Using gut blood flow measurements to predict feeding intolerance in critically ill adults

Study on the Predictive Value of Gastrointestinal Blood Flow for Enteral Nutrition Intolerance in Critically Ill Patients

This study will test whether bedside ultrasound measurements of gastrointestinal blood flow can help predict which critically ill adults receiving enteral nutrition will develop feeding intolerance.

Quick facts

• Study type: Observational
• Enrollment: 500 (estimated)
• Ages: 18 Years and up
• Sex: All
• Sponsor: Ruijin Hospital (Academic / other)
• Locations: 1 site (Shanghai)
• Trial ID: NCT07521111 on ClinicalTrials.gov

What this trial studies

This is a prospective observational cohort at Ruijin Hospital where researchers will perform bedside point-of-care ultrasound on ICU patients at admission and on Day 1, Day 4, and Day 7 of enteral nutrition. Ultrasound measurements will include vessel diameters, time-averaged maximum velocity, calculated blood flow, and VExUS scores for the celiac artery, superior mesenteric artery, portal vein, hepatic vein, and inferior vena cava. The team will use these hemodynamic parameters, alongside routine clinical indicators, to build and compare three predictive models using machine learning methods. The goal is to determine whether adding blood flow data improves early prediction of enteral nutrition intolerance compared with clinical data alone.

Who should consider this trial

Good fit: Adults (over 18) admitted to the ICU who are expected to require enteral nutrition for more than 7 days and who (or whose legal representatives) can provide informed consent are ideal candidates.

Not a fit: Patients with recent major gastrointestinal surgery, contraindications to abdominal POCUS, severe baseline gastrointestinal disease, severe peripheral vascular or valvular heart disease, or who are pregnant or lactating are excluded and would not benefit from this protocol.

Why it matters

Potential benefit: If successful, the approach could allow clinicians to identify patients at high risk of feeding intolerance earlier and personalize nutrition plans to reduce interruptions and complications.

How similar studies have performed: Prior research links gut perfusion and hemodynamics to gastrointestinal dysfunction and POCUS is used for bedside hemodynamic assessment, but using serial GI blood flow measurements plus machine learning to predict enteral nutrition intolerance is largely novel.

Eligibility criteria

Inclusion Criteria:

* Age \> 18 years old.
* Expected duration of enteral nutrition support \> 7 days.
* Patients or their legal representatives sign the informed consent form.

Exclusion Criteria:

* History of major gastrointestinal surgery such as subtotal gastrectomy and gastrointestinal anastomosis.
* Contraindications to abdominal point-of-care ultrasound (POCUS) examination (e.g., recent large-area abdominal burns, dressings blocking movement, open abdomen).
* Presence of severe gastrointestinal diseases such as gastroparesis, intestinal obstruction, digestive tract perforation, and gastrointestinal bleeding upon admission.
* Presence of severe peripheral vascular disease or valvular heart disease.
* Pregnant or lactating women.

Where this trial is running

Shanghai

• Ruijin Hospital, Shanghai Jiao Tong University School of Medicine — Shanghai, China (Recruiting)

Study contacts

• Study coordinator: Weiqing Zhang, Ph.D

Conditions Critical Illness; Enteral Nutrition Intolerance; Enteral Nutrition Feeding; Prediction Models; Machine Learning