drawbacks: morbidity and mortality rates go up to 20%-40% and 3% respectively, and acute kidney injury and pulmonary effusion/oedema are the most frequent postoperative complications. More than 70% of the patients are admitted in Intensive Care Unit after the surgery.
Intraoperative hypotension (IOH) during CRS-HIPEC is common, and as it is associated with the potential for harm [9]. At the same time, extensive fluid resuscitation in peritoneal cancer patients is associated with a poor postoperative outcome, and avoiding fluid overload is recommended. Optimizing flow and pressure requires repeated measurement of both variables and use of established protocols for vasopressor and fluid administration (the so called "individualized hemodynamic management") has been shown to be associated with decreased postoperative complications compared to routine care. Efficient and accurate control of arterial pressure and cardiac output is a major concern during CRS-HIPEC, because it requires frequent manual adjustments of vasopressor infusion rates and timely fluid administration.
A peculiar aspect of CRS-HIPEC is the delicate phase of intraoperative chemotherapy. During this procedure, hyperthermia and the extensive cytolysis caused by the chemotherapeutic drug lead to multifactorial metabolic acidosis and intense vasodilation: managing fluid therapy and vasoconstrictor drugs is often extremely challenging.
The aim of this study is to perform a pilot study describing a hemodynamic management protocol based on artificial intelligence - derived parameters, that allows to implement the standard goal directed therapy (GDT) protocol in term of amount of IOH and stroke volume (SV) optimization during CRS-HIPEC.
All patients included in the study will have a radial arterial catheter inserted before or immediately after anesthesia induction and connected to Hemosphere. The clinician will follow an algorithm based on Assisted Fluid Management (AFM) for fluid infusion and on Hypotension Prediction Index (HPI) to titrate vasopressors and inotropes. AFM will be set as "medium" during cytoreductive phase and "restrictive" during HIPEC. A maximum volume of fluids per patients will be set at 10 ml/kg/hr.
Specifically, this study aims to test the hypotheses that a hemodynamic protocol based on HPI-AFM monitoring compared to standard GDT helps clinicians reduce IOH during surgery and improve the time "in-target" range of SV index (a value that estimates the time with SVI within target range, characterizing optimization of cardiac function), avoiding a detrimental fluid overload.
Two hierarchical primary endpoints were defined. The first primary endpoint will be the time-weighted average (TWA) - MAP less than 65 mmHg (expressed in mmHg) throughout surgery. The second primary endpoint will be the time spent during surgery in an optimized range of SVI (the "in target" range will be defined at the beginning of hemodynamic monitoring).
Secondary endpoints will be total norepinephrine dose and total amount of fluids.
Exploratory outcomes will be the fraction of AFM software-prompted boluses that resulted in the desired increase in SV, the incidence of post-operative complications (specifically postoperative Pulmonary Complications), ICU and hospital length of stay (LOS) and the analysis of hospital costs related to the adoption of AFM software in the clinical practice of our hospital.
The study cohort will be compared to an historical cohort of 50 patients underwent to CRS-HIPEC between 2022 and 2024, managed with an institutional goal directed therapy protocol.
Exclusion Criteria:
The patients will be managed following an algorithm based on Assisted Fluid Management (AFM) for fluid infusion and on Hypotension Prediction Index (HPI) to titrate vasopressors and inotropes. AFM will be set as "medium" during cytoreductive phase and "restrictive" during HIPEC.
Device: Assisted Fluid Management
The patients have been managed following institutional algorithm aimed to optimize stroke volume index and reduce intraoperative hypotension
Other: Goal Directed Fluid Therapy (GDT)
Intraoperative fluid infusion will be regulated according to the Assisted Fluid Management (AFM) software and on Hypotension Prediction Index (HPI) will be used to titrate vasopressors and inotropes.
Institutional goal directed therapy protocol used to optimize SVI and reduce intraoperative hypotension
TWA-MAP<65mmHg
We intend to define two hierarchical primary endpoints. The first primary endpoint will be the time-weighted average (TWA) - MAP less than 65 mmHg (expressed in mmHg) throughout surgery. The second primary endpoint will be the time spent during surgery in an optimized range of SVI (the "in target" range will be defined at the beginning of hemodynamic monitoring). The optimized range of SVI is the range between the patient's baseline SVI rate and the SVI obteined after a 250 ml fluid bolus.
Time frame: Perioperative
TIT-SVI
We intend to define two hierarchical primary endpoints. The first primary endpoint will be the time-weighted average (TWA) - MAP less than 65 mmHg (expressed in mmHg) throughout surgery. The second primary endpoint will be the time spent during surgery in an optimized range of SVI (the "in target" range will be defined at the beginning of hemodynamic monitoring). The optimized range of SVI is the range between the patient's baseline SVI rate and the SVI obteined after a 250 ml fluid bolus.
Time frame: Perioperative
Vasopressors
Total norepinephrine dose
Time frame: Perioperative
Fluids
Total amount of intraoperative fluids
Time frame: Perioperative
AFM effectiveness
The fraction of AFM software-prompted boluses that resulted in the desired increase in SVI
Time frame: Perioperative
PPCs
Incidence of postoperative pulmonary complications
Time frame: Up to one month from the day of surgery
Hospital costs
Analysis of hospital costs related to the adoption of AFM software in the clinical practice of our hospital
Time frame: At discharge to home
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Fondazione Policlinico Universitario Agostino Gemelli IRCCS