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50yoM with controlled HIV presented with slowly enlarging inguinal lymphadenopathy over the last 9 months. Flow cytometry and lymph node biopsy revealed an aberrant population of lymphoid cells. Here's the H&E: Here are the results of IHC: Stain Result CD3 Negative CD4 Positive CD5 Positive CD20 Negative CD30 Positive CD45 Positive ALK1 Positive What is the diagnosis? Anaplastic Large Cell Lymphoma (ALCL) – ALK-positive! A subtype of peripheral T-cell lymphoma, it classically presents as large cells with abundant cytoplasm, pleomorphic, horseshoe-shaped nuclei, and CD30 positivity.   The presence of Alk1 positivity is associated with translocation t(2;5) producing the ALK1 :: NMP1  fusion gene. It is frequently associated with HIV, mycosis fungiodes, and pulmonary pseudotumors. The main differentials include Hodgkins Lymphoma (also CD30+, CD3-, CD20-), and Alk-negative ALCL.   Known as a moderately aggressive tumor, it has an overall prognosis better than other peripheral T cell lymphomas, including Alk1 negative ALCL, with 5 year survival of 80%. The presence of MYC rearrangement, small cell morphology, or lymphohistiocytic variant indicate a poor prognosis.   References: https://www.ncbi.nlm.nih.gov/books/NBK537150/ .

Here's something I never thought I'd say: I spent the afternoon coding with ChatGPT 4.0. In about 3 hours I was able to turn out an updated, polished, robust, and future-proofed piece of code to assist blood bankers with selecting HLA compatible platelets. When used judiciously and wisely, large language models like ChatGPT truly are incredible tools. After finishing the code, I composed this post with ChatGPT. You'll notice it's not really my voice, but it captures all the essential points I wanted to make. Full disclosure: the following text was produced with ChatGPT. Automation is transforming medicine by streamlining complex workflows, minimizing human error, and enabling healthcare professionals to focus on patient care. In transfusion medicine, automation has the potential to revolutionize tasks like platelet compatibility matching, where precision and efficiency are vital. Through the power of coding, we recently embarked on a project to automate HLA platelet matching, creating a tool that simplifies this intricate process and produces clear, professional results. Platelet compatibility largely hinges on matching donor and recipient Human Leukocyte Antigens (HLA), a mismatch of which is the most common underlying factor in platelet refractoriness. The process involves utilizing a number of different methods, but most commonly revolves around bioinformatic data from services like HLA MatchMaker, and Mean Fluorescence Intensity (MFI) values which are a semi-quantitative assessment of HLA antibody strength. Avoidance notes to prevent alloimmunization against future donor antigens is also important. MFI values can be summed to produce a compatibility score, and while this process is time-consuming and error prone, it does allow selection of the most suitable platelet units while avoiding those that may trigger rejection. Manually calculating HLA compatibility from MFI involves sorting through large datasets of donor and recipient information, correctly matching HLA antigens, and ensuring the correct application of MFI scores, all of which requires significant attention to detail. The risk of human error looms large, and the process can be daunting for even experienced professionals. Automation, on the other hand, eliminates these drawbacks, offering consistent accuracy, faster turnaround times, and the ability to scale workflows seamlessly. The code we developed today showcases the benefits of automation. By parsing recipient and donor files, expanding HLA antigens into standardized formats, and calculating compatibility scores programmatically, the tool significantly reduces the potential for manual errors. The system also handles duplicate avoidance notes efficiently and generates a polished Word document report with tables formatted for clarity. Designed with future-proofing in mind, the code is modular and adaptable for future updates, ensuring it can grow alongside evolving needs in transfusion medicine. The output generated by the tool is a comprehensive Word document that is both readable and usable. Platelet units are ranked in order of decreasing compatibility, tables are presented in landscape orientation for better visibility, and column widths are tailored, particularly for the Avoids column, to display longer text. The use of bold headers and subtle shading enhances readability, making it easier for blood bankers to review compatibility results at a glance. By combining automation with user-centric design, the final output serves as a powerful decision-making tool. Looking ahead, the project can be improved by embedding detailed instructions for use directly into the code. This ensures the tool remains accessible and easy to use, even if external instruction files are misplaced. Additionally, building a robust test harness will facilitate future updates and maintain code reliability as the tool evolves. With these enhancements, the system can become an even more indispensable asset for transfusion medicine teams. Automation and coding are powerful allies in modern medicine, bridging the gap between complex data analysis and actionable insights. By reducing human error and enhancing workflows, these tools empower healthcare professionals to provide safer and more efficient patient care. For those looking to harness this potential, learning to use tools like ChatGPT for coding can be a transformative first step. With creativity and determination, coding can open doors to endless possibilities in healthcare innovation.

