Faculty Bibliography

BACKGROUND:Each year the AABB Clinical Transfusion Medicine Committee (CTMC) procures a synopsis highlighting new, important, and clinically relevant studies in the field of transfusion medicine (TM). This has been made available as a publication in Transfusion since 2018. METHODS:CTMC members reviewed and identified original manuscripts covering TM-related topics published electronically (ahead-of-print) or in print from December 2020 to December 2021. Selection of publications was discussed at committee meetings and chosen based on perceived relevance and originality. Next, committee members worked in pairs to create a synopsis of each topic, which was then reviewed by additional committee members. The first and senior authors assembled the final manuscript. Although this synopsis is extensive, it is not exhaustive, and some articles may have been excluded or missed. RESULTS:The following topics are included: blood products; convalescent plasma; donor collections and testing; hemoglobinopathies; immunohematology and genomics; hemostasis; patient blood management; pediatrics; therapeutic apheresis; and cell therapy. CONCLUSIONS:This synopsis highlights and summarizes recent key developments in TM and may be useful for educational purposes.

BACKGROUND:We developed a simple tool to estimate the probability of dying from acute COVID-19 illness only with readily available assessments at initial admission. METHODS:This retrospective study included 13,190 racially and ethnically diverse adults admitted to one of the New York City Health + Hospitals (NYC H+H) system for COVID-19 illness between March 1 and June 30, 2020. Demographic characteristics, simple vital signs and routine clinical laboratory tests were collected from the electronic medical records. A clinical prediction model to estimate the risk of dying during the hospitalization were developed. RESULTS:Mean age (interquartile range) was 58 (45-72) years; 5421 (41%) were women, 5258 were Latinx (40%), 3805 Black (29%), 1168 White (9%), and 2959 Other (22%). During hospitalization, 2,875 were (22%) died. Using separate test and validation samples, machine learning (Gradient Boosted Decision Trees) identified eight variables-oxygen saturation, respiratory rate, systolic and diastolic blood pressures, pulse rate, blood urea nitrogen level, age and creatinine-that predicted mortality, with an area under the ROC curve (AUC) of 94%. A score based on these variables classified 5,677 (46%) as low risk (a score of 0) who had 0.8% (95% confidence interval, 0.5-1.0%) risk of dying, and 674 (5.4%) as high-risk (score ≥ 12 points) who had a 97.6% (96.5-98.8%) risk of dying; the remainder had intermediate risks. A risk calculator is available online at https://danielevanslab.shinyapps.io/Covid_mortality/. CONCLUSIONS:In a diverse population of hospitalized patients with COVID-19 illness, a clinical prediction model using a few readily available vital signs reflecting the severity of disease may precisely predict in-hospital mortality in diverse populations and can rapidly assist decisions to prioritize admissions and intensive care.

Importance/UNASSIGNED:There is clinical equipoise for COVID-19 convalescent plasma (CCP) use in patients hospitalized with COVID-19. Objective/UNASSIGNED:To determine the safety and efficacy of CCP compared with placebo in hospitalized patients with COVID-19 receiving noninvasive supplemental oxygen. Design, Setting, and Participants/UNASSIGNED:CONTAIN COVID-19, a randomized, double-blind, placebo-controlled trial of CCP in hospitalized adults with COVID-19, was conducted at 21 US hospitals from April 17, 2020, to March 15, 2021. The trial enrolled 941 participants who were hospitalized for 3 or less days or presented 7 or less days after symptom onset and required noninvasive oxygen supplementation. Interventions/UNASSIGNED:A unit of approximately 250 mL of CCP or equivalent volume of placebo (normal saline). Main Outcomes and Measures/UNASSIGNED:The primary outcome was participant scores on the 11-point World Health Organization (WHO) Ordinal Scale for Clinical Improvement on day 14 after randomization; the secondary outcome was WHO scores determined on day 28. Subgroups were analyzed with respect to age, baseline WHO score, concomitant medications, symptom duration, CCP SARS-CoV-2 titer, baseline SARS-CoV-2 serostatus, and enrollment quarter. Outcomes were analyzed using a bayesian proportional cumulative odds model. Efficacy of CCP was defined as a cumulative adjusted odds ratio (cOR) less than 1 and a clinically meaningful effect as cOR less than 0.8. Results/UNASSIGNED:Of 941 participants randomized (473 to placebo and 468 to CCP), 556 were men (59.1%); median age was 63 years (IQR, 52-73); 373 (39.6%) were Hispanic and 132 (14.0%) were non-Hispanic Black. The cOR for the primary outcome adjusted for site, baseline risk, WHO score, age, sex, and symptom duration was 0.94 (95% credible interval [CrI], 0.75-1.18) with posterior probability (P[cOR<1] = 72%); the cOR for the secondary adjusted outcome was 0.92 (95% CrI, 0.74-1.16; P[cOR<1] = 76%). Exploratory subgroup analyses suggested heterogeneity of treatment effect: at day 28, cORs were 0.72 (95% CrI, 0.46-1.13; P[cOR<1] = 93%) for participants enrolled in April-June 2020 and 0.65 (95% CrI, 0.41 to 1.02; P[cOR<1] = 97%) for those not receiving remdesivir and not receiving corticosteroids at randomization. Median CCP SARS-CoV-2 neutralizing titer used in April to June 2020 was 1:175 (IQR, 76-379). Any adverse events (excluding transfusion reactions) were reported for 39 (8.2%) placebo recipients and 44 (9.4%) CCP recipients (P = .57). Transfusion reactions occurred in 2 (0.4) placebo recipients and 8 (1.7) CCP recipients (P = .06). Conclusions and Relevance/UNASSIGNED:In this trial, CCP did not meet the prespecified primary and secondary outcomes for CCP efficacy. However, high-titer CCP may have benefited participants early in the pandemic when remdesivir and corticosteroids were not in use. Trial Registration/UNASSIGNED:ClinicalTrials.gov Identifier: NCT04364737.

BACKGROUND:The AABB Clinical Transfusion Medicine Committee (CTMC) compiles an annual synopsis of the published literature covering important developments in the field of transfusion medicine (TM), which has been made available as a manuscript published in Transfusion since 2018. METHODS:CTMC committee members reviewed original manuscripts including TM-related topics published electronically (ahead) or in print from December 2019 to December 2020. The selection of topics and manuscripts was discussed at committee meetings and chosen based on relevance and originality. Next, committee members worked in pairs to create a synopsis of each topic, which was then reviewed by two additional committee members. The first and senior authors of this manuscript assembled the final manuscript. Although this synopsis is extensive, it is not exhaustive, and some papers may have been excluded or missed. RESULTS:The following topics are included: COVID-19 effects on the blood supply and regulatory landscape, COVID convalescent plasma, adult transfusion practices, whole blood, molecular immunohematology, pediatric TM, cellular therapy, and apheresis medicine. CONCLUSIONS:This synopsis provides easy access to relevant topics and may be useful as an educational tool.

The ABO blood group system includes phenotypes, or subgroups, that differ in the amount of A and B antigens present on the red blood cells (RBCs). These subgroups also differ in the A, B, or H substances present in secretions (for individuals who have the secretor phenotype). B subgroups are very rare and are less frequently reported than A subgroups. Usually, B subgroups are discovered during serologic testing when there is a discrepancy between RBC and serum grouping results. Subgroups of B are usually identified by a reference laboratory using molecular and adsorption-elution methods. This report details a case of a young, healthy, pregnant woman with a B subgroup detected by a small transfusion service using adsorption-elution methods. Serology and genotyping of the ABO gene was performed at a reference laboratory where the serology was consistent with a B subgroup, but no changes were identified in ABO gene sequencing. It is important to correctly identify B subgroups in donors and recipients to help resolve ABO discrepancies and potentially prevent ABO incompatibility in blood transfusion, thus minimizing transfusion reactions.

Background/Case Studies: The COVID-19 pandemic has altered almost everything. The first case of COVID-19 was confirmed in New York (NY) on 3/1/20. As of 6/30, there were >212,000 confirmed cases, >50,000 patients hospitalized, and >18000 confirmed and >4600 probable deaths in NYC. The governor declared a state of emergency on 3/7. Social distancing and mandatory quarantines implemented on 3/12 have resulted in dramatic reductions in the blood supply. To preserve the blood supply and available hospital beds, all elective surgery was canceled effective 3/16. I sought to assess the usage of blood products in our hospitalized confirmed and suspected COVID-19 patients. Study Design/Methods: After obtaining IRB approval, an Epic report to identify all patients, who had a positive SARS-CoV-2 PCR test result and were transfused from 3/1/20 to 6/30/20, was created to identify how many COVID-19 patients had been transfused and the number and type of blood products they received. Results/Findings: From 3/1-6/30, 993 patients tested positively for COVID-19. 1669 confirmed and suspected patients had been admitted to the hospital, 1361 had been discharged (excluding deaths), and 253 had died. Of the admitted confirmed COVID-19 patients, 121 patients were transfused at least one blood product. A massive transfusion protocol was activated on 3 patients. A total of 519 RBCs, 78 SDPs, 40 plasmas, and 15 pooled cryoprecipitate (CRYO) units were transfused to COVID-19 patients. Table 1 depicts the mean number, range, and percent of transfusions by product type administered to COVID-19 patients.
Conclusion(s): 121 COVID-19 patients were transfused a total of 652 blood products. 21.8% of all blood products during the period were transfused to COVID-19 patients. COVID-19 patients received 23.6% of RBCs, 16.8% of plasmas, 24.2% of SDPs, and 21.4% of pooled CRYO transfused in the hospital. Although their needs were only a portion of the hospital's overall blood usage, maintaining an ample blood inventory is required to support the care of COVID-19 patients especially those requiring ECMO and long-term mechanical ventilation

BACKGROUND:New York City (NYC) bore the greatest burden of COVID-19 in the United States early in the pandemic. In this case series, we describe characteristics and outcomes of racially and ethnically diverse patients tested for and hospitalized with COVID-19 in New York City's public hospital system. METHODS:We reviewed the electronic health records of all patients who received a SARS-CoV-2 test between March 5 and April 9, 2020, with follow up through April 16, 2020. The primary outcomes were a positive test, hospitalization, and death. Demographics and comorbidities were also assessed. RESULTS:22254 patients were tested for SARS-CoV-2. 13442 (61%) were positive; among those, the median age was 52.7 years (interquartile range [IQR] 39.5-64.5), 7481 (56%) were male, 3518 (26%) were Black, and 4593 (34%) were Hispanic. Nearly half (4669, 46%) had at least one chronic disease (27% diabetes, 30% hypertension, and 21% cardiovascular disease). Of those testing positive, 6248 (46%) were hospitalized. The median age was 61.6 years (IQR 49.7-72.9); 3851 (62%) were male, 1950 (31%) were Black, and 2102 (34%) were Hispanic. More than half (3269, 53%) had at least one chronic disease (33% diabetes, 37% hypertension, 24% cardiovascular disease, 11% chronic kidney disease). 1724 (28%) hospitalized patients died. The median age was 71.0 years (IQR 60.0, 80.9); 1087 (63%) were male, 506 (29%) were Black, and 528 (31%) were Hispanic. Chronic diseases were common (35% diabetes, 37% hypertension, 28% cardiovascular disease, 15% chronic kidney disease). Male sex, older age, diabetes, cardiac history, and chronic kidney disease were significantly associated with testing positive, hospitalization, and death. Racial/ethnic disparities were observed across all outcomes. CONCLUSIONS AND RELEVANCE/CONCLUSIONS:This is the largest and most racially/ethnically diverse case series of patients tested and hospitalized for COVID-19 in New York City to date. Our findings highlight disparities in outcomes that can inform prevention and testing recommendations.

To limit introduction of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), the United States restricted travel from China on February 2, 2020, and from Europe on March 13. To determine whether local transmission of SARS-CoV-2 could be detected, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) conducted deidentified sentinel surveillance at six NYC hospital emergency departments (EDs) during March 1-20. On March 8, while testing availability for SARS-CoV-2 was still limited, DOHMH announced sustained community transmission of SARS-CoV-2 (1). At this time, twenty-six NYC residents had confirmed COVID-19, and ED visits for influenza-like illness* increased, despite decreased influenza virus circulation.^† The following week, on March 15, when only seven of the 56 (13%) patients with known exposure histories had exposure outside of NYC, the level of community SARS-CoV-2 transmission status was elevated from sustained community transmission to widespread community transmission (2). Through sentinel surveillance during March 1-20, DOHMH collected 544 specimens from patients with influenza-like symptoms (ILS)^§ who had negative test results for influenza and, in some instances, other respiratory pathogens.^¶ All 544 specimens were tested for SARS-CoV-2 at CDC; 36 (6.6%) tested positive. Using genetic sequencing, CDC determined that the sequences of most SARS-CoV-2-positive specimens resembled those circulating in Europe, suggesting probable introductions of SARS-CoV-2 from Europe, from other U.S. locations, and local introductions from within New York. These findings demonstrate that partnering with health care facilities and developing the systems needed for rapid implementation of sentinel surveillance, coupled with capacity for genetic sequencing before an outbreak, can help inform timely containment and mitigation strategies.

BACKGROUND:The AABB Clinical Transfusion Medicine Committee (CTMC) compiles an annual synopsis of the published literature covering important developments in the field of transfusion medicine (TM) for the board of director's review. This synopsis is now made available as a manuscript published in TRANSFUSION. STUDY DESIGN AND METHODS/METHODS:CTMC committee members review original manuscripts including TM-related topics published in different journals between late 2018 and 2019. The selection of topics and manuscripts are discussed at committee meetings and are chosen based on relevance and originality. After the topics and manuscripts are selected, committee members work in pairs to create a synopsis of the topics, which is then reviewed by two committee members. The first and senior authors of this manuscript assembled the final manuscript. Although this synopsis is comprehensive, it is not exhaustive, and some papers may have been excluded or missed. RESULTS:The following topics are included: infectious risks to the blood supply, iron donor studies, pre-transfusion testing interference and genotyping, cold agglutinin disease (CAD), HLA alloimmunization in platelet transfusions, patient blood management, updates to TACO and TRALI definitions, pediatric TM, and advances in apheresis medicine. CONCLUSION/CONCLUSIONS:This synopsis provides easy access to relevant topics and may be useful as an educational tool.

Background: An ABO blood group subtype is called a subgroup and/or variant. Subgroups of ABO are often distinguished by decreased amounts of A, B or O (H) antigens on red blood cells. Blood type A appears to have the most variation in subgroups. In general, serologic distinction between A1 and other subgroups of A is based on the ability of anti- A1 lectin (an extract of Dolichos biflorus seeds) to agglutinate A1 red blood cells (RBC) but not cells of other A subgroups. As A2 is most common A subtype and is frequently detected at regular hospital transfusion services. Definitive identification of ABO subgroups is usually performed at a reference laboratory using molecular techniques and special immunohematology methods. Here we report an interesting case where a subgroup B was detected by an astute technologist using manual immunohematology tests and conventional reagents at our hospital transfusion service. Our hospital transfusion service received a blood specimen requesting a type and screen from a pregnant woman with no known medical problems. Testing the specimen showed a front type of O and a back type of B, with a negative antibody screening.
Aim(s): To resolve the typing discrepancy and to correctly Identify the ABO blood type of the pregnant patient.
Method(s): In an attempt to enhance the typing reactions with the patient's RBCs and plasma, mixtures of the front typing and back typing were incubated separately for 15 minutes at room temperature. This however did not result in any change in reactivity. The technologist became suspicious of a possible B subgroup as this was a healthy young woman and it would be rare for such a young patient to exhibit missing antibodies in the reverse type. He then performed a DAT on the specimen to assure that nothing was coating the patient's RBCs which might interfere with further testing. The DAT was negative for IgG and C3d. He subsequently performed an absorption on vigorously washed patient RBC) with anti-B reagent from Ortho. The reaction mixture was incubated at room temperature (RT) for 15 minutes, followed by an elution. The eluate was added to washed A cells, B cells, and screening cells (Ortho), and then incubated at room temperature for 15 minutes. The mixtures were washed with eluate washing solution. Anti-IgG Coombs reagent was added, the tubes were centrifuged, and results were recorded.
Result(s): A cells: Negative B cells: 2 + Screen cell #1: negative Screen cell #2: negative Screen cell #3: negative Summary/Conclusions: Based on the manual tests the technologist designed and performed, he was able to demonstrate the 2 + reactivity with type B reagent RBCs and concluded that the patient's blood type is a B subgroup. The patient's specimen was then sent to New York Blood Center Immunohematology Reference Laboratory for further confirmation and identification. The B group of the patient's RBCs was not detectable again by the conventional immunohematology tests. Molecular tests (PCR-RFLP) and full gene sequencing were performed. A B allele (*B1.01) and an O1 allele (*O1.09) were identified, which predicts a B weak subtype. The molecular testing confirms the conclusion made by our technologist using conventional manual immunohematology tests