ThrombocytopeniaNCT06870851
Predicting Platelet Count From Viscoelastic Testing
An observational study of Thrombocytopenia, run by Kepler University Hospital at 1 site in Austria.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- Thrombocytopenia
- How many people
- 2,500 participants
- Where
- 1 siteAustria
- Study dates
- 1 Oct 2024to Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 100 years
- All sexes
- Adult, Older adult
Study population: surgical patients in the operating room and the intensive care of participating centers
Who may be able to join
- ROTEM measurement and platelet count measurement within 3 hours.
Who cannot join
- under 18 Years
- more than 3 hours between ROTEM and platelet count measurement
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Machine Learning Based Prediction of Platelet Concentration From ROTEM Measurements
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
- Medical subject headings
- Thrombocytopenia
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Mar 2025
- Study start1 Oct 2024
- Primary completionApr 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for ThrombocytopeniaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 2,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Kepler University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06870851
- Sponsor's protocol ID
- plateletprediction
- Status last verified
- Mar 2025
- First submitted
- 3 Mar 2025
- Last updated
- 11 Mar 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 Mar 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning Based Prediction of Platelet Concentration From ROTEM Measurements
- ClinicalTrials.gov ID
- NCT06870851
- Acronym / sponsor ID
- plateletprediction
- Conditions
- Thrombocytopenia
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 2,500 participants (estimated)
- Lead sponsor
- Kepler University HospitalUniversity, hospital or other
- Study start
- 1 Oct 2024 (actual)
- Primary completion
- Apr 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 11 Mar 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- surgical patients in the operating room and the intensive care of participating centers
Key inclusion criteria (1 listed)
- ROTEM measurement and platelet count measurement within 3 hours.
Key exclusion criteria (2 listed)
- under 18 Years
- more than 3 hours between ROTEM and platelet count measurement
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Predicition of platelet conentration from ROTEM measurements using machine learning
Time frame: 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.
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Mar 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Thrombocytopenia, run by Kepler University Hospital at 1 site in Austria.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 11 Mar 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Austria. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Predicition of platelet conentration from ROTEM measurements using machine learning (time frame: 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.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Mar 2025.