In 2021 I co-founded the Society for Innovation and Research (SIR) while in my clinical pathology residency. Our goal was to promote and support resident participation in research and innovation. Using PubMed indexed publications as a metric of success, we found that SIR more than doubled the average number of resident publications, while also increasing the average number of residents publishing and the average number of co-authored publications (a surrogate for collaboration within the residency program). In short, SIR was a breakout success. Efforts to promote resident research productivity often emphasize grant funding in their curricula; however, with SIR we avoided the subject entirely for two reasons. First, obtaining grant-funding is largely inaccessible while in clinical training, and second the rigors of sustaining grant-funded research are unattractive to many residents, who as a cohort are starting to emphasize lifestyle in their career choices. Instead of emphasizing applying for grants and spending precious free hours at the bench, we introduced a new paradigm of research and participation in science in graduate medical education, with “one foot only in the ivory tower”. In doing so, we considered the following three major points. First, doctors need to be educated consumers of scientific literature. SIR featured monthly workshops during which residents presented works in progress to their co-residents, who then participated in giving critical feedback. Thus, residents in the audience built critical thinking skills about collecting, analyzing, and displaying data in an experiential fashion. It was our belief that this experiential learning would solidify the importance of critical thinking better than simply reading and discussing literature. Second, most residents will not have the time to participate in discovery research. Yet, this does not mean they cannot participate in research at all. In SIR we emphasized retrospective chart reviews and case reports, both being more attainable for busy residents. We routinely utilized TriNetX, a deidentified clinical database from institutions across the world, and in doing so introduced skills in bioinformatics and data science, which are becoming more critical with every passing year. These kinds of projects can still produce valuable results, and largely do not require grant funding. By shifting focus away from the long tradition of grant-funded bench work, we gave residents the tools to participate in research for years to come, whether they opt to pursue grant funding or not. Third, communicating science is of the upmost importance with the uptick of health misinformation spreading across social media, and should be a major goal of any research oriented program in graduate medical education. SIR workshops allowed residents to not only practice presenting projects, but also to hear their co-residents present and observe what worked well. In summary, we shouldn’t teach research skills to residents with the framework that everyone needs to be a grant-funded researcher to be successful, or that this is the pinnacle of participation in the scientific endeavor. Current residents are becoming doctors in an era in which scientific literacy is in decline, and much of the joy of science has been lost to hyper-competitive grant funding and relentless productivity metrics. We should be introducing new paradigms of accessible research to residents, as we did in SIR, as it is more critical than ever that they embrace the scientific endeavor to improve the conditions of humanity.

In this post we’re going to talk about sequencing and genomics, and I hope it’s as educational for you as it was for me.   Let’s start by putting sequencing in perspective. There are a variety of methods we use in molecular pathology, each of which tells us different information about the genome of our patient. I find to helpful to think of molecular methods as dividable into two bins: methods that give us structural information and methods that give us sequence information. Remember that the genome is not just a string of base pairs; all that DNA is eloquently wrapped around histones and packed into chromatin, which is further organized into supercoiled DNA, which ultimately becomes a chromosome. The genome itself occurs on a scale from base pair to chromosome, and similarly we need methods that can give us information across this scale.   In the structural bin, we have karyotypes and fluorescence in situ hybridization (FISH). Karyotypes involve the collection of condensed chromosomes at metaphase, staining thereof (several different methods for this), and then arrangement into chromosome pairs for analysis of differences. FISH involves the hybridization of fluorescently labeled probes, but in order to get good detection of that probe it has to be fairly large, between 1 mega base pair and 100 kilo base pairs. Both karyotype and FISH are good for structural information like translocations, as well as medium-large insertions and deletions.   