VExUS-ED: Early venous congestion is associated with clinical fluid overload in patients with sepsis
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Initial fluid resuscitation is central to sepsis management, yet excessive fluids may exceed a patient's fluid tolerance, increasing the risk of fluid overload and organ dysfunction. The Venous Excess Ultrasound (VExUS) score allows noninvasive bedside assessment of venous congestion, but its prevalence and predictive value in the emergency department (ED) are unclear. METHODS: We analyzed prospectively collected data from the Acutelines data-biobank (University Medical Center Groningen, Netherlands). Adults with suspected sepsis requiring initial fluid resuscitation underwent VExUS assessments, including inferior vena cava and organ-specific Doppler measurements, within three hours of ED admission. The primary outcome was clinical fluid overload within 72 h, defined as positive fluid balance plus ≥10% weight gain, pulmonary edema on imaging, or loop diuretic use. Associations were analyzed using logistic and mixed-effects regression. RESULTS: Among 103 patients, 34 (33%) developed clinical fluid overload. At ED admission, 75% had VExUS grade 0, 22% grade 1, and 3% grade ≥ 2. At baseline, VExUS>0 and abnormal hepatic venous Doppler flow were associated with fluid overload within 72 h (aOR 3.66, 95% CI 1.23-11.55; p = 0.022 and 4.20, 95% CI 1.21-16.38; p = 0.028, respectively). In repeated-measures analyses, VExUS>0 and abnormal intrarenal venous Doppler flow were associated with next-day fluid overload. CONCLUSION: In patients with suspected sepsis, mild venous congestion was independently associated with clinical fluid overload within 72 h. Abnormal hepatic and intrarenal flow patterns may provide additional information on venous congestion. Early, serial VExUS assessments may detect fluid intolerance and support individualized fluid management.
Source: Journal of Critical Care
Authors: Sanne Ter Horst, Jochem van Oosten, Ranek Laros, Bashar Sukkar, Jildou van Everdink, Alessandra di Mauro, Adyaan Alawi, Willemijn de Vries, Michèle ter Voert, Ilektra Koliaki, Amber Slot, Donna van der Wiel, Jingyi Lu, Lucia Colavolpe, Deborah Blanca, Hjalmar R. Bouma, Jan C. ter Maaten, Tycho J. Olgers
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,610
OpenAlex ID: W7135180478
