Transfusion-dependent AnemiaPRETRACONCT05466370
Prediction of Transfusion-Associated Complications
An observational study of Transfusion-dependent Anemia, run by Kepler University Hospital at 1 site in Austria.
Trial summary
Currently, about 350000 red blood cell concentrates are produced from blood donations in Austria every year. In addition to the main effect of replacing lost blood, red blood cell concentrates also have many undesirable effects - from blood group compatibilities, which are easily avoidable due to care, to… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Transfusion-dependent Anemia
- What is being tested?
- Transfusion of Allogeneic Blood
- How many people
- 3,366 participants
- Where
- 1 siteAustria
- Study dates
- 15 Jul 2022to 31 Jul 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
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 years and older
- All sexes
- Adult, Older adult
Study population: As described in the inclusion criteria.
Who may be able to join
- All adult patients that received at a blood transfusion the Kepler University Hospital in the period between 2016-10-31 to 2020-08-31.
Who cannot join
- None.
Trial locations and contacts
1 site in 1 country.
About this study
Currently, about 350000 red blood cell concentrates are produced from blood donations in Austria every year.
In addition to the main effect of replacing lost blood, red blood cell concentrates also have many undesirable effects - from blood group compatibilities, which are easily avoidable due to care, to storage-related side effects, to mostly intensive care problems as a result of massive transfusions, to system-wide effects such as TRALI, TACO and TRIM.
Read more
Before being administered to patients, red blood cell concentrates undergo an extensive quality assurance process in which a large number of parameters are collected. Prior to use on patients, for example, bedside tests and tests for further incompatibilities with a blood sample from the intended patient are performed. With the implementation of Patient Blood Management (PBM) in recent years, the use of red cell concentrates has become more targeted - the number of transfusions is decreasing in most developed countries. However, it is still possible to suffer transfusion-related adverse events (TRAE). Thus, active research activity to reduce these TRAEs continues to be called for.
To date, however, it is not known which patients experience transfusion-related adverse events. Despite the broad measures of hemovigilance and pre-transfusion testing, it is still not possible to predict which individual patient will respond to a transfusion with a typical adverse event such as hypotension, hemolysis, renal failure, or TRALI. It seems understandable that characteristics of the patient as well as characteristics of the administered unit could play a role for this. In particular, it is conceivable that a combination of characteristics of the blood unit and characteristics of the patient could determine a complication in the course of administration. For this reason, it seems attractive to use artificial intelligence and machine learning methods to predict any complications.
- Conditions
- Transfusion-dependent Anemia
- Being tested
- Transfusion of Allogeneic Blood
- Keywords
- Artificial Intelligence, Machine Learning, Transfusion, Complications
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Transfusion of Allogeneic BloodBiological
Transfusion of Allogeneic Blood
| Study group | Role | What they receive |
|---|---|---|
| AKI | Acute Kidney Injury Receives: Biological: Transfusion of Allogeneic Blood | |
| ARF | Acute Respiratory Failure Receives: Biological: Transfusion of Allogeneic Blood | |
| AKI and ARF | Acute Kidney Injury and Acute Respiratory Failure Receives: Biological: Transfusion of Allogeneic Blood | |
| no complication | no complication Receives: Biological: Transfusion of Allogeneic Blood |
What is being measured
The primary outcome is the main question the study is designed to answer.
AUROC for Classification of AKI
AUROC for Classification of AKI
Measured: 2016-10-31 to 2020-08-31
AUROC for Classification of ARF
AUROC for Classification of ARF
Measured: 2016-10-31 to 2020-08-31
AUROC for Classification of AKI and ARF
AUROC for Classification of AKI and ARF
Measured: 2016-10-31 to 2020-08-31
Secondary outcomes (2)
Confusion Matrix
Confusion Matrix Results: true positives, true negatives, false positive, false negatives and values calculated from these results.
Measured: 2016-10-31 to 2020-08-31
Descriptive Statistics
Descriptive Statistics (age in years, gender as male/female, blood group as A, B, 0, AB, hemoglobin in g/dl, platelets in count/microliter, leukocytes in cells per liter, CRP in mg/dl, creatinine in mg/dl, GFR ml/minute, glucose in mg/dl, potassium in mmol/l, TT, aPTT in seconds, ALT U/liter, paO2 mmHg, Rhesus type as positive or negative, height in cm, weight in kg, body temperature in kg, age of blood in days, cholesterine in mg/dl, systolic blood pressure in mmHg, diastolic blood pressure in mmHg)
This outcome measure will compare the individual feature (e. g. height in cm) in one group vs. the other. Significant difference will be described by p-value.