In the sequence bin we have sequencing, which we will talk about more in a minute, and chromosomal microarray (CMA). Like FISH, CMA involves the hybridization of probes, but their scale is much smaller – only 5-10 kilo base pairs. Because of this, CMA can give limited information on sequence. However, it is really best for copy number changes, such as unbalanced translocations, and smaller deletions and insertions. It’s important to remember that CMA cannot detect a balanced translocation, and for this you will need to use either karyotype or FISH. Karyotype FISH CMA Sequencing Useful for Chromosome Chromatin Chromatin/ Base pair Base pair Resolution (in base pairs, bp) 5 mega bp 1 mega - 100 kilo bp 5-10 kilo bp 1 bp Good for Translocations, Large deletions and insertions Translocations, Medium deletions and insertions Unbalanced translocations, Smaller deletions and insertions, Limited base pair data Smallest deletions and insertions, Single base pair changes Bad for Sequence data Sequence data Balanced translocations, Structural information Structural information   Table credit: Caitlin Raymond Then there is sequencing, which can only give information about the base pairs in string of DNA, and cannot give information about structure. It can detect the smallest deletions and insertions, as well as single base pair changes. Sequencing began with the Sanger method, which is labor intensive and limited to about 1 kilo base pair of output. However, new sequencing platforms have come on the market, and we’ll talk about two of particular interest here: next generation sequencing (NGS) and nanopore sequencing.   There are multiple platforms for NGS, which vary in their technical details. What they have in common is that each platform uses massively parallel sequencing of many small DNA fragments attached to a solid surface. Sequencing may occur by adding only one nucleotide at a time and assessing for its incorporation (pyrosequencing, ion semiconductor sequencing), or by adding a mixture of reversibly terminal nucleotides conjugated to a unique florescent probe (sequencing by synthesis). Regardless of the technical details, NGS systems output a massive amount of sequencing data, much more so than the Sanger sequencing method that preceded them. All that data can be collated to sequence large segments of DNA rapidly and efficiently, including whole genomes.  Image source: https://www.researchgate.net/figure/Comparison-between-Sanger-sequencing-and-next-generation-sequencing-NGS-technologies_fig2_260197220 Nanopore sequencing, in contrast to most forms of NGS, does not utilize a DNA polymerase. Instead, a helicase sits atop a nanopore that crosses a membrane barrier. The helicase extrudes a single strand of the DNA through the nanopore, which has an ionic current running through it. Each nucleotide makes a predictable change in the current as it passes through the narrowest aperture of the nanopore, and the sequence is determined. Nanopore sequencing can produce reads for hundreds of kilo bases, and across stretches of DNA that are not easily sequenceable through other methods, such as telomeres and centromeres.  Image source: https://www.genome.gov/genetics-glossary/Nanopore-DNA-Sequencing In order to understand the role of these newer sequencing technologies in genomics, it helps to know a little of the history of the human genome. The original Human Genome Project launched in 1990, and in 2003 they announced that they had sequenced 92% of 10 samples. That remaining 8% included difficult to sequence regions like telomeres, and just recently in 2022 the Telomere to Telomere project released the first ever fully sequenced human genome. You’ll also note that only 10 samples were sequenced in the Human Genome Project, hardly a representative sample. In 2008, the 1,000 Genomes Project was launched, aiming to fully sequence 1,000 samples of the human genome from around the globe.   Image credit: Caitlin Raymond To make sense of all this data, the Encyclopedia of DNA Elements (ENCODE) Project was launched, aiming to produce a comprehensive database of all functional elements in the human genome. The National Institutes of Health also stated two centers to investigate the role of genetics in human disease. The Common Disease Genomics center aims to understand the role of genetics in common diseases such as diabetes and high blood pressure. In contrast, the Centers for Mendelian Genomics aims to further study the role of specific genes in the development of inherited diseases, such as cystic fibrosis.   In terms of classifying the results of this data, two terms are commonly used, but frequently misunderstood. A polymorphism, or single nucleotide polymorphism (SNP), is a sequence change at a single base pair that is present in ≥ 1% of the reference genome. A variant is a sequence change present at < 1% of the reference genome. Obviously, as more genomes and sequences are added to the reference database, we’ll have a better understanding of which sequence changes are SNPs and which are variants.   Variants are often investigated for links to disease states, and are currently classified on a five-point scale: benign, likely benign, unknown significance, likely pathogenic, and pathogenic. Variants and their assigned classification can be found in the ClinVar database, which is freely available online. With so much yet unknown about the human genome and how it influences disease, it can come as little surprise that assigning a category to a variant is challenging, and sometimes variants are reclassified based on updated studies in the scientific literature. Most often, a variant with unknown significance (VUS) is reassigned to either the benign or pathogenic categories. In a recent study, Veenstra et al. found that most VUS are being reclassified as benign as we learn more about the diversity of the human genome [1]; however, some still are being reclassified as pathogenic. SoRelle et al. published similar findings, and moreover found that the rate at which VUS are being reclassified is steadily increasing [2]. In 2018, Mersch et al. found that the average time to reclassification of a VUS dropped from a mean of ~2.5 years to less than 1 year between 2006 and 2016, with no sign of slowing down [3].   