Sickle cell disease (SCD) is an inherited red blood cell disorder caused by a structural abnormality of hemoglobin called sickle hemoglobin (HbS). Clinical manifestations of SCD are mainly characterized by chronic hemolysis and acute vaso-occlusive crisis, which are responsible for severe acute and chronic organ damage. SCD is widespread in sub-Saharan Africa, in the Middle East, Indian subcontinent, and some Mediterranean regions. With voluntary population migrations, people harboring the HbS gene have spread globally. In 2006, the World Health Organization recognized hemoglobinopathies, including SCD, as a global public health problem and urged national health systems worldwide to design and establish programs for the prevention and management of SCD. Herein we describe the historical experience of the network of hemoglobinopathy centers and their approach to SCD in Italy, a country where hemoglobinopathies have a high prevalence and where SCD, associated with different genotypes including ß-thalassemia, is present in the native population.

Background. The E-MIOT (Extension-Myocardial Iron Overload in Thalassemia) project is an Italian Network assuring high-quality quantification of tissue iron overload by magnetic resonance imaging (MRI). We evaluated the impact of the COVID-19 pandemic on E-MIOT services. Methods. The activity of the E-MIOT Network MRI centers in the year 2020 was compared with that of 2019. A survey evaluated whether the availability of MRI slots for patients with hemoglobinopathies was reduced and why. Results. The total number of MRI scans was 656 in 2019 and 350 in 2020, with an overall decline of 46.4% (first MRI: 71.7%, follow-up MRI: 36.9%), a marked decline (86.9%) in the period March–June 2020, and a reduction in the gap between the two years in the period July–September. A new drop (41.4%) was recorded in the period October–December for two centers, due to the general reduction in the total amount of MRIs/day for sanitization procedures. In some centers, patients refused MRI scans for fear of getting COVID. Drops in the MRI services >80% were found for patients coming from a region without an active MRI site. Conclusions. The COVID-19 pandemic had a strong negative impact on MRI multi-organ iron quantification, with a worsening in the management of patients with hemoglobinopathies.

Survival analysis is a statistical approach widely employed to model the time of an event, such as a patient’s death. Classical approaches include the Kaplan–Meier estimator and Cox proportional hazards regression, which assume a linear relationship between the model’s covariates. However, the linearity assumption might pose challenges with high-dimensional data, thus stimulating interest in performing survival analysis using neural network models. In the present work, we implemented a deep Cox neural network (Cox-net) to predict the time of a cardiac event using patient data collected from the Myocardial Iron Overload in Thalassemia (MIOT) project. Cox-net achieved a concordance index (c-index) of 0.812 ± 0.036, outperforming the classical Cox regression (0.790 ± 0.040), and it demonstrated resilience to varying levels of censored patients. A permutation feature importance analysis identified fibrosis and sex as the most significant predictors, aligning with clinical knowledge. Cox-net was able to represent the nonlinear relationships between covariates and maintain reliable survival curve predictions in datasets with a large number of censored patients, making it a promising tool for determining the appropriate clinical pathway for thalassemic patients.