Transfusion in critical care: Past, present and future

Shah, Akshay; Oczkowski, Simon; Aubron, Cécile; Vlaar, Alexander P.J.; Dionne, Joanna C.; Force, Esicm Transfusion Task

doi:10.1111/tme.12738

Cited by 7 publications

(4 citation statements)

References 136 publications

(215 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the critical Hb level is reached, compensatory physiological responses to anemia are unable to maintain tissue oxygenation [42]. A further decline in Hb concentration will, therefore, lead to a decrease in the delivery of oxygen and oxygen consumption [43]. It has been suggested that the critical Hb level is not only patient-and disease-dependent but can also vary over time, as the compensatory responses to anemia may be affected by different comorbidities.…”

Section: Discussionmentioning

confidence: 99%

Measuring Mitochondrial Oxygen Tension during Red Blood Cell Transfusion in Chronic Anemia Patients: A Pilot Study

et al. 2023

View full text Add to dashboard Cite

In light of the associated risks, the question has been raised whether the decision to give a blood transfusion should solely be based on the hemoglobin level. As mitochondria are the final destination of oxygen transport, mitochondrial parameters are suggested to be of added value. The aims of this pilot study were to investigate the effect of a red blood cell transfusion on mitochondrial oxygenation as measured by the COMET device in chronic anemia patients and to explore the clinical usability of the COMET monitor in blood transfusion treatments, especially the feasibility of performing measurements in an outpatient setting. To correct the effect of volume load on mitochondrial oxygenation, a red blood cell transfusion and a saline infusion were given in random order. In total, 21 patients were included, and this resulted in 31 observations. If patients participated twice, the order of infusion was reversed. In both the measurements wherein a blood transfusion was given first and wherein 500 mL of 0.9% saline was given first, the median mitochondrial oxygen tension decreased after red blood cell transfusion. The results of this study have strengthened the need for further research into the effect of blood transfusion tissue oxygenation and the potential role of mitochondrial parameters herein.

show abstract

Section: Discussionmentioning

confidence: 99%

Measuring Mitochondrial Oxygen Tension during Red Blood Cell Transfusion in Chronic Anemia Patients: A Pilot Study

et al. 2023

View full text Add to dashboard Cite

show abstract

“… 1 Despite the beneficial effects of an RBC transfusion, infectious and non-infectious complications may develop, meaning that patient safety must be ensured by using blood products appropriately. 2 The immunomodulatory effects of RBC transfusion may result in a higher incidence of nosocomial infections. 3 Furthermore, these products are expensive resources with limited availability; red blood cell (RBC) transfusions cost $500-1200 per unit.…”

Section: Introductionmentioning

confidence: 99%

Does red blood cell transfusion affect clinical outcomes in critically ill patients? A report from a large teaching hospital in south Iran

Naderi-Boldaji,

Zand,

Asmarian

et al. 2024

Ann Saudi Med

View full text Add to dashboard Cite

BACKGROUND: Despite the beneficial effects, RBC transfusion can be associated with infectious and non-infectious complications in critically ill patients. OBJECTIVES: Investigate current RBC transfusion practices and their effect on the clinical outcomes of patients in intensive care units (ICUs). DESIGN: Retrospective observational study SETTING: Three mixed medical-surgical adult ICUs of a large academic tertiary hospital PATIENTS AND METHODS: From March 2018 to February 2020, all adult patients admitted to medical or surgical ICU. Patients who received one or more RBC transfusions during the first month of ICU admission were included in the “transfusion” group, while the remaining patients were assigned to the “non-transfusion” group. MAIN OUTCOME MEASURES: Mortality and length of ICU and hospital stay. SAMPLE SIZE: 2159 patients RESULTS: Of 594 patients who recieved transfusions, 27% of patients received red blood cell (RBC) products. The mean pre-transfusion hemoglobin (Hb) level was 8.05 (1.46) g/dL. There was a significant relationship between higher APACHE II scores and ICU mortality in patients with Hb levels of 7–9 g/dL (OR adjusted=1.05). Also, ICU mortality was associated with age (OR adjusted=1.03), APACHE II score (OR adjusted=1.08), and RBC transfusion (OR adjusted=2.01) in those whose Hb levels were >9 (g/dl). CONCLUSION: RBC transfusion was associated with an approximately doubled risk of ICU mortality in patients with Hb>9 g/dL. High APACHE II score and age increase the chance of death in the ICU by 8% and 3%, respectively. Hence, ICU physicians should consider a lower Hb threshold for RBC transfusion, and efforts must be made to optimize RBC transfusion practices. LIMITATIONS: Single-center and retrospective study.

show abstract

“…In critically ill patients, anemia and coagulopathy are common and associated with poor outcomes, such as increased risk of mortality, myocardial infarction, and thrombosis [29]. Transfusion of blood and blood products remains a cornerstone of anemia and coagulopathy treatment in critical care.…”

Section: Introductionmentioning

confidence: 99%

Predicting the need for blood transfusion in intensive care units with reinforcement learning

Wang

Zhao

Petzold

2022

Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

View full text Add to dashboard Cite

As critically ill patients frequently develop anemia or coagulopathy, transfusion of blood products is a frequent intervention in the Intensive Care Units (ICU). However, inappropriate transfusion decisions made by physicians are often associated with increased risk of complications and higher hospital costs. In this work, we aim to develop a decision support tool that uses available patient information for transfusion decision-making on three common blood products (red blood cells, platelets, and fresh frozen plasma). To this end, we adopt an off-policy batch reinforcement learning (RL) algorithm, namely, discretized Batch Constrained Q-learning, to determine the best action (transfusion or not) given observed patient trajectories. Simultaneously, we consider different state representation approaches and reward design mechanisms to evaluate their impacts on policy learning. Experiments are conducted on two realworld critical care datasets: the MIMIC-III and the UCSF. Results demonstrate that policy recommendations on transfusion achieved comparable matching against true hospital policies via accuracy and weighted importance sampling evaluations on the MIMIC-III dataset. Furthermore, a combination of transfer learning (TL) and RL on the data-scarce UCSF dataset can provide up to 17.02% improvement in terms of accuracy, and up to 18.94% and 21.63% improvement in jump-start and asymptotic performance in terms of weighted importance sampling averaged over three transfusion tasks. Finally, simulations on transfusion decisions suggest that the transferred RL policy could reduce patients' estimated 28-day mortality rate by 2.74% and decreased acuity rate by 1.18% on the UCSF dataset. In short, RL with appropriate patient state encoding and reward designs shows promise in treatment recommendations for blood transfusion and further optimizes the real-time treatment strategies by improving patients' clinical outcomes.

show abstract

Transfusion in critical care: Past, present and future

Cited by 7 publications

References 136 publications

Measuring Mitochondrial Oxygen Tension during Red Blood Cell Transfusion in Chronic Anemia Patients: A Pilot Study

Measuring Mitochondrial Oxygen Tension during Red Blood Cell Transfusion in Chronic Anemia Patients: A Pilot Study

Does red blood cell transfusion affect clinical outcomes in critically ill patients? A report from a large teaching hospital in south Iran

Predicting the need for blood transfusion in intensive care units with reinforcement learning

Contact Info

Product

Resources

About