This raises an important question: if a patient was notified of a VUS in their clinical sequencing results, and the status of that VUS changes, do we have a duty to inform the patient? A minority of clinical genetics centers are already doing so. In a 2018 survey of 105 genetics centers, 26 (or ~25%) responded that they were routinely recontacting patients if a VUS in their results was reclassified [4]. However, the issue of consent for recontacting has not been fully addressed. When do patients consent to recontact for updated information about their clinical genetics results? What if they do not consent? In a survey about their preferences regarding recontact, 50.4% of patients declined to receive updates about their results, commonly citing concerns about insurability [5]. Another as yet unanswered question is who will be responsible for updating the patient? In a 2019 statement, the American College of Medical Genetics suggested the ordering provider bear chief responsibility, but that patients, consulting geneticists, clinical labs, and even research laboratories all shared some responsibility in making this possible.   Image credit: Caitlin Raymond To summarize, big data has arrived in genomics with new sequencing technologies enabling the production of huge datasets. With all this data our understanding of polymorphisms and particularly variants is rapidly changing, and there is ongoing debate about how to convey this to patients.   I’d like to close with some thought for the societal impact of big data in genomics. Technology in molecular pathology is racing ahead, with societal customs and our legal system struggling to keep up. The next 10 years will be critical to lay a fair groundwork for who gets access to this data and how this data is used. "One of my concerns has been the limits on applications of our understanding of the genome. Should there be limits? I think there should. I think the public has expressed heir concenr about ways this information might be misused." - Francis Collins   1.       Veenstra, D. L., Rowe, J., Pagán, J. A., Brown, H. S., Schneider, J., Gupta, A., ... & Appelbaum, P. S. (2021). Reimbursement for genetic variant reinterpretation: 5 questions payers should ask.  The American journal of managed care ,  27 (10), e336. 2.       SoRelle JA, Thodeson DM, Arnold S, Gotway G, Park JY. Clinical Utility of Reinterpreting Previously Reported Genomic Epilepsy Test Results for Pediatric Patients.  JAMA Pediatr.  2019;173(1):e182302. doi:10.1001/jamapediatrics.2018.2302 3.       Mersch J, Brown N, Pirzadeh-Miller S, Mundt E, Cox HC, Brown K, Aston M, Esterling L, Manley S, Ross T. Prevalence of Variant Reclassification Following Hereditary Cancer Genetic Testing. JAMA. 2018 Sep 25;320(12):1266-1274. doi: 10.1001/jama.2018.13152. PMID: 30264118; PMCID: PMC6233618. 4.       Sirchia F, Carrieri D, Dheensa S, et al. Recontacting or not recontacting? A survey of current practices in clinical genetics centres in Europe. Eur J Hum Genet. 2018 Jul;26(7):946-954. doi: 10.1038/s41431-018-0131-5. Epub 2018 Apr 23. PMID: 29681620; PMCID: PMC6018700. 5.       Henrikson NB, Scrol A, Leppig KA, Ralston JD, Larson EB, Jarvik GP. Preferences of biobank participants for receiving actionable genomic test results: results of a recontacting study. Genet Med. 2021 Jun;23(6):1163-1166. doi: 10.1038/s41436-021-01111-2. Epub 2021 Feb 18. PMID: 33603197; PMCID: PMC8194390. 6.       David, K.L., Best, R.G., Brenman, L.M.  et al.  Patient re-contact after revision of genomic test results: points to consider—a statement of the American College of Medical Genetics and Genomics (ACMG).  Genet Med  21, 769–771 (2019). https://doi.org/10.1038/s41436-018-0391-z

Last year I had a patient with anti-Fya, Fyb, and Fy3 antibodies. Don’t know what that means? Let’s learn together in this bullet learning entry. Initially discovered in the 1950s, the Duffy blood group (abbreviated as Fy) consists of 6 antigens on a transmembrane protein/cytokine receptor. These antigens are Fya, Fyb, Fy3, Fy4, Fy5, and Fy6. The latter three - Fy4, Fy5, and Fy6 - are considered clinically insignificant. This protein also facilitates malaria infection, and absence of Duffy antigens is associated with resistance. As you can imagine, patients from areas with endemic malaria are more likely to be Duffy negative. This is a problem in the US, as most of our blood supply is from Caucasians, who are more likely to be Duffy positive. This particularly impacts patients with sickle cell disease in the US. They are more likely to be of African American descent, be Duffy negative, and have difficulty obtaining appropriate blood. What a great argument for diversity in our blood donor supply! In the case of our patient, we were able to source Fya, Fyb, Fy3 negative blood. But the search was difficult, and treatment was delayed. Please take a moment and consider donating blood. See this link to find a blood donor center near you! https://americasblood.org/for-donors/find-a-blood-center/   References: https://www.intechopen.com/chapters/69794

Over the past six months I've gone on a scavenger hunt for all the instruments in our clinical pathology divisions. I combined all my findings into a (semi) comprehensive guide to instruments, indexed by division, instrument name, and method. I hope this helps your learning as much as it did mine!

