NCT06870851

Predicting Platelet Count From Viscoelastic Testing

Machine Learning Based Prediction of Platelet Concentration From ROTEM Measurements

• Status: Active Not Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 2,500 (estimated)
• Sponsor: Kepler University Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 100 Years
• Healthy volunteers: —

Summary

Viscoelastic testing is a highly recommended cornerstone of modern coagulation medicine, reducing transfusion needs. A disadvantage of viscoelastic tests is the impossibility of making a definitive statement about the platelet count. Therefore, the aim of this retrospective observational study is, on the one hand, to predict the platelet count based on standard ROTEM parameters with the help of several machine learning methods and, on the other hand, to detect a low platelet count ( \<100000 ml-1 and \< 50000 ml-1).

Conditions

• Thrombocytopenia

Timeline

• Start date: 2024-10-01
• Primary completion: 2025-04-01
• Completion: 2025-12-01
• First posted: 2025-03-11
• Last updated: 2025-03-11

Locations

1 site across 1 country: Austria