AI-driven tool to guide blood preparation before surgery
Official title: Intelligent Clinical Decision Support for Preoperative Blood Management: A Cluster-Randomized Clinical Trial
Run by Washington University School of Medicine · NCT07223853 · Data updated 2026-11-12
This tests an AI decision-support tool that helps clinicians decide which surgery patients should have blood prepared ahead of time to ensure timely transfusion for those who need it and avoid unnecessary preparation for those who don't.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 50 (estimated) |
| Sponsor | Washington University School of Medicine Academic / other |
| Locations | 1 site (St Louis, Missouri) |
| Status | Recruiting |
| Started | October 28, 2025 |
| Main results expected | December 1, 2026 |
| Study ends | January 1, 2027 |
| Registry record updated | August 27, 2026 |
| Trial ID | NCT07223853 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are patients scheduled for surgery in a main operating room at Barnes Jewish Hospital who are seen in an affiliated preoperative assessment clinic and have a valid S-PATH model prediction prior to that visit, and who are not pregnant and have no history of red cell alloantibodies.
✕Probably not a fit
Patients who are pregnant, have a history of red cell alloantibodies, are having procedures in remote operating rooms, or are not evaluated in the affiliated preoperative clinics (or lack a valid S-PATH prediction) are unlikely to benefit from this intervention.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
The trial compares an AI-based clinical decision support system (S-PATH) to usual care for perioperative blood ordering at a single academic center. Clinicians in affiliated preoperative assessment clinics will use model predictions to guide whether blood is prepared for patients scheduled in main operating rooms. The study will track outcomes such as how often blood is prepared, actual transfusion needs and timing, blood waste, costs, and patient safety. Implementation occurs at Barnes Jewish Hospital with patients who have a valid S-PATH prediction and meet inclusion criteria.
Why it matters
Potential benefit: If successful, the tool could reduce unnecessary blood preparation and waste while ensuring patients who need transfusions receive blood promptly.
How similar studies have gone: Retrospective and predictive-model studies have shown machine-learning methods can identify patients at risk of transfusion, but prospective implementations of AI decision support for perioperative blood ordering remain limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Clinician Level Exclusion Criteria: * Clinician (resident physician or advanced practice provider) who works at a preoperative assessment clinic Clinician Level Exclusion Criteria: * None Patient Inclusion Criteria: * Scheduled for surgery in one of the main operating room areas (non-remote) at Barnes Jewish Hospital * Evaluated in-person at one of the preoperative assessment clinics affiliated with BJC Healthcare * Have a valid S-PATH model prediction prior to their preoperative assessment clinic visit Patient Exclusion Criteria: * Pregnant * Presence or history of red cell alloantibodies
Where it's running
-
Washington University / Barnes Jewish Hospital
St Louis, Missouri, United States Recruiting
Study contacts
- Study coordinator: Sunny S Lou, MD, PhD
- Email: slou@wustl.edu
- Phone: 314-362-5000
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
-
How age affects germinal center responses after flu and rabies vaccines
Researchers will test how the immune system responds to flu and rabies vaccines in younger adults (18–40) and older adults (65+).
-
Cognitive Tasks and Models in a Large Online Sample
This study tests cognitive tasks and computational models in a large online group to see if these tools can help predict symptoms like hallucinations and delusions in the general population.
-
Can seven tasks help distinguish schizophrenia and schizoaffective disorder from healthy people
The study tests seven cognitive tasks to see if they can tell apart people with schizophrenia or schizoaffective disorder from healthy adults and predict symptoms like hallucinations and delusions.
-
Online perioperative education to support head and neck cancer patients and their caregivers
This trial tests a digital education program called CareOrbit to see if it improves understanding, satisfaction, and outcomes for adults with head and neck cancer undergoing reconstructive surgery or laryngectomy.
-
Somatostatin analogues after PRRT for nonfunctional neuroendocrine tumors
This study tests whether continuing somatostatin analogues after PRRT helps patients with nonfunctional neuroendocrine tumors compared with just observation.
-
ICG with near-infrared imaging to visualize head and neck cancer during surgery
This study tests whether first-window indocyanine green fluorescence seen during surgery matches the cancer extent seen on pathology in patients with head and neck squamous cell carcinoma.
How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.