Do Allogeneic Blood Transfusions Cause Infection?
Aryeh Shander, Sherri Ozawa, Steven T. Brower
- 发表年份
- 2017
- 引用次数
- 2
摘要
It is not difficult to find clinicians who would answer the question above in the affirmative and also many who would disagree. What is well known is the fact that blood can transmit infection and that very real threat will continue as long as there is a reliance on donor blood. Since the early years of the human immunodeficiency virus (HIV) epidemic, active debate about screening processes for agents transmitted by transfusion has been ongoing and it remains alive today with the newly discovered infections. Moving beyond the direct transmission of pathogens through blood, here is the question of the day: do, or can, red blood cell (RBC) transfusions cause de novo infection?1 In this issue of Anesthesia & Analgesia, Mazzeffi et al2 provide insights into the links between blood transfusion and some hospital-acquired infections in patients undergoing colon surgery. Those who contend that only randomized prospective studies can establish causality would proffer that there are insufficient data of substance to claim that transfusions can cause nosocomial infections.3 On the other hand, those who “believe” that RBC transfusion can be a causative agent for nosocomial infections cite a plethora of observational studies that support this association.4 To strengthen their argument, the “believers” point to the mechanisms through which transfusions could increase the risk of infections. One major contender is the immune modulation that has been characterized as one of the risks of transfusions. Immunomodulatory effects of allogeneic blood have been long recognized since the preliminary observations that transfusion can prolong the life of kidney transplants, bringing the transfusion-related immune modulation (TRIM) into the glossary of transfusion medicine.5 However, TRIM is not a medical diagnosis and understanding its clinical significance remains a challenge. On the other hand, nosocomial infections are often multifactorial and they do occur in many hospitalized patients, even those who are not transfused. With no real diagnostic test or clinical surrogate for TRIM, clinicians can only suspect RBC transfusions and the subsequent TRIM among the contributing factors for significant nosocomial or postdischarge infections. We could end this commentary by declaring a mistrial, given that both sides can be partially correct, as well as partially wrong, but that would leave indefensible knowledge gaps. To try to span these gaps, we will first address the issue of causality and then the issue of retrospective trials and their significance in the world of transfusions. The concept of evidence-based medicine (EBM) as it applies to individual patient care was initially developed by Sackett et al,6 and since its inception, it carries the connotation that EBM is the highest quality practice. Contrasted with the other commonly used concept, Best Clinical Practice, EBM uses data, preferably of the highest quality rating, to support the therapeutic intervention, and thus attaining the best possible results for the patient being treated. Evidence, a legal term, should be replaced with “data,” and data should be the driver for clinical decisions. Although there are a few definitions of causality, for the purpose of this writing, we will consider it as a process such as transfusion of packed RBC that can be directly and clearly implicated for an outcome. In the realm of the legal world, establishing causation can involve various aspects related to the facts and policies, and depending on the context, a probability of just above 50% might be sufficient ground for causation and legal liability. In medicine, causality can be even more complicated, and practitioners can avoid implication by the “level of evidence” or the strength of the data. In essence, more than a 90% threshold and less than a 5% chance can be required to tie a process (therapy or intervention) to an outcome. Of course, disease is not the same as a crime, and many disease processes can b
关键词
相关论文
Causal Diagrams for Epidemiologic Research
Sander Greenland, Judea Pearl, James M. Robins
1999
Robots and Jobs: Evidence from US Labor Markets
Daron Acemoğlu, Pascual Restrepo
2019
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Leigh R. Hochberg, Daniel Bacher, Beata Jarosiewicz 等 11 位作者
2012
Campbell-Walsh urology
Alan J. Wein editor-in-chief
2012