Measured: 2016-10-31 to 2020-08-31
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Jul 2022
- Study start15 Jul 2022
- Primary completion31 Jul 2022
- Study completion31 Jul 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Transfusion-dependent AnemiaStudies 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
- 3,366 participants (actual)
Sponsor and investigators
- Lead sponsor
- Kepler University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Thomas Tschoellitsch, MD, Principal investigator, Kepler University Hospital and Johannes Kepler University, Linz, Austria
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05466370
- Sponsor's protocol ID
- PRETRACO
- Acronym
- PRETRACO
- Status last verified
- Apr 2023
- First submitted
- 12 Jul 2022
- Last updated
- 26 Apr 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Tschoellitsch T, Moser P, Maletzky A, Seidl P, Bock C, Roland T, Ludwig H, Sussner S, Hochreiter S, Meier J. Potential Predictors for Deterioration of Renal Function After Transfusion. Anesth Analg. 2024 Mar 1;138(3):645-654. doi: 10.1213/ANE.0000000000006720. Epub 2024 Feb 16.
PubMed 38364244
Study at a glance
From the registry record, last updated by the sponsor on 26 Apr 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prediction of Transfusion-Associated Complications
- ClinicalTrials.gov ID
- NCT05466370
- Acronym / sponsor ID
- PRETRACO / PRETRACO
- Conditions
- Transfusion-dependent Anemia
- Keywords
- Artificial Intelligence, Machine Learning, Transfusion, Complications
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 3,366 participants (actual)
- Lead sponsor
- Kepler University HospitalUniversity, hospital or other
- Study start
- 15 Jul 2022 (actual)
- Primary completion
- 31 Jul 2022 (actual)
- Study completion
- 31 Jul 2022 (actual)
- First posted
- 20 Jul 2022 (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.
Currently, about 350000 red blood cell concentrates are produced from blood donations in Austria every year.
In addition to the main effect of replacing lost blood, red blood cell concentrates also have many undesirable effects - from blood group compatibilities, which are easily avoidable due to care, to storage-related side effects, to mostly intensive care problems as a result of massive transfusions, to system-wide effects such as TRALI, TACO and TRIM.
Before being administered to patients, red blood cell concentrates undergo an extensive quality assurance process in which a large number of parameters are collected. Prior to use on patients, for example, bedside tests and tests for further incompatibilities with a blood sample from the intended patient are performed. With the implementation of Patient Blood Management (PBM) in recent years, the use of red cell concentrates has become more targeted - the number of transfusions is decreasing in most developed countries. However, it is still possible to suffer transfusion-related adverse events (TRAE). Thus, active research activity to reduce these TRAEs continues to be called for.
To date, however, it is not known which patients experience transfusion-related adverse events. Despite the broad measures of hemovigilance and pre-transfusion testing, it is still not possible to predict which individual patient will respond to a transfusion with a typical adverse event such as hypotension, hemolysis, renal failure, or TRALI. It seems understandable that characteristics of the patient as well as characteristics of the administered unit could play a role for this. In particular, it is conceivable that a combination of characteristics of the blood unit and characteristics of the patient could determine a complication in the course of administration. For this reason, it seems attractive to use artificial intelligence and machine learning methods to predict any complications.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| AKI | – | Biological: Transfusion of Allogeneic BloodAcute Kidney Injury |
| ARF | – | Biological: Transfusion of Allogeneic BloodAcute Respiratory Failure |
| AKI and ARF | – | Biological: Transfusion of Allogeneic BloodAcute Kidney Injury and Acute Respiratory Failure |
| no complication | – | Biological: Transfusion of Allogeneic Bloodno complication |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- As described in the inclusion criteria.
Key inclusion criteria (1 listed)
- All adult patients that received at a blood transfusion the Kepler University Hospital in the period between 2016-10-31 to 2020-08-31.
Key exclusion criteria (1 listed)
- None.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Transfusion of Allogeneic BloodTransfusion of Allogeneic Blood | Biological | AKI, AKI and ARF, ARF, no complication |
Primary outcome
AUROC for Classification of AKI
Time frame: 2016-10-31 to 2020-08-31
AUROC for Classification of AKI
AUROC for Classification of ARF
Time frame: 2016-10-31 to 2020-08-31
AUROC for Classification of ARF
AUROC for Classification of AKI and ARF
Time frame: 2016-10-31 to 2020-08-31
AUROC for Classification of AKI and ARF
2 secondary outcomes
Confusion Matrix
Time frame: 2016-10-31 to 2020-08-31
Descriptive Statistics
Time frame: 2016-10-31 to 2020-08-31
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Apr 2023.
- Derived from this study: PubMed 38364244Tschoellitsch T, Moser P, Maletzky A, Seidl P, Bock C, Roland T, Ludwig H, Sussner S, Hochreiter S, Meier J. Potential Predictors for Deterioration of Renal Function After Transfusion. Anesth Analg. 2024 Mar 1;138(3):645-654. doi: 10.1213/ANE.0000000000006720. Epub 2024 Feb 16.
- Individual participant dataSharing planned: No
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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.
Thomas Tschoellitsch, MD principal investigator
Kepler University Hospital and Johannes Kepler University, Linz, Austria
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 Transfusion-dependent Anemia, 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 1 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: finished, as of the sponsor's last update on 26 Apr 2023. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
AUROC for Classification of AKI (time frame: 2016-10-31 to 2020-08-31). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05466370, which also lists 1 linked publication.
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 26 Apr 2023.