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- An interactive dashboard for statistical analysis of intensive care unit COVID-19 dataPublication . Dias, Rúben; Ferreira, Artur; Pinto, Iola; Brás-Geraldes, Carlos; Von Rekowski, Cristiana; Bento, LuísCOVