Vox Sanguinis最新文献

Background and objectives: Cold-stored platelets (CSPs) stored out to 14 days are approved in the United States for use in actively bleeding patients when conventional room temperature-stored platelets are unavailable. Cold storage promotes aggregate formation, yet how specific storage conditions impact aggregate formation remains poorly defined. As CSPs are stored in gas-permeable bags, we investigated how the shelving style (perforated, solid) or label orientation (up, down) affects CSP aggregate formation.

Materials and methods: Single-donor apheresis platelets (N = 17, Trima 100% plasma) were split equally into small-volume platelet storage bags to create four mini-units/donor. These were stored for 14 days (1-6°C) under the following conditions: (i) perforated shelving, label down; (ii) perforated shelving, label up; (iii) solid shelving, label down; and (iv) solid shelving, label up. Units were visually scored for aggregates and assayed for platelet count, mean platelet volume, immature platelet fraction and metabolic parameters. In a subset of units (N = 11 donors), we evaluated surface receptor expression, thrombin generation, aggregation and occlusion under physiologically relevant flow.

Results: Aggregate occurrence was similar across all four storage conditions, and varied more with respect to donor (coefficient of variation [CV] = 116%) than storage condition (CV = 14%). While units stored on solid shelves had statistically significant different metabolic parameters compared to units stored on perforated shelves, phenotypical and functional differences between shelving styles were unremarkable. There were no differences in intrinsic haemostatic function of units under all four conditions.

Conclusion: Aggregate formation in CSPs appears to be donor-dependent, and not impacted by shelf style or label placement.

Background and objectives: Pre-hospital critical care faces challenges in carrying platelet concentrates (PC). Cold-stored platelets (CSP) may offer improved haemostatic function over room temperature platelets. Rapid warming of blood products is crucial for hypothermic trauma patients. This study evaluates whether the°M Warmer System (°MEQU, Copenhagen), used for red cells and intravenous thrombin receptor activator peptide 6 fluids, affects CSP functionality compared to a standard giving set.

Materials and methods: Buffy coat-derived platelets, in a platelet additive solution to plasma ratio of approximately 65:35, were stored at 4 ± 2°C without agitation for 6 days. A baseline measurement was taken on Day 2. On Day 6, a 'pre-sample' was taken; then CSP were either infused through the°MEQU or a standard transfusion-giving set. Platelet function was assessed by aggregation and thromboelastography (TEG). Platelet activation was assessed by CD62P expression, Annexin V binding, microparticle concentration and soluble CD62P concentration. Ten replicates were completed.

Results: Neither aggregation nor TEG showed significant differences between PC infused through the standard set or the rapid blood warmer. Soluble CD62P levels were significantly higher in both the standard giving set (26.7 ± 6.4 ng/mL) and rapid blood warmer (25.9 ± 5.1 ng/mL) compared to the pre-sample (18.8 ± 4.8 ng/mL), with no significant difference between the groups.

Conclusion: The°MEQU did not detrimentally affect platelet quality and functionality compared to a standard giving set, suggesting the feasibility for a CSP clinical trial in the pre-hospital environment.

Background and objectives: We should control free K⁺ during massive transfusion (>80 mL/kg) of red blood cells (RBCs) in small children. To manage this, several national and international guidelines recommend using RBCs stored only up to 7 days. We tested a washing step for RBCs in saline-adenine-glucose-mannitol (SAGM) with or without irradiation to reduce supernatant K⁺ levels, improve quality and potentially extend the shelf life of stored RBCs.

Materials and methods: RBCs of 240-330 mL were prepared from whole blood donations, then split into halves and stored in SAGM solution at 4 ± 2°C for 21 days. RBCs were split and washed on Days 1 and 8, and some were gamma-irradiated on Day 8. Glucose, lactate, lactate dehydrogenase (LDH), adenosine triphosphate (ATP), K⁺ and haemolysis were determined over 21 days.

Results: After washing on Day 1, only glucose and lactate improved, whereas after washing on Day 8, LDH and K⁺ also improved. Irradiation resulted in accelerated K⁺ accumulation and increased haemolysis. Mean extracellular K⁺ concentrations were 21.2 ± 1.03 mM after irradiation on Day 8 versus 1.12 ± 0.05 mM after irradiation plus wash on Day 8, and 38.80 ± 2.13 mM on Day 10 after irradiation on Day 8 and 16.6 ± 0.05 mM on Day 10 after irradiation plus wash on Day 8.

Conclusion: K⁺ concentrations remained <25 mM within 8 days of storage. We recommend irradiation by Day 8 at the latest for neonatal transfusion. The shelf life may be extended by another 48 h if the RBCs are also washed.

Background and objectives: The US Food and Drug Administration guidance for cold-stored platelets (CSPs) permits storage of apheresis platelets at 1-6°C for ≤14 days. During a pilot programme, CSPs were evaluated in a large US blood centre over a 10-month period (September 2023 to July 2024) to better understand the formation of aggregates under routine use.

