Predicting Platelet Count From Viscoelastic Testing

NCT06870851 | Active Not Recruiting

• 1 other identifier: plateletprediction
• Study Type: observational
• Target: 2,500
• Locations: 1 country
• Sites: 1

Brief 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

Outcome Measures

Primary Outcomes (1)

• Predicition of platelet conentration from ROTEM measurements using machine learning

  Several machine learning techniques for the prediction of the platelet concentration from ROTEM parameters (regression approach), namely linear regression, Random Forest, neural network, gradient boosting machine (GBM) and adaptive boosting (ADA) will be assessed. Describing the quality of these prediction models, the mean square error (MSE), the root of the mean of the square of errors(RMSE), the mean absolute error (MAE), and the root mean squared logarithmic error (RMSLE), and the coefficient of determination (R2) will be used.

  Obtained ROTEM analyses are the baseline at all four centres and patients will be included if platelets were determined concomitantly within three hours on the same day.

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

surgical patients in the operating room and the intensive care of participating centers

You may qualify if:

• ROTEM measurement and platelet count measurement within 3 hours.

You may not qualify if:

• under 18 Years
• more than 3 hours between ROTEM and platelet count measurement

Sponsors & Collaborators

• Kepler University Hospital: lead

Study Sites (1)

Universitätsklinik für Anästhesie und Intensivmedizin

Linz, Austria

Location

MeSH Terms

Conditions

Thrombocytopenia

Condition Hierarchy (Ancestors)

Blood Platelet Disorders; Hematologic Diseases; Hemic and Lymphatic Diseases; Cytopenia

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 3, 2025
• First Posted: March 11, 2025
• Study Start: October 1, 2024
• Primary Completion: April 1, 2025
• Study Completion: December 1, 2025
• Last Updated: March 11, 2025

Record last verified: 2025-03

Locations

AU (1)