Hemodynamic

After major surgery, fluid overload is associated with an increase of morbidity and mortality. Fluid administration should therefore be given wisely. However, there is a paucity of monitor to predict preload dependence in paediatric anaesthesia. The aim of this study is to determine if VTI variation, measured through the suprasternal window, with a cardiac doppler probe, can predict preload dependence. Indeed, cardiac probe are present in most operating room and suprasternal window is reachable in most surgical case, which should allow VTI monitoring for the vast majority of our patient.

The goal of this prospective, randomized, single-blinded is to learn if there is an ideal sedation protocol in cataract surgery in adults. The main questions it aims to answer are: * Does the combination of Dexmedetomidine and Propofol affect significantly Ramsay sedation scale, compared to Dexmedetomidine and compared to Propofol? * How does each sedation protocol affect hemodynamics? (Heart rate and blood pressure) * Are respiratory events more common in a certain group? * Is the surgeon's satisfaction similar among groups? * Are adverse effects (bradycardia, hypotension, nausea) more common in a certain group? Researchers will compare 3 sedation protocols : Dexmedetomidine versus Propofol versus the combination of these 2 drugs and to see if one protocol is overall superior to the others. Fentanyl will also be used in all 3 sedation protocols. Participants will : * Receive one of these three protocols * Be operated for one or both eyes * Monitored during the whole surgery and in the recovery room * Be evaluated by the Ramsay sedation scale by a trained Anesthesiologist or CRNA during surgery and in the recovery room Surgeons will be asked about how much they were satisfied.

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.

Intracranial atherosclerotic stenosis (ICAS) carries substantial stroke risk despite optimal medical treatment. Current risk stratification relies primarily on stenosis severity, but novel hemodynamic markers may improve prediction. In this multiple prospective registry study we aim to investigate whether regional hemodynamics, measured by a novel Magnetic resonance imaging-derived Pressure Ratio (MPR) technique, are associated with stroke risk in ICAS.

We will enroll patients scheduled for abdominal aortic aneurysm repair and divide in two groups; in the control group the hemodynamic optimization will be made based on standard cardiovascular parameters showed in the Hemosphere platform. In the interventional group the hemodynamic optimization will be made based on the hypotension prediction index.

Fluid responsiveness is a critical determinant guiding fluid therapy in critically ill patients. However, excessive fluid administration can result in fluid overload, leading to venous congestion and worse clinical outcomes. Venous congestion, a marker of impaired fluid clearance, is increasingly recognized as a significant contributor to poor prognosis. Previous studies have demonstrated the coexistence of fluid responsiveness and venous congestion in critically ill patients. Notably, these studies were limited by the absence of fluid challenge-the gold standard for assessing fluid responsiveness-leaving the dynamic relationship between fluid responsiveness and venous congestion incompletely understood. This study aims to investigate the interplay and temporal evolution of fluid responsiveness and venous congestion following a standardized fluid challenge in critically ill patients.

Compare the incidence of hypotension during the propofol-induced period between the internal jugular vein variability-guided fluid infusion group and the conventional fluid infusion group through a fluid infusion experiment before anesthesia induction, so as to evaluate the feasibility of using the internal jugular vein variability under deep inspiration to guide preoperative fluid infusion.