I’ve seen a recent opinion on social media amongst medical trainees that research is boring, something done only to check the boxes to advance in one’s career. I don’t know the penetrance of this opinion and it may be isolated, but I see a link between this dispassionate description of research activities by trainees and a recent paper discussing the decline of disruptive science. Hear me out.   In 2016, Funk and Owen-Smith published something called the consolidation-disruption index (CDI) [1]. Essentially, this index expresses whether a new study consolidates scientific understanding, that is whether it reinforces current understanding of a subject, versus disruption, which is whether it brings new ideas and updates to understanding of a subject. The CDI is calculated based on the number of citations a study has in the 5 years following its publication and expressed on a scale from -1 (most consolidating) to 1 (most disruptive).   Earlier this year, Park et al. applied this formula to 45 million scientific papers and 3.9 million patents published across a 60-year span in 4 disciplines – life sciences, physical sciences, social sciences, and technology [2]. They found an astounding and alarmingly steady decline in the average CDI across all disciplines studied from 1950 to 2010. Life sciences experienced the greatest decline in disruptive papers, while technology experienced the least.   Of course, this study made a big impact in scientific circles, and ignited a chorus of think pieces addressing why disruptive science is declining. One common theme among these was the corporatization of science and the emphasis on volume of citations for young scientists to obtain grant funding and promotion. As pointed out by Bhattacharya et al., the push for evidence of productivity incentivizes scientists to publish incremental work and concentrates the volume of scientific effort on ideas that have already been established [3]. Similarly, Derek Thompson points out that scientists are not incentivized to submit grant proposals on entirely new ideas given the tight competition to obtain a grant and the high risk of failure [4]. Instead, scientists submit grants that are ‘optimally new’: new enough to secure a grant, but safe enough to secure publication.   Together, all these influences have created a surplus of papers designed to advance careers, not science, and it seems that medical trainees have certainly picked up on this trend. There’s been a steady decline in the number of trainees opting for the physician-scientist pathway, as well as a decline in the number of physician-scientists participating in biomedical research in their careers [5]. At the same time, there’s been increasing interest among PhD graduate students in leaving academia entirely [6-8].   I would argue that for a large percentage of trainees, corporatization has sucked the joy from science. The maxim to ‘publish or perish’ and exhausting competition over limited funding makes it almost impossible to enjoy the process of discovery and keep joyful curiosity about the work of science. Small wonder then that medical trainees view research as a box to check for their application, a menial task for career enhancement rather than an exploration of the human condition. As one trainee put it, research has indeed become ‘boring’.   So how do we put the joy back into science? Revision of the funding model would certainly help. Calls to fund careers of promising young scientists without ties to the success of a specific project abound. Increased support from institutions to cover gaps in grant funding and less emphasis on citations for promotion, among many others, have been proposed. Whether there is the will power to enact these changes remains to be seen.   1.       Russell J. Funk, Jason Owen-Smith (2016) A Dynamic Network Measure of Technological Change. Management Science 63(3):791-817. https://doi.org/10.1287/mnsc.2015.2366 2.       Park, M., Leahey, E. & Funk, R.J. Papers and patents are becoming less disruptive over time. Nature 613, 138–144 (2023). https://doi.org/10.1038/s41586-022-05543-x 3.       Bhattacharya, Jayanta and Packalen, Mikko. Stagnation and Scientific Incentives (February 2020). NBER Working Paper No. w26752, Available at SSRN: https://ssrn.com/abstract=3539319 4.       Thompson, D. The Consolidation-Disruption Index is Alarming. https://www.theatlantic.com/newsletters/archive/2023/01/academia-research-scientific-papers-progress/672694/ 5.       Garrison, H. H., & Ley, T. J. (2022). Physician‐scientists in the United States at 2020: Trends and concerns.  The FASEB Journal ,  36 (5). 6.       Chen, S. (2021). Leaving academia: why do doctoral graduates take up non-academic jobs and to what extent are they prepared?.  Studies in Graduate and Postdoctoral Education ,  12 (3), 338-352. 7.       Hunter, K. H., & Devine, K. (2016). Doctoral students’ emotional exhaustion and intentions to leave academia.  International Journal of doctoral studies ,  11 (2), 35-61. 8.       Kis, A., Tur, E. M., Lakens, D., Vaesen, K., & Houkes, W. (2022). Leaving academia: PhD attrition and unhealthy research environments.  Plos one ,  17 (10), e0274976.