Materials and methods: Platelets collected in 100% plasma were moved into cold storage within 4 h of collection and shipped to local hospitals. Hospitals returned any units with aggregates to the blood centre. Units were visually inspected and tested for platelet concentration, pH, metabolism and activation parameters. At expiration (Day 14), units were passed through a transfusion filter (170-260 μm) and assessed post-filtration and after 24 h.

Results: Aggregation rates were high initially but decreased to 9% of released CSPs by study conclusion. Fifty-five aggregated units were returned. The majority of units (42%) had a small, flaky phenotype, which did not change over storage. Platelet counts significantly decreased with a 50% drop by expiry. Lactadherin and P-selectin increased, CD63 and CD41/61 complex decreased and there was slower metabolism. Filtration removed all aggregates, except for one unit with small aggregates being observed 24 h post-filtration. Platelet recovery after filtration was 94% ± 26%. Seven repeat donors donated 6 units with no aggregates and 17 units with aggregates, with variable aggregate phenotypes between donations.

Conclusion: This study demonstrates that aggregate phenotypes in CSPs are highly variable and removed effectively by filtration; they appear to arise more from external handling conditions than from any intrinsic product property.

Background and objectives: Severe dry eye disease is a commonly diagnosed condition that can be treated with serum eye drops (SEDs). SEDs are manufactured from the serum obtained from whole-blood donation. Patient information provided with SEDs has not been evaluated so far. This study aims to understand patients' views on SED materials and identify possible improvements.

Materials and methods: The study period was between 1 November 2021 and 30 June 2022. Eligible patients were supplied with either autologous SED (AutoSED) or patient-tailored (allogeneic) SED (PT SED) manufactured by Australian Red Cross Lifeblood. Patients were invited to participate via email or post and completed an online survey or participated in a semi-structured telephone interview.

Results: A total of 64 patients supplied with AutoSED and 18 with PT SED completed the survey, of whom 10 and 8, respectively, were interviewed. More AutoSED (89.1%) than PT SED (58.8%) patients reported that the instructions on the carton were helpful. More AutoSED patients (78.1%) than PT SED (55.6%) reported receiving the SED brochure and that the information was easy to understand. Information on how to dispose the eye drops and the risk of treatment was easy to understand. Sixteen patients reported accessing the quick-response code to view the SED video and indicated that it was easy to understand.

Conclusion: Patient views on the materials provided with SEDs were generally positive. Suggested improvements included changing the location of sealing stickers on the carton, providing further detailed information on shelf-life after power supply challenges and natural disasters and storage and handling during travel.

Blood transfusions are vital in health care, yet maintaining an adequate and safe blood supply remains a significant challenge. To address blood donation-associated challenges, this review explores how integrating artificial intelligence (AI) technologies can improve donor recruitment, retention and management. For instance, robotic process automation can streamline repetitive administrative tasks, allowing staff to focus on more critical activities and improving efficiency. When augmented with AI techniques such as machine learning (ML) and natural language processing, it transitions from static rule-based automation to intelligent process automation. This combination enables dynamic decision making, handling unstructured data and optimizing workflows, thus extending its role in improving efficiency and decision making in donor management. ML algorithms can analyse large datasets to predict future donation patterns, identify donor behaviour trends and forecast blood demand more accurately. By applying these predictive models, blood banks can plan more effectively, avoid shortages and precisely target recruitment efforts. Additionally, AI-driven chatbots are gaining traction as a tool for improving communication with potential and existing donors, ultimately fostering better retention rates. Beyond routine donor management, AI also shows promise in supporting rare donor identification and targeted engagement strategies. While these innovations hold great potential, their implementation faces challenges such as data availability and quality, ethical issues concerning AI utilization, the necessity for clinical and technical expertise, a robust infrastructure, environmental impact and cybersecurity risks. Addressing these issues through practical strategies and thoughtful integration will be the key to ensuring the responsible, effective and sustainable adoption of AI in blood banking systems.

Background and objectives: Screening for transfusion-transmitted infections (TTIs) among blood donors is done using qualitative screening assays. Screening values that are close to cut-off values lie in the uncertainty zone, often denoted as the grey zone (GZ). This scoping review evaluated studies that have assessed the GZ reactivity by supplementary tests and its consequences.

Materials and methods: Studies evaluating GZ or indeterminate or inconclusive results for TTI screening among blood donors were searched using PubMed, Scopus and Google Scholar databases. Full text for the included articles was reviewed and analysed for study characteristics, TTI screening and GZ reactivity. This included GZ range, repeat or confirmatory testing, follow-up of such donors, effect on donor deferral and collected blood units.

Results: A total of 16 studies were included. GZ was evaluated for human immunodeficiency virus (HIV), hepatitis B virus (HBV), hepatitis C virus (HCV), syphilis, Chagas disease and human T-lymphotropic virus (HTLV). GZ values ranged from 0.5 to 1.2 times sample to cut-off (S/CO) values in different studies. The protocol for repeat/confirmatory testing was also heterogeneous. During repeat testing, many donors were found to be reactive or repeat GZ reactive. In confirmatory assays, the majority were negative, but many were positive or indeterminate. The protocol for donor follow-up and deferral protocols also varied significantly among different centres.

Conclusion: GZ evaluation showed a small yet significant risk of TTI from samples identified within the GZ range. There is further need for follow-up studies to establish TTI risk from repeat reactive or indeterminate samples, which will help in establishing uniform protocols for GZ samples.

Background and objectives: Blood donor return behaviour is frequently examined through questionnaires assessing donors' motivations, attitudes, awareness and willingness to donate. An enhanced donor invitation model that better predicts donation dynamics using specific behavioural variables is needed. This study aims to incorporate machine learning into processing blood donor datasets, thereby increasing donor return rates through precision marketing.

Materials and methods: This retrospective study was conducted between 1 January 2022 and 31 December 2023, focusing on blood donors whose records were maintained by the Kaohsiung Blood Center in Taiwan. Three machine learning models (MLMs), namely eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost), were employed. Each model underwent cross-validation, and their performance was evaluated using accuracy, average precision, balanced accuracy, F1 score and log loss. The best performing model was selected to generate predictive donor return lists, which were subsequently tested.

Results: All three MLMs demonstrated strong predictive power in generating donor return prediction lists. The performance metrics for the three models were as follows: accuracy: 0.8093, 0.8096 and 0.8106; specificity: 0.9227, 0.9256 and 0.9229. CatBoost was found to be the best performing model. The most influential predictive factors were return donation interval and donation location. Results showed a significant improvement in donor return rates (57.99% vs. 15.54%, p < 0.0001).

Conclusion: MLMs leveraging both behavioural and demographic variables can predict and identify high-return-rate donors by prioritizing return thresholds. Precision marketing significantly improves donor return rates, enabling blood banks to rapidly meet transfusion demands during emergencies.

Background and objectives: Because of inherent differences, reports on paediatric transfusion reactions are more heterogeneous than those seen in the adult population. In this study, we aimed to prospectively (active haemovigilance) study the incidence, clinical presentation and factors influencing transfusion reactions among paediatric patients.

Materials and methods: This was a prospective descriptive study in a teaching children's hospital from the public healthcare system in North India over 1 year. The study involved active monitoring, reporting and analysis of the data related to acute transfusion reactions (i.e., within 24 h of transfusion).

Results: During the study period, there were a total of 5198 transfusions in 1401 paediatric patients (876 male; 525 female); among them, 621 patients received multiple transfusions. A total of 93 acute transfusion reactions were analysed (1.7 for every 100 paediatric transfusions and 6.6 for every 100 paediatric patients transfused) with similar incidences in both genders. Febrile non-haemolytic transfusion reaction (FNHTR; n = 80), followed by allergic reaction (n = 12), was the most common transfusion reaction reported. The incidence of transfusion reactions was significantly higher (p < 0.05) in patients with a history of previous transfusion (12.7) compared to patients receiving transfusion for the first time (1.7). Overall, the majority of transfusion reactions in paediatric populations were due to platelet transfusions (49% of all reported reactions). The majority of FNHTRs were reported with red cell transfusions (51%), whereas the majority of allergic reactions were due to platelet transfusions (63.6%).

Conclusion: The study highlights the need for active surveillance to accurately report and study the factors influencing transfusion reactions in paediatric patients.

Background and objectives: Prehospital transfusion is now increasingly used in civilian and military medicine. Blood products are, however, perishable and rarely needed in civilian settings. Given the rapid development of drone-based logistics and Finland's low population density, we aimed to build a computational framework to assess the feasibility and requirements of drone-based delivery of blood products to trauma sites. Unlike previous studies, which focus mostly on deliveries to hospitals in compact urban areas, we model direct deliveries to trauma scenes across an entire sparsely populated country.

Materials and methods: We used predicted trauma data on a 1 × 1 km grid covering Finland. Drone base locations were optimized using mixed-integer linear programming, and drone operations were analysed with a discrete event simulation model. Our approach combines strategic location optimization with operational-level simulation and is grounded in high-resolution, real-world data-driven trauma demand estimates.

Results: With 20 base locations and drones capable of a 60-km delivery range, over 80% of predicted trauma events can be reached. If drones can return to base, one drone per base is typically sufficient due to the rarity of missions.

Conclusions: We present a novel computational framework for simulating drone-based blood delivery to trauma scenes. Our results suggest that while current drone capabilities may still be limited, the approach is promising for countries with similar geography. The framework is adaptable and can support planning in other regions with reliable trauma demand data.