AIMC Topic: Blood Transfusion

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MIASurviveMTP: Machine learning for immediate assessment and survival prediction after massive transfusion protocol.

PloS one
Early triage of trauma patients requiring massive transfusion (MT) may help to marshal appropriate resources and improve treatment and outcome. Artificial intelligence (AI) and machine learning (ML) offer theoretical advantages compared to convention...

Machine learning for the prediction of blood transfusion risk during or after mitral valve surgery: a multicenter retrospective cohort study.

Scientific reports
This study aimed to identify the optimal prediction method and key preoperative variables for red blood cell (RBC) transfusion risk in patients undergoing mitral valve surgery. We conducted a retrospective study involving 1477 patients from eight lar...

Patient Blood Management in Pediatric Patients: Current Strategies and Future Perspectives.

Turkish journal of haematology : official journal of Turkish Society of Haematology
Patient blood management (PBM) is an evidence-based, multidisciplinary approach aimed at optimizing the care of patients who might require transfusion. While PBM has been widely adopted in adult practice, its application in pediatric settings remains...

Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive geriatric assessment.

BMC medical informatics and decision making
BACKGROUND: Lumbar spinal stenosis is one of the most common surgery-requiring conditions of the spine in the aged population. As elderly patients often present with multiple comorbidities and limited physiological reserve, individualized risk assess...

Machine learning-based prediction of bleeding risk in extracorporeal membrane oxygenation patients using transfusion as a surrogate marker.

Transfusion
BACKGROUND: The increasing use of extracorporeal membrane oxygenation (ECMO) has highlighted challenges in managing bleeding complications. Optimal transfusion strategies remain uncertain for this diverse patient group, necessitating accurate predict...

O blood usage trends in the pediatric population 2015-2019: A multi-institutional analysis.

Transfusion
BACKGROUND: In 2019, AABB released the bulletin "Recommendations on the Use of Group O Red Blood Cells" in which the recommendations about pediatric and neonatal blood transfusions were limited. Eight U.S. pediatric hospitals sought to determine tren...

Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.

BMC medical informatics and decision making
BACKGROUND: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management.

Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine.

Transfusion
BACKGROUND: Health data comprise data from different aspects of healthcare including administrative, digital health, and research-oriented data. Together, health data contribute to and inform healthcare operations, patient care, and research. Integra...

Assessment of machine learning classifiers for predicting intraoperative blood transfusion in non-cardiac surgery.

Transfusion clinique et biologique : journal de la Societe francaise de transfusion sanguine
BACKGROUND: This study aimed to develop a machine learning classifier for predicting intraoperative blood transfusion in non-cardiac surgeries.

A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

The journal of trauma and acute care surgery
BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly after injury. This has profound implications for resuscitation from hemorrhagic shock, as ATC is associated with increased risk for massive transfusi...