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ID07099664

Using Suprasternal Ultrasound to Measure Aortic Time-Velocity Integral VTI for Predicting Fluid Needs in Children Undergoing Surgery

Led by University Hospital, Lille · Updated on 2026-05-22

90

Participants Needed

1

Research Sites

N/A

Total Duration

AI-Summary

What this Trial Is About

Researchers are investigating whether measuring the variation in the aortic Time-velocity Integral VTI via suprasternal ultrasound can predict preload dependence in children undergoing surgery. This study focuses on pediatric patients under 18 years old who require general anesthesia for various procedures. The aim is to improve fluid management, as fluid overload after major surgery is linked to increased risks and complications, and current methods to predict preload dependence in pediatric anesthesia are limited. The study involves measuring the aortic VTI and cardiac output using a suprasternal Doppler probe after general anesthesia induction and fasting compensation. Patients cardiac output changes are assessed after receiving a fluid volume of 10 mlkg of crystalloid solution. The study examines whether differences in VTI variation correlate with patients who respond to volume expansion with a significant increase in cardiac output. Participants will undergo measurements of aortic VTI variation before surgery, after induction, and after fasting compensation, but before the surgical incision. Researchers will evaluate the proportion of patients suitable for suprasternal aortic measurements, determine optimal VTI variation thresholds for identifying preload dependence, and study correlations between fasting duration and preload dependence. The study is observational, with participant involvement focusing on ultrasound measurements and monitoring during anesthesia. Participation lasts through the perioperative period with no long-term follow-up specified.

CONDITIONS

Brief Title

Use of the Aortic Time-velocity Integral Via Suprasternal Ultrasound to Search Preload Dependence in Paediatric Surgery : Kid's Fluid Management (FM)

Research Team

M

Martin DUBERNET, Dr

J

Julien COROUGE, Dr

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