Using machine learning and ultrasound to predict complications after major gastrointestinal surgery

Prediction of Complications After Major Gastrointestinal Surgery With Machine Learning and Point of Care Ultrasound: an Observational Cohort Study.

Observational Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) · NCT06166719

This study is testing if using machine learning and ultrasound can help doctors predict complications after major gut surgery in adults, so they can give better care and manage fluids more effectively.

Quick facts

Study typeObservational
Enrollment200 (estimated)
Ages18 Years and up
SexAll
SponsorAcademisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) Academic / other
Locations1 site (Amsterdam, Noord-Holland)
Trial IDNCT06166719 on ClinicalTrials.gov

What this trial studies

This observational study focuses on adult patients undergoing major gastrointestinal surgery to predict potential complications such as low blood pressure and the need for ICU admission. It employs a machine learning framework that analyzes continuous blood pressure measurements and integrates point of care ultrasound data to assess fluid therapy responses. The goal is to identify complications earlier and provide guidance on fluid administration strategies. The study will also explore the activity of the renin-angiotensin-aldosterone system following liver resection.

Who should consider this trial

Good fit: Ideal candidates are adults aged 18 and older scheduled for elective major gastrointestinal surgeries like esophagectomy, gastrectomy, pancreatomy, or major liver resection.

Not a fit: Patients with major cardiac shunts, dialysis shunts, or those for whom point of care ultrasound assessments are unreliable may not benefit from this study.

Why it matters

Potential benefit: If successful, this approach could lead to earlier detection of complications and improved management of fluid therapy in surgical patients.

How similar studies have performed: Other studies have shown promise in using machine learning and ultrasound for predicting surgical complications, but this specific approach is novel.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* ≥18 years of age.
* elective major gastrointestinal surgery: esophagectomy, gastrectomy, pancreatomy or major liver resection (3 segments or more).

Exclusion Criteria:

* no informed consent
* Patients with major cardiac shunts
* Patients with dialysis shunts or peritoneal dialysis
* Patients in whom POCUS is not possible or assessment of fluid status is unreliable e.g. BMI\> 40, pulmonary fibrosis.

Where this trial is running

Amsterdam, Noord-Holland

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Surgery-ComplicationsOverload FluidIntensive care unitGastro-intestinal surgeryPrediction
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.