An octogenarian woman with past medical history of coronary artery disease on aspirin and Plavix presents from an assisted living facility with complaints of blood in her diaper. Hemoglobin is 5.8 g/dL, and a unit of O negative blood is given on emergency release, meaning the blood was transfused before a full type and screen and crossmatch could be performed. Two hours following transfusion, information is obtained from an outside hospital significant for a history of anti-E. Upon completion of testing, the emergency release unit was found to be incompatible on crossmatch, and antigen typing of the unit was significant for the presence of E antigen.   What are you concerned about? Hemolysis!   Hemolytic transfusion reactions occur when a patient antibody binds to antigen on a transfused red blood cell (RBC). The bound antibody may then fix complement to the surface of the transfused RBC and initiate lysis, which releases the contents of the RBC into the blood stream. Contents of the RBC include lactate dehydrogenase (LDH) and bilirubin, and monitoring for elevations in these analytes helps determine a diagnosis of hemolysis. Similarly, hemoglobin is released from the lysed RBC which is then bound by haptoglobin. The haptoglobin-hemoglobin complex is then taken up and digested by macrophages, which prevents accumulation of hemoglobin in the kidneys and reduces the potential for renal injury. Thus, hemolysis involves a decrease in circulating haptoglobin, and reduced haptoglobin levels help determine a diagnosis of hemolysis.   Hemolysis can occur in two compartments in the body. Intravascular hemolysis occurs within blood vessels and generally causes a more severe syndrome. Because the contents of RBCs are being released directly into the blood stream, the classic triad of elevated LDH and bilirubin, and reduced haptoglobin, is commonly seen. The body’s natural defenses against hemolysis – namely haptoglobin – can be easily overwhelmed, and excess circulating hemoglobin can accumulate in the kidneys, causing both renal injury and hemoglobinuria. This is an important way to distinguish intravascular hemolysis from extravascular hemolysis. Extravascular hemolysis occurs when antibody-coated RBCs are taken up by macrophages in the reticuloendothelial system (i.e. the spleen), which then digests the RBC and its contents. Some of the RBC contents may spill out of macrophages, but because RBC destruction is largely occurring inside macrophages, extravascular hemolysis tends to feature less severe elevations in LDH and bilirubin, less severe reductions in haptoglobin, and less severe symptoms all around. It’s important to note that there are exceptions, and severe cases of extravascular hemolysis have been reported.   Hemolytic transfusion reactions can be acute, meaning they occur within 24 hours of transfusion, or delayed, meaning they occur between 1- and 28-days following transfusion. Acute hemolytic transfusion reactions involve a pre-existing antibody, and are typically more severe, whereas delayed transfusion reactions can involve either a pre-existing or newly made antibody and tend to be less severe. Hemolytic transfusion reactions can also be divided into two categories based on the type of antibody involved. ABO antibodies are naturally occurring largely IgM antibodies. IgM antibodies are very good at fixing complement, and ABO-incompatibility tends to cause severe, intravascular hemolytic transfusion reactions. Non-ABO antibodies typically develop in response to antigen exposure and are largely IgG. They may or may not fix compliment, may cause either intravascular or extravascular hemolysis, and tend to cause less severe reactions than ABO antibodies. Again, there are exceptions to this, with non-ABO antibodies causing severe hemolysis.   Prior to 1985, ABO-incompatibility was responsible for ~15% of all deaths from hemolytic transfusion reactions [1]. Investigations showed that erroneous patient identification on blood samples for type and screen was a common underlying culprit, and the term ‘wrong blood in tube’ (WBIT) was coined. Between 1985 and 2005 a bevy of initiatives to increase blood safety were launched, including two-factor patient identification, bar code scanning of sample labels and patient wrist bands, bar code scanning on blood product labels, and administrative systems for tracking of patient blood type and antibody history [1]. These efforts had good effect, and from 2005-2008 ABO-incompatibility accounted for only 5.5% of deaths from hemolytic transfusion reactions [1].   In line with innovations to prevent hemolysis came innovations in treating hemolysis. First line treatment remains supportive, such as maintaining normokalemia, normotension, and urine pH > 6.5. The options for second line treatment have expanded, and now include steroids, plasma exchange, and continuous dialysis [2]. There are now even third line options for refractory cases of hemolysis. Ruxolotinib is a JAK-STAT inhibitor that serves to inhibit downstream cytokine activity in severe cases of hemolysis, and eculizumab is a monoclonal antibody against C5 in the complement cascade that can inhibit formation of the membrane attack complex and destruction of RBCs [2].   Now that we know so much about hemolysis, let’s come back to our patient with a history of anti-E who was transfused an E positive unit on emergency release. She was briefly managed in the ICU where it was determined she was bleeding from her bladder. Aspirin and Plavix were held, and the patient underwent bladder irrigation. Notably, she developed no signs or symptoms of acute or delayed hemolysis during her hospital stay. She did well and was discharged to follow up outpatient.   So why didn’t this patient have hemolysis? Because hemolysis is influenced by a number of factors: how much antigen the patient is exposed to, how antigenic the antigen is, the titer of the alloantibody, and whether the antibody fixes complement can all influence whether a hemolytic transfusion reaction develops. In this case, anti-E is described as producing mild to moderate hemolysis, so is less antigenic than other antigens, and the patient’s DAT was negative for C3d, which means her anti-E antibody was not very good at fixing complement. These are both possible explanations for why this patient escaped hemolysis even though she was exposed to E antigen. Hemolysis does not occur 100% of the time, and is not 100% fatal.   Take away points: Hemolytic transfusion reactions can be acute or delayed. ABO incompatibility is generally more severe than non-ABO incompatibility. Treatment for hemolytic reactions is largely supportive, but there are also fancier options. Hemolysis does not happen 100% of the time, and is not 100% fatal. A DAT helps you determine what type of antibody is on the patient’s RBC, and whether it fixes complement.    References: 1.       Vamvakas, E. C., & Blajchman, M. A. (2010). Blood still kills: six strategies to further reduce allogeneic blood transfusion-related mortality. Transfusion medicine reviews, 24(2), 77-124. 2.       Ackfeld, T., Schmutz, T., Guechi, Y., & Le Terrier, C. (2022). Blood transfusion reactions—a comprehensive review of the literature including a swiss perspective. Journal of Clinical Medicine, 11(10), 2859.

Donating blood is an essential community service that saves lives. Because donors are healthy volunteers, several safety precautions are put in place to maintain their well-being. For example, there are restrictions on how often one can donate different types of blood products, to ensure that the donor has adequate time to recover. Blood Product Donated Donation Interval Whole Blood 56 days/8 weeks 1 unit of red blood cells 56 days/8 weeks 2 units of red blood cells 112 days/16 weeks Platelets 7 days/1 week Plasma 48 hours/2 days (no more than twice in 7 days) One common issue of donor safety is iron depletion or deficiency. A donation of one unit of whole blood contains about 250 mg of iron, or about 25% of the iron stores in a typical adult male. For menstruating individuals, this percentage is higher. Loss of iron stores leads first to iron depletion, which is defined as iron levels <26 ng/dL, then to iron deficiency, which is defined as iron levels <19 ng/dL. If iron deficiency is not corrected, it can reduce production of red blood cells and lead to anemia, which is defined as hemoglobin levels < 13.5 g/dL in males and <12.0 g/dL in females.   Blood donation centers routinely test hemoglobin levels prior to blood donation. This can uncover anemia and an anemic donor will be deferred for donor safety. However, iron levels are generally determined with a ferritin level, which is not routinely performed at donor centers. Studies show that while anemia is present in 4.2% of all donors and 6.2% of female donors, iron deficiency is more prevalent at 13.6% of all donors, and 22.6% of female donors [1].   As transfusion medicine physicians, we care about the iron levels of our donors for two main reasons. First, we want to maintain the well-being of our healthy volunteer donors. Iron is an essential nutrient and evidence suggests it is critical not just for the production of red blood cells, but also for brain maturation and development as well as healthy pregnancies [2]. Second, we want to act as good stewards of our blood supply. Approximately 8-12% of all potential blood donations are deferred due to iron deficiency, and mitigating iron deficiency could reduce deferrals by 66% [2].   A great deal of research has been done to investigate iron deficiency in donors. First, the HEIRS study found that iron supplementation in the first 8 weeks after donation can help donors recover faster [3]. Second, the STRIDE study found that testing for ferritin levels at donation and providing written documentation of the result is as effective as prescribing iron supplementation [4]. Finally, the CHILL study found that adolescent donors are more at risk of iron deficiency than their adult counterparts [5].   Currently, the AABB recommends that blood donation centers adopt the following three strategies to mitigate iron deficiency in their donors. First, that they provide educational materials about iron deficiency and discuss its impacts, particularly in at risk subgroups of donors like adolescents and individuals who menstruate. Second, that they provide direct intervention either to all donors or to at risk subgroups by testing for ferritin levels, providing iron tablets or vouchers for iron supplements, or spacing out donation intervals to allow for adequate recovery. Finally, that donor centers implement monitoring of donor iron deficiency after implementing one or both of the above strategies.   There remain some unanswered questions in the field of donor iron deficiency. First, what dose of iron supplementation is appropriate? In the original HEIRS study, donors were supplemented with daily iron doses. In the time since that study, evidence has emerged that daily iron dosing actually inhibits the absorption of iron by triggering the release of hepcidin [6, 7], and current recommendations are to dose iron every other day or even three times per week.   Another unanswered question is the risk of iron supplementation itself. Several recent studies have found a link between iron supplementation and increased risk of bacteremia and bacterial seeding [8]. However, these studies were done on healthy donors taking iron supplements and did not include those with iron deficiency in the study population. Whether these results can be extrapolated to iron deficient donors remains to be seen. To date, studies of donor iron deficiency have not tracked infection, hospitalization, or death as an outcome of donor iron supplementation.   In summary, blood donation can lead to iron deficiency, and iron supplementation of donors is a cost-effective intervention to maintain donor health and the blood supply. However, there may be room for improvement in the current guidelines and further studies would certainly be indicated.   References: 1.       Salvin, H.E., Pasricha, S.R., Marks, D.C. and Speedy, J., 2014. Iron deficiency in blood donors: a national cross‐sectional study.  Transfusion ,  54 (10), pp.2434-2444. 2.       Smith GA, Fisher SA, Doree C, Di Angelantonio E, Roberts DJ. Oral or parenteral iron supplementation to reduce deferral, iron deficiency and/or anaemia in blood donors. Cochrane Database of Systematic Reviews. 2014(7). 3.       Kiss JE, Brambilla D, Glynn SA, Mast AE, Spencer BR, Stone M, Kleinman SH, Cable RG; National Heart, Lung, and Blood Institute (NHLBI) Recipient Epidemiology and Donor Evaluation Study–III (REDS-III). Oral iron supplementation after blood donation: a randomized clinical trial. JAMA. 2015 Feb 10;313(6):575-83. doi: 10.1001/jama.2015.119. PMID: 25668261; PMCID: PMC5094173. 4.       Mast AE, Bialkowski W, Bryant BJ, Wright DJ, Birch R, Kiss JE, D'Andrea P, Cable RG, Spencer BR. A randomized, blinded, placebo-controlled trial of education and iron supplementation for mitigation of iron deficiency in regular blood donors. Transfusion. 2016 Jun;56(6 Pt 2):1588-97. doi: 10.1111/trf.13469. Epub 2016 Jan 26. PMID: 26813849; PMCID: PMC4905782. 5.       Patel, E. U., White, J. L., Bloch, E. M., Grabowski, M. K., Gehrie, E. A., Lokhandwala, P. M., Brunker, P., Goel, R., Shaz, B. H., Ness, P. M., & Tobian, A. (2019). Association of blood donation with iron deficiency among adolescent and adult females in the United States: a nationally representative study.  Transfusion ,  59 (5), 1723–1733. https://doi.org/10.1111/trf.15179 6.       Moretti, D., Goede, J. S., Zeder, C., Jiskra, M., Chatzinakou, V., Tjalsma, H., ... & Zimmermann, M. B. (2015). Oral iron supplements increase hepcidin and decrease iron absorption from daily or twice-daily doses in iron-depleted young women. Blood, The Journal of the American Society of Hematology, 126(17), 1981-1989. 7.       Nicole U Stoffel, Colin I Cercamondi, Gary Brittenham, Christophe Zeder, Anneke J Geurts-Moespot, Dorine W Swinkels, Diego Moretti, Michael B Zimmermann. Iron absorption from oral iron supplements given on consecutive versus alternate days and as single morning doses versus twice-daily split dosing in iron-depleted women: two open-label, randomised controlled trials. The Lancet Haematology, Volume 4, Issue 11, 2017, Pages e524-e533, https://doi.org/10.1016/S2352-3026(17)30182-5 . 8.       Cross, J. H., Bradbury, R. S., Fulford, A. J., Jallow, A. T., Wegmüller, R., Prentice, A. M., & Cerami, C. (2015). Oral iron acutely elevates bacterial growth in human serum. Scientific reports, 5, 16670. https://doi.org/10.1038/srep16670

Unclear on Castleman's? Let's learn together in this bullet learning entry. A rare entity with unknown etiology, Castleman’s Disease (CD) is a non-clonal lymphoproliferative disorder that primarily affects lymph nodes and features abundant proliferation of B cells and plasma cells in lymphoid organs. Clinically, CD is classified as unicentric or multicentric, and pathologically it has 4 subtypes: hyaline vascular, plasma cell, mixed, and HHV-8 associated. Current theories are that immune dysregulation, found in chronic inflammation or viral infection, underlies CD, and there is evidence that upregulation of the IL-6 pathway, through over-secretion of IL-6 or over-production of IL-6 receptor, is critical to the pathogenesis of CD. Additionally, HIV is known to be associated with CD, especially the multicentric variant, and almost all cases of HIV-associated CD are HHV-8 positive. Non-HIV-associated CD, or idiopathic CD, features HHV-8 in ~50% of cases.  First line therapy for the more common unicentric CD is surgical resection of the affected lymph node +/- IL-6 inhibition through Tocilizumab, a monoclonal antibody to the IL-6 receptor, or Siltuximab, a monoclonal antibody to IL-6.   Antiviral therapy against HHV-8 has also shown benefit , as have immunomodulatory treatments such as rituximab and interferon-alpha.        References:  Yoshizaki K, et al. The Role of Interleukin-6 in Castleman Disease. Hematol Oncol Clin North Am. 2018 Feb;32(1):23-36. doi: 10.1016/j.hoc.2017.09.003. PMID: 29157617. Ehsan N, Zahra F. Castleman Disease. [Updated 2022 Nov 14]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK576394/ Oksenhendler, E., et al. "The full spectrum of Castleman disease: 273 patients studied over 20 years." British journal of haematology 180.2 (2018): 206-216. Fu, B., et al. Why tocilizumab could be an effective treatment for severe COVID-19?. J Transl Med 18, 164 (2020). https://doi.org/10.1186/s12967-020-02339-3