Yazer, Mark H

Abstract Background Substituting group A whole blood (GAWB) might relieve some of the burden on the low titer group O whole blood (LTOWB) inventory. This simulation examined the effect of implementing GAWB at a large trauma hospital. Study Design and Methods A civilian trauma center with LTOWB and GAWB par levels set to 22 and 10 units, respectively, was modeled as the baseline. The average daily number of WB recipients was 0.5 who received an average of four WB units per patient. LTOWB was issued in packages of five and all had to be consumed before a group A patient could be switched to GAWB. Several variations on the baseline simulation were also modeled. Results In the baseline simulation, there was a median (interquartile range, IQR) of 1 (0–2) GAWB and 16 (13–19) LTOWB recipients per month. The median (IQR) GAWB and LTOWB units transfused per month was 2 (0–9) and 56 (42–72), respectively. Fourteen percent of group A patients received any quantity of GAWB. The variations that had the most impact on GAWB usage included increasing the number of WB recipients to 2.5 per day where the median (IQR) monthly number of GAWB recipients and units transfused increased to 4 (3–5) recipients and 21 (12–29) units, respectively, and when the average WB requirements increased to eight units per patient resulting in transfusing a median (IQR) of 10 (5–15) GAWB units per month to 3 (1–4) recipients. Discussion Under routine civilian hospital circumstances, implementing GAWB will have a modest impact on LTOWB inventory.

Abstract Artificial intelligence (AI) and machine learning (ML) are beginning to enhance key workflows across blood banking (BB) and transfusion medicine (TM), including donor engagement, inventory forecasting, immunohaematology interpretation, haemovigilance and clinical decision support. These tools can extract signals from large, diverse datasets to improve efficiency, consistency and timeliness of care while enabling more proactive patient blood management. At the same time, TM is uniquely sensitive to safety and trust, so the field must pair innovation with disciplined validation and governance. This review surveys emerging applications and distils a balanced ethics and oversight framework tailored to TM and BB practice. Core elements include outcome‐focused validation and continuous monitoring; targeted fairness testing where biological or scientific plausibility suggests subgroup differences; layered transparency that distinguishes transparency, interpretability and explainability; and privacy by design with proportionate consent. We emphasize human oversight at every step: clinicians and laboratorians evaluate, monitor and troubleshoot models, perform tasks AI cannot, integrate multiple inputs to make decisions and interact with AI through guardrails such as intended‐use statements, confidence thresholds and clear override pathways. Accountability is shared across users, service directors, institutions and regulators. When implemented with these safeguards, AI can reduce preventable errors, improve resource allocation and support more equitable access to safe transfusion. The goal is principled pragmatism that protects patients and donors while enabling timely adoption of well‐validated tools.

AbstractBackgroundWhole blood (WB) is carried by special operations forces as part of a remote damage control resuscitation strategy. The effects of an underwater mission on the quality and coagulation profile of WB were simulated by exposure to hyperbaric pressures in a chamber.MethodsWB units collected in CPDA‐1 were exposed to three different combinations of hyperbaric pressure and duration of exposure: Group A 153.52 kPa (15.24 msw; 1.52 atm) for 4 h; n = 9, Group B 506.63 kPa (50.29 msw; 5.00 atm) for 1 h; n = 9, Group C 153.52 kPa (15.24 msw; 1.52 atm) for 1 h; n = 7. The following parameters were measured on each unit: prothrombin time/international normalized ratio, activated partial thromboplastin time, thromboelastography and concentration determinations of platelets, lactate, fibrinogen, and lactate dehydrogenase. Each sample underwent baseline, prepressurization, immediate postpressurization, and 6 h postpressurization laboratory testing.ResultsSix hours following hyperbaric exposure, the lactate concentration in group C was higher than prepressurization measurement and the platelet concentration in Group A was lower than prepressurization measurement. There were no changes in any of the other analyzed biochemical, coagulation and thromboelastogram parameters following exposure to hyperbaric stress.DiscussionThese data suggest that pressurization of WB up to 5 atm did not impact parameters tested. Changes observed in lactate and platelet count need further study, as well as complementary testing of red blood cell integrity. Further investigation of the hyperbaric extremes is necessary to determine if there is a damage inducing pressure to which WB should not be exposed.

AbstractBackgroundMass casualty incidents (MCIs) create an immediate surge in blood product demand. We hypothesize local inventories in major U.S. cities would not meet this demand.Study Design and MethodsA simulated blast in a large crowd estimated casualty numbers. Ideal resuscitation was defined as equal amounts of red blood cells (RBCs), plasma, platelets, and cryoprecipitate. Inventory was prospectively collected from six major U.S. cities at six time points between January and July 2019. City‐wide blood inventories were classified as READY (>1 U/injured survivor), DEFICIENT (<10 U/severely injured survivor), or RISK (between READY and DEFICIENT), before and after resupply from local distribution centers (DC), and features of DEFICIENT cities were identified.ResultsThe simulated blast resulted in 2218 injured survivors including 95 with severe injuries. Balanced resuscitation would require between 950 and 2218 units each RBC, plasma, platelets and cryoprecipitate. Inventories in 88 hospitals/health systems and 10 DCs were assessed. Of 36 city‐wide surveys, RISK inventories included RBCs (n = 16; 44%), plasma (n = 24; 67%), platelets (n = 6; 17%), and cryoprecipitate (n = 22; 61%) while DEFICIENT inventories included platelets (n = 30; 83%) and cryoprecipitate (n = 12; 33%). Resupply shifted most RBC and plasma inventories to READY, but some platelet and cryoprecipitate inventories remained at RISK (n = 24; 67% and n = 12; 33%, respectively) or even DEFICIENT (n = 11; 31% and n = 6; 17%, respectively). Cities with DEFICIENT inventories were smaller (p <.001) with fewer blood products per trauma bed (p <.001).DiscussionIn this simulated blast event, blood product demand exceeded local supply in some major U.S. cities. Options for closing this gap should be explored to optimize resuscitation during MCIs.