NCT04856618: PREMATRICS

Machine Learning-Based Prediction of Major Perioperative Allogeneic Blood Requirements in Cardiac Surgery

Completed Last updated 29 November 2022

What this trial tests

trial testing Massive Transfusion of Allogeneic Blood in Transfusion-dependent Anemia in 3,782 participants. Completed in 20 July 2022.

Timeline

16 June 2021

Primary endpoint
30 June 2021

20 July 2022

Quick facts

Lead sponsor	Kepler University Hospital
Status	Completed
Study type	OBSERVATIONAL
Enrollment	3,782
Start date	16 June 2021
Primary completion	30 June 2021
Estimated completion	20 July 2022
Sites	1 location across Austria

Drugs / interventions tested

• Massive Transfusion of Allogeneic Blood — full drug profile →

Conditions studied

• Transfusion-dependent Anemia — all drugs for Transfusion-dependent Anemia →

Sponsor

Kepler University Hospital

Who can join

Eligibility, any sex, with Transfusion-dependent Anemia. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Cardiac surgery is one of the clinical surgical specialties that carries a particularly high risk for patients to suffer from severe bleeding perioperatively and consequent anemia, which subsequently requires transfusion of allogeneic blood.

Although a surprisingly high number of patients in cardiac surgery do not require perioperative transfusions, it is primarily those patients who do require transfusion who are subsequently at risk for a worse outcome.

In recent years many studies have been published discussing measures that can assist physicians in avoiding the triad of anemia, bleeding, and transfusion in cardiac surgery. Within these publications, the implementation of Patient Blood Management (PBM) is advised. PBM is a set of measures aimed at improving patient outcome by reducing perioperative bleeding and thus preventing both anemia and bleeding.

The three pillars of this bundle are the preoperative preparation of anemic patients with iron, erythropoietin, folic acid and vitamin B12, the prevention of intraoperative blood loss and the reasonable indication for allogeneic transfusions.

Nevertheless, it must be mentioned that the implementation of at least part of these measures is laborious, and full implementation of the recommended bundle is therefore rarely achieved. As a consequence, the full potential of Patient Blood Management is not always realized. Unfortunately this means that transfusion of allogeneic blood cannot be prevented in many patients.

A small proportion of patients undergoing cardiac surgery requires a very large amount of allogeneic blood perioperatively. These patients are typically those with a particularly poor outcome. Massive transfusion of allogeneic blood in this situation is an indicator of complications and a cause of increased mortality.

Although cardiac surgeons and anesthesiologists believe they can assess which patients are at high risk for hemorrhage, recent publications indicate that there is an urgent need for adequate predictive methods. A variety of studies exist that attempt to predict perioperative transfusion requirements, but to date have been plagued by several limitations. Either the previous publications do not focus on the prediction of massive transfusion of allogeneic blood, i.e. administration of ten or more packed red blood cell units perioperatively, but on much lower transfusion volumes, have only low predictive strength to predict massive transfusion in daily clinical practice, or are hardly usable for true prediction because they use factors (features) that are not strictly present only in the preoperative phase.

If an accurate prediction model based on a few features could be created and those patients particularly at risk of massive transfusion of allogeneic blood could be identified, it would subsequently be possible to develop an adapted clinical pathway that would allow patient care to be improved and individualized interventions adapted to the situation to be implemented.

In the best case, an adapted care of patients would be possible, which is able to increase the acceptance for the use of even complex measures of patient blood management. This is especially true for measures such as preoperative preparation with iron and/or erythropoietin, the use of a cell saver, and a particularly careful surgical approach.

Even if it is difficult to apply all measures of patient blood management in all patients, it would be possible with an approach as described to identify those patients who would benefit most from individualized approaches.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

1. Machine learning-based prediction of massive perioperative allogeneic blood transfusion in cardiac surgery.
   Tschoellitsch T, Böck C, Mahečić TT, Hofmann A, et al · · 2022 · cited 13× · PMID 35852544 · DOI 10.1097/eja.0000000000001721
2. Big Data in cardiac surgery: real world and perspectives.
   Montisci A, Palmieri V, Vietri MT, Sala S, et al · · 2022 · cited 8× · PMID 36309702 · DOI 10.1186/s13019-022-02025-z