Sara Trompeter

Patients with β-thalassemia major (BTM) require regular blood transfusions, supported by appropriate iron chelation therapy (ICT), throughout their life. β-thalassemia is a global disease that is most highly prevalent in Southeast Asia, Africa, and Mediterranean countries. However, the global distribution of patients with β-thalassemia is changing due to population migration, and Northern European countries now have significant thalassemia populations. Globally, many patients with BTM have limited access to regular and safe blood transfusions. A lack of voluntary nonremunerated blood donors, poor awareness of thalassemia, a lack of national blood policies, and fragmented blood services contribute to a significant gap between the timely supply of, and demand for, safe blood. In many centers, there is inadequate provision of antigen testing, even for common red cell antigens such as CcEe and Kell. Policies to raise awareness and increase the use of red blood cell antigen testing and requesting of compatible blood in transfusion centers are needed to reduce alloimmunization (the development of antibodies to red blood cell antigens), which limits the effectiveness of transfusions and the potential availability of blood. Patients with BTM are also at risk of transfusion-transmitted infections unless appropriate blood screening and safety practices are in place. Hence, many patients are not transfused or are undertransfused, resulting in decreased health and quality-of-life outcomes. Hemovigilance, leukoreduction, and the ability to thoroughly investigate transfusion reactions are often lacking, especially in resource-poor countries. ICT is essential to prevent cardiac failure and other complications due to iron accumulation. Despite the availability of potentially inexpensive oral ICT, a high proportion of patients suffer complications of iron overload and die each year due to a lack of, or inadequate, ICT. Increased awareness, training, and resources are required to improve and standardize adequate blood transfusion services and ICT among the worldwide population of patients with BTM. ICT needs to be available, affordable, and correctly prescribed. Effective, safe, and affordable new treatments that reduce the blood transfusion burden in patients with β-thalassemia remain an unmet need.

PURPOSE: To explore the use and reproducibility of magnetic resonance-derived myocardial T1 mapping in patients with iron overload. MATERIALS AND METHODS: The research received ethics committee approval and all patients provided written informed consent. This was a prospective study of 88 patients and 67 healthy volunteers. Thirty-five patients underwent repeat scanning for reproducibility. T1 mapping used the shortened modified Look-Locker inversion recovery sequence (ShMOLLI) with a second, confirmatory MOLLI sequence in the reproducibility group. T2 * was performed using a commercially available sequence. The analysis of the T2 * interstudy reproducibility data was performed by two different research groups using two different methods. RESULTS: Myocardial T1 was lower in patients than healthy volunteers (836 ± 138 msec vs. 968 ± 32 msec, P < 0.0001). Myocardial T1 correlated with T2 * (R = 0.79, P < 0.0001). No patient with low T2 * had normal T1 , but 32% (n = 28) of cases characterized by a normal T2 * had low myocardial T1 . Interstudy reproducibility of either T1 sequence was significantly better than T2 *, with the results suggesting that the use of T1 in clinical trials could decrease potential sample sizes by 7-fold. CONCLUSION: Myocardial T1 mapping is an alternative method for cardiac iron quantification. T1 mapping shows the potential for improved detection of mild iron loading. The superior reproducibility of T1 has potential implications for clinical trial design and therapeutic monitoring.

For healthcare datasets, it is often impossible to combine data samples from multiple sites due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of powerful machine learning algorithms without requiring the pooling of data. Healthcare data have many simultaneous challenges, such as highly siloed data, class imbalance, missing data, distribution shifts, and non-standardized variables, that require new methodologies to address. Federated learning adds significant methodological complexity to conventional centralized machine learning, requiring distributed optimization, communication between nodes, aggregation of models, and redistribution of models. In this systematic review, we consider all papers on Scopus published between January 2015 and February 2023 that describe new federated learning methodologies for addressing challenges with healthcare data. We reviewed 89 papers meeting these criteria. Significant systemic issues were identified throughout the literature, compromising many methodologies reviewed. We give detailed recommendations to help improve methodology development for federated learning in healthcare.

Each year, blood transfusions save millions of lives. However, under current blood-matching practices, sensitization to non-self-antigens is an unavoidable adverse side effect of transfusion. We describe a universal donor typing platform that could be adopted by blood services worldwide to facilitate a universal extended blood-matching policy and reduce sensitization rates. This DNA-based test is capable of simultaneously typing most clinically relevant red blood cell (RBC), human platelet (HPA), and human leukocyte (HLA) antigens. Validation was performed, using samples from 7927 European, 27 South Asian, 21 East Asian, and 9 African blood donors enrolled in 2 national biobanks. We illustrated the usefulness of the platform by analyzing antibody data from patients sensitized with multiple RBC alloantibodies. Genotyping results demonstrated concordance of 99.91%, 99.97%, and 99.03% with RBC, HPA, and HLA clinically validated typing results in 89 371, 3016, and 9289 comparisons, respectively. Genotyping increased the total number of antigen typing results available from 110 980 to >1 200 000. Dense donor typing allowed identification of 2 to 6 times more compatible donors to serve 3146 patients with multiple RBC alloantibodies, providing at least 1 match for 176 individuals for whom previously no blood could be found among the same donors. This genotyping technology is already being used to type thousands of donors taking part in national genotyping studies. Extraction of dense antigen-typing data from these cohorts provides blood supply organizations with the opportunity to implement a policy of genomics-based precision matching of blood.

Faced with the rapidly evolving COVID-19 pandemic, in March 2020 the UK Government advocated strict self-isolation ('shielding') to protect extremely vulnerable patient groups deemed at high risk of severe SARS-CoV-2 infection. 1 These included children and adults with sickle cell anemia (HbSS). On the advice of the National Hemoglobinopathy Panel (NHP), a multidisciplinary expert advisory group, shielding guidance was extended to all sickle cell disease (SCD) sub-types. Patients with transfusion dependent (TDT) and non-transfusion dependent thalassemia (NTDT), Diamond-Blackfan anemia (DBA) and other rare inherited anemias were also advised to shield if considered at high risk based on agreed clinical criteria. These included severe iron overload, splenectomy, diabetes and cardiac disease. 2 Data provided by two participating centers with the largest thalassemia cohorts indicate up to 30% of patients meet these criteria.