The Impact of the COVID-19 Pandemic on the Organization of Cardio-Hematology Care-A Polish Single Center Experience

Diagnostic landscape of first-time cytometric screening for paroxysmal nocturnal hemoglobinuria in Poland in 2013-2022

BACKGROUND

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired hematopoietic stem cell disorder characterized by PIG-A mutations, leading to glycophosphatidylinositol (GPI)-anchored proteins deficiency that triggers hemolysis - a hallmark of the disease. PNH diagnostics is based on high-sensitivity multicolor flow cytometry (MFC), enabling to detect even small populations of PNH cells. In this single-center, retrospective study, we aimed to characterize a cohort of PNH clone-positive patients first time screened from January 1st, 2013 until December 31st, 2022 with MFC according to International Clinical Cytometry Society PNH Consensus Guidelines.

RESULTS

Out of 2790 first-time screened individuals, the presence of PNH clone in neutrophils was detected in 322 patients, including 49 children and 273 adults. Annual incidence was stable at a median of 31 patients (14 and 19 with clone sizes ≤ 1% and > 1%, respectively), with a decline in number of patients with clone sizes > 1% observed in 2020, potentially influenced by the COVID-19 pandemic. The most common screening indications were aplastic anemia and other cytopenias.

CONCLUSIONS

A significant underrepresentation of hemolytic patients was observed as compared to the published cohorts suggesting that these patients are missed in diagnostic process and classic PNH remains underdiagnosed in Poland.

How COVID-19 has changed the utilization of different health care services in Poland

BACKGROUND

The COVID-19 pandemic has affected health care systems in many ways, including access to and the use of non-COVID services. The aim of the study was to assess the impact of the pandemic on the utilization of different public health care services in Poland.

METHODS

The aggregated data on health care users and provided services for the years 2015/2016-2021 were used to analyse the changes in health care utilization during the pandemic and deviations from pre-pandemic utilization trends. Quantitative analysis was complemented with qualitative descriptions of the changes in principles of health care provision during the pandemic.

RESULTS

The results show a considerable drop in the provision of most health care services in 2020 that in some cases disturbed pre-pandemic utilization trends and was not made up for in 2021. The most significant decrease has been observed in the field of preventive and public health services, as well as rehabilitation. The provision of these services was put on hold during the pandemic.

CONCLUSIONS

The accumulated COVID-19-related "health debt" urgently calls for government actions to strengthen disease prevention and health promotion in Poland.

Application of Heuristic Algorithms in the Tomography Problem for Pre-Mining Anomaly Detection in Coal Seams

The paper presents research on a specific approach to the issue of computed tomography with an incomplete data set. The case of incomplete information is quite common, for example when examining objects of large size or difficult to access. Algorithms devoted to this type of problems can be used to detect anomalies in coal seams that pose a threat to the life of miners. The most dangerous example of such an anomaly may be a compressed gas tank, which expands rapidly during exploitation, at the same time ejecting rock fragments, which are a real threat to the working crew. The approach presented in the paper is an improvement of the previous idea, in which the detected objects were represented by sequences of points. These points represent rectangles, which were characterized by sequences of their parameters. This time, instead of sequences in the representation, there are sets of objects, which allow for the elimination of duplicates. As a result, the reconstruction is faster. The algorithm presented in the paper solves the inverse problem of finding the minimum of the objective function. Heuristic algorithms are suitable for solving this type of tasks. The following heuristic algorithms are described, tested and compared: Aquila Optimizer (AQ), Firefly Algorithm (FA), Whale Optimization Algorithm (WOA), Butterfly Optimization Algorithm (BOA) and Dynamic Butterfly Optimization Algorithm (DBOA). The research showed that the best algorithm for this type of problem turned out to be DBOA.