Validation of a Red Blood Cell Transfusion Prediction Model in a Low Transfusion Rate Population. (TRACK-TCT)

External Validation of the TRACK Allogeneic Transfusion Model in a Dutch Adult Cardiac Surgery Population, and the Effect on Discriminative Ability When Adding Anti-platelet Therapy

The transfusion risk and clinical knowledge (TRACK) allogeneic blood transfusion prediction model was developed more than ten years ago and demonstrated good discriminative ability in patients with increased risk for allogeneic blood transfusion in an all Italian population. At the time of derivation, dual anti-platelet medication was suggested in the treatment of acute coronary syndrome, but not yet fully implemented.

The aim of this study is to externally validate the TRACK blood transfusion prediction model in the cardiac surgery population of Medisch Spectrum Twente Thoraxcentrum Twente. Additionally, the impact of adding the preoperative use of dual anti-platelet medication, as additional predictive factor, to the TRACK blood transfusion prediction model will be investigated.

Study Overview

• Status: Completed
• Conditions: Platelet Aggregation; Blood Transfusion
• Intervention / Treatment: Other: TRACK-TCT

Detailed Description

Cardiothoracic surgery is associated with increased perioperative blood loss and the need for allogeneic blood and blood product transfusions. This is due to three distinct factors, the invasive nature of the surgical procedures, the need for high dose anti-coagulation during extracorporeal circulation, and lastly the exposure of blood to the internal surface area of the heart-lung machine. Most cardiac patients use anti-platelet therapy before and after surgery, making hemostasis management in this specific patient population even more complex. European guidelines recommend administering anti-platelet therapy using Aspirin in combination with platelet receptor inhibitors such as Clopidogrel, Prasugrel or Ticagrelor, also known as dual anti-platelet therapy in patients with acute coronary syndrome.

Making distinct decisions regarding individual patient hemostasis management remains challenging. Decision making supported by prediction models, such as, EuroSCORE is well established in the cardiac surgery population. A few models pertaining specifically to allogeneic blood transfusion have been created and externally validated. Most of these prediction models perform reasonably well, predicting red blood cell transfusions with seventy-eighty percent accuracy, depending on the model and number of prediction factors used. Some are even excellent for predicting the chance of severe post-operative bleeding. As the transfusion of even one unit of allogeneic blood transfusion impacts mortality, the choice for the best feasible prediction model for routine clinical practice that reflects daily practice, uses a limited number of predictive factors, has a predictive capacity of more than seventy percent, and discriminates between risk groups for allogeneic blood transfusion is desirable.

Transfusion Risk and Clinical Knowledge (TRACK) model validation and optimization The TRACK model was developed more than ten years ago in an Italian adult cardiac surgery population. The decision to validate the TRACK model was based on its simplicity and relatively high predictive capacity, in comparison to other models with higher numbers of complex factors. This model has an allogeneic blood transfusion predictive capacity of seventy-two percent and uses a point system to divide patients into different risk groups, according to the total number of points allocated. During the derivation of this model, dual anti-platelet medication was included, but no significant association was found. In the twelve years since development, the popularity of dual anti-platelet medication used in acute coronary syndrome patients has significantly increased and its association with post-operative bleeding and allogeneic blood transfusion has been suggested.

Recent studies suggest that platelet activity may play a significant role in the prediction of post-operative bleeding, and one research group found that adding platelet activity to the CRUSADE score showed a significant increase in predicting risk of major bleeding in acute coronary syndrome patients. A re-evaluation of the association between dual anti-platelet (DAPT) and allogeneic blood transfusion is necessary. This will be done by the addition of DAPT as an extra predictive factor to the TRACK model, during external validation.

The negative association between mortality and transfusion products is well known. In addition, the related significant increase in hospital costs makes better perioperative hemostasis management crucial. Identifying cardiac surgery patients at risk for blood transfusion pre-operatively would aid clinicians in modifying the perioperative approach with goal the prevention of unnecessary allogeneic blood transfusion and the associated complications thereof.

Validating this model might aid clinicians in reducing allogeneic blood transfusions, transfusion complications and associated costs. Ultimately this might aid for development of patient specific transfusion strategies and new blood management protocols.

The aim of this study is to externally validate the TRACK blood transfusion prediction model in the cardiac surgery population of Medisch Spectrum Twente Thoraxcentrum Twente. Additionally, the impact of adding the preoperative use of dual anti-platelet medication will be studied, as additional predictive factor, to the TRACK blood transfusion prediction model.

• Study Type: Observational
• Enrollment (Actual): 6428

Contacts and Locations

Study Locations

• Netherlands
  • Overijssel
    • Enschede, Overijssel, Netherlands, 7500KA
      • Thoraxcentrum Twente

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The study population will consist of adult patients, 18 years and older, who underwent any cardiac surgery with the use of a heart lung machine, between 1 January 2016 and 31 December 2021 in the Thoraxcentrum Twente, Medisch Spectrum Twente, Enschede.

Description

Inclusion Criteria:

• Patients receiving on-pump cardiac surgery

Exclusion Criteria:

• Patients who opted out for reuse of their data for scientific purposes

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
TRACK; External validation of TRACK prediction model with 5 variables: age, weight, sex, pre-op HCT, Type of surgery.
TRACK-TCT; New model development with 6 variables. 5 From the TRACK model: age, weight, sex, pre-op HCT, Type of surgery. A sixth variable will be added i.e.: pre-operative P2Y12 drug use	Other: TRACK-TCT; An extra variable will be added to an existing prediction model. It is hypothesized that the predictive ability will improve and that better distinction could be made between patients with an increased risk for receiving blood transfusions.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
External validation TRACK blood prediction Model (TRACK)	Does adding P2Y12 inhibitors as extra variable to the TRACK model after validation improve the predictive capacity? This will be done by validation of the TRACK model in the cardiac surgery population of TCT by calculating the discriminative ability. The change in discriminative ability, after correction for optimism, when the pre-operative use of P2Y12 inhibitors is added as extra variable will be assessed and the net improvement in reclassification will be calculated.	1 year
Evaluation of the change in predictive capacity when adding P2Y12 as extra variable (TRACK-TCT)	Does adding P2Y12 inhibitors as extra variable to the TRACK model after validation improve the predictive capacity? This will be done by validation of the TRACK model in the cardiac surgery population of TCT by calculating the discriminative ability. The change in discriminative ability, after correction for optimism, when the pre-operative use of P2Y12 inhibitors is added as extra variable will be assessed and the net improvement in reclassification will be calculated.	1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Male vs Female	How does the performance of the model change in an all-male and all-female population.	1 year
Post operative complication in patients that received a blood transfusion	Does allogeneic blood transfusion increase the risk of post-operative complications or thromboembolic events?	1 year
Mortality difference in patients that received a blood transfusion	What is the difference in 30-day mortality between patients receiving allogeneic blood transfusions and patients that does not?	1 year

Collaborators and Investigators

• Sponsor: Medisch Spectrum Twente
• Investigators: Principal Investigator: Frank R Halfwerk, MD PhD, Medisch Spectrum Twente

Publications and helpful links

General Publications

• Ranucci M, Bozzetti G, Ditta A, Cotza M, Carboni G, Ballotta A. Surgical reexploration after cardiac operations: why a worse outcome? Ann Thorac Surg. 2008 Nov;86(5):1557-62. doi: 10.1016/j.athoracsur.2008.07.114.
• Task Force on Patient Blood Management for Adult Cardiac Surgery of the European Association for Cardio-Thoracic Surgery (EACTS) and the European Association of Cardiothoracic Anaesthesiology (EACTA); Boer C, Meesters MI, Milojevic M, Benedetto U, Bolliger D, von Heymann C, Jeppsson A, Koster A, Osnabrugge RL, Ranucci M, Ravn HB, Vonk ABA, Wahba A, Pagano D. 2017 EACTS/EACTA Guidelines on patient blood management for adult cardiac surgery. J Cardiothorac Vasc Anesth. 2018 Feb;32(1):88-120. doi: 10.1053/j.jvca.2017.06.026. Epub 2017 Sep 30. No abstract available.
• Raphael J, Mazer CD, Subramani S, Schroeder A, Abdalla M, Ferreira R, Roman PE, Patel N, Welsby I, Greilich PE, Harvey R, Ranucci M, Heller LB, Boer C, Wilkey A, Hill SE, Nuttall GA, Palvadi RR, Patel PA, Wilkey B, Gaitan B, Hill SS, Kwak J, Klick J, Bollen BA, Shore-Lesserson L, Abernathy J, Schwann N, Lau WT. Society of Cardiovascular Anesthesiologists Clinical Practice Improvement Advisory for Management of Perioperative Bleeding and Hemostasis in Cardiac Surgery Patients. Anesth Analg. 2019 Nov;129(5):1209-1221. doi: 10.1213/ANE.0000000000004355. Erratum In: Anesth Analg. 2020 Feb;130(2):e44.
• Gorlinger K, Shore-Lesserson L, Dirkmann D, Hanke AA, Rahe-Meyer N, Tanaka KA. Management of hemorrhage in cardiothoracic surgery. J Cardiothorac Vasc Anesth. 2013 Aug;27(4 Suppl):S20-34. doi: 10.1053/j.jvca.2013.05.014.
• Karkouti K, Wijeysundera DN, Yau TM, Beattie WS, Abdelnaem E, McCluskey SA, Ghannam M, Yeo E, Djaiani G, Karski J. The independent association of massive blood loss with mortality in cardiac surgery. Transfusion. 2004 Oct;44(10):1453-62. doi: 10.1111/j.1537-2995.2004.04144.x.
• Khan B, Islam MU, Ahmad I, Rehman MU. Modifiable Risk Factors associated with Post-Operative Bleeding and transfusion requirements in Cardiac Surgery. Pak J Med Sci. 2022 Mar-Apr;38(4Part-II):855-861. doi: 10.12669/pjms.38.4.5685.

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2022
• Primary Completion (Actual): June 30, 2023
• Study Completion (Actual): January 1, 2024

Study Registration Dates

• First Submitted: October 12, 2022
• First Submitted That Met QC Criteria: October 12, 2022
• First Posted (Actual): October 14, 2022

Study Record Updates

• Last Update Posted (Actual): March 7, 2024
• Last Update Submitted That Met QC Criteria: March 5, 2024
• Last Verified: March 1, 2024

More Information

Terms related to this study

• Keywords: External validation; Prediction Model; Blood transfusion; P2Y12 Receptor Inhibitor
• Other Study ID Numbers: Protocol_TRACK-TCT_v 2.0

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: The data that support the findings of this study will be made openly available in a repository according to FAIR (Findable, Accessible, Interoperable, Reproducible) guidelines.
• IPD Sharing Time Frame: During this year (2024)
• IPD Sharing Supporting Information Type: ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No