Red blood cell transfusion may be more detrimental than anemia for the clinical outcome of patients with severe traumatic brain injury

Impact of anemia on acute ischemic stroke outcomes: A systematic review of the literature

INTRODUCTION

Anemia has been reported in nearly 40% of acute ischemic stroke (AIS) patients and is linked to significant morbidity and disability. The presence of anemia is associated with worse outcomes in AIS, specifically in the presence of large vessel occlusion (LVO). An optimal hemoglobin (Hb) target specific to this pathology has not yet been established. The goal of this review is to systematically review literature that observes the association that exists between AIS outcomes and hemoglobin (Hb) levels.

METHODS

A systematic review was performed in accordance with guidelines for the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) to identify studies from 2008-2022. The following inclusion and exclusion criteria were used: studies of adult patients with AIS; must describe outcomes with regard to Hb levels in AIS (not limited to LVO); must be written in English. The clinical variables extracted included Length of Stay (LOS), modified rankin score (mRS), Hb levels, and mortality.

RESULTS

A total of 1,154 studies were gathered, with 116 undergoing full text review. 31 studies were included in this review. The age of patients ranged from 61.4 to 77.8. The presence of anemia in AIS increased LOS by 1.7 days on average and these patients also have a 15.2% higher rate of mortality at one year, on average.

DISCUSSION

This data suggests that the contemporary thresholds for treating anemia in AIS patients may be inadequate because anemia is strongly associated with poor outcomes (e.g., mRS>2 or mortality) and increased LOS in AIS patients. The current generalized Hb threshold for transfusion (7 g/dL) is also used in AIS patients, however, a more aggressive transfusion parameter should be further explored based on these findings. Further studies are required to confirm these findings and to determine if a more liberal RBCT threshold will result in clinical benefits.

Intelligent prediction of RBC demand in trauma patients using decision tree methods

BACKGROUND

The vital signs of trauma patients are complex and changeable, and the prediction of blood transfusion demand mainly depends on doctors' experience and trauma scoring system; therefore, it cannot be accurately predicted. In this study, a machine learning decision tree algorithm [classification and regression tree (CRT) and eXtreme gradient boosting (XGBoost)] was proposed for the demand prediction of traumatic blood transfusion to provide technical support for doctors.

METHODS

A total of 1371 trauma patients who were diverted to the Emergency Department of the First Medical Center of Chinese PLA General Hospital from January 2014 to January 2018 were collected from an emergency trauma database. The vital signs, laboratory examination parameters and blood transfusion volume were used as variables, and the non-invasive parameters and all (non-invasive + invasive) parameters were used to construct an intelligent prediction model for red blood cell (RBC) demand by logistic regression (LR), CRT and XGBoost. The prediction accuracy of the model was compared with the area under the curve (AUC).

RESULTS

For non-invasive parameters, the LR method was the best, with an AUC of 0.72 [95% confidence interval (CI) 0.657-0.775], which was higher than the CRT (AUC 0.69, 95% CI 0.633-0.751) and the XGBoost (AUC 0.71, 95% CI 0.654-0.756, P < 0.05). The trauma location and shock index are important prediction parameters. For all the prediction parameters, XGBoost was the best, with an AUC of 0.94 (95% CI 0.893-0.981), which was higher than the LR (AUC 0.80, 95% CI 0.744-0.850) and the CRT (AUC 0.82, 95% CI 0.779-0.853, P < 0.05). Haematocrit (Hct) is an important prediction parameter.

CONCLUSIONS

The classification performance of the intelligent prediction model of red blood cell transfusion in trauma patients constructed by the decision tree algorithm is not inferior to that of the traditional LR method. It can be used as a technical support to assist doctors to make rapid and accurate blood transfusion decisions in emergency rescue environment, so as to improve the success rate of patient treatment.

Red cell use in trauma

PURPOSE OF REVIEW

Red cell transfusions are commonly used in management of hemorrhage in trauma patients. The appropriate indications and criteria for transfusion are still debated. Here, we summarize the recent findings on the use of red cell transfusion in trauma setting.

RECENT FINDINGS

Recent evidence continues to support the long-established link between allogeneic transfusion and worse clinical outcomes, reinstating the importance of more judicious use of allogeneic blood and careful consideration of benefits versus risks when making transfusion decisions. Studies support restrictive transfusion strategies (often based on hemoglobin thresholds of 7-8 g/dl) in most patient populations, although some argue more caution in specific populations (e.g. patients with traumatic brain injury) and more studies are needed to determine if these patients benefit from less restrictive transfusion strategies. It should be remembered that anemia remains an independent risk factor for worse outcomes and red cell transfusion does not constitute a lasting treatment. Anemia should be properly assessed and managed based on the cause and using hematinic medications as indicated.

SUMMARY

Although the debate on hemoglobin thresholds for transfusion continues, clinicians should not overlook proper management of the underlying issue (anemia).