Evaluating Ultrasound of the Inferior Vena Cava and Other Ultrasound Methods to Diagnose Acute Pulmonary Edema in Adults with Sudden Breathing Trouble in the Emergency Department
Led by Università degli Studi del Piemonte Orientale Amedeo Avogadro · Updated on 2026-01-08
200
Participants Needed
1
Research Sites
N/A
Total Duration
AI-Summary
What this Trial Is About
Researchers are evaluating the use of point-of-care ultrasound POCUS to diagnose acute pulmonary edema in adults who come to the emergency department with sudden breathing difficulties and respiratory failure. The study focuses on measuring the respiratory variation in the diameter of the inferior vena cava IVC to identify heart-related fluid buildup in the lungs. It also explores whether combining IVC ultrasound with lung and cardiac ultrasound, plus clinical and lab data like hemoglobin and plasma protein changes, improves diagnosis and risk assessment.
This is a single-center, prospective observational study enrolling adults aged 18 and older who present with acute dyspnea and respiratory failure. Participants will receive standard clinical evaluations including lab tests and chest imaging, along with ultrasound assessments at admission, one hour later, and when possible, 24 to 48 hours afterward. The study does not involve any experimental treatments but observes and records diagnostic data during routine care.
Participants will undergo multiple assessments, including ultrasound scans of the IVC, lungs, and heart, clinical evaluations, and laboratory tests. Researchers will measure the accuracy of IVC diameter changes at admission and after one hour in diagnosing pulmonary edema. They will also analyze early changes in hemoglobin and plasma proteins as indicators of fluid shifts. Clinical outcomes such as hospital admission, need for increased care, and mortality will be tracked, with the overall study period lasting until November 2028.
CONDITIONS
Brief Title
Acute DYSPnea in the Emergency Department: Diagnostic Value of Point-of-care UltraSound
Research Team
F
Francesco Gavelli, MD, PhD
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Università degli Studi del Piemonte Orientale Amedeo Avogadro
Lead Sponsor
Who Can Participate
Age: 18Years +
All Genders
Eligibility Criteria
You may qualify if you...
Adults aged 518 years
Presenting to the emergency department with acute dyspnea and acute respiratory failure, defined by at least one of the following: PaO8 < 60 mmHg on room air, oxygen saturation < 90% on room air, or PaO8/FiO8 ratio < 300
Able to provide written informed consent or eligible for deferred consent according to local rules
Undergoing standard diagnostic evaluation including lab tests and chest imaging as routine care
You will not qualify if you...
Refusal to provide informed consent or consent by legal representative when applicable
Inadequate or technically insufficient ultrasound assessment
Acute respiratory failure caused by chest trauma
Cardiac arrest at presentation or during emergency department stabilization
Need for invasive mechanical ventilation during initial emergency stabilization
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person) at emergency department admission
Diagnostic Evaluation
Duration - Up to 2 days
Participants undergo standardized clinical assessment, laboratory testing, chest imaging as per routine care, and multimodal point-of-care ultrasound evaluation at emergency department admission, after 1 hour, and at 24-48 hours when clinically feasible.
3 assessments at emergency department: baseline, after 1 hour, and at 24-48 hours
Long-term Monitoring
Duration - Duration of hospital stay as applicable
Clinical outcomes including need for hospitalization, escalation of care, and in-hospital mortality are recorded.
Follow-up assessments during hospital stay depending on clinical course
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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Published Research Related To This Trial
Decrease of haemoconcentration reliably detects hydrostatic pulmonary oedema in dyspnoeic patients in the emergency department - a machine learning approach.
Francesco Gavelli, Luigi Mario Castello, Xavier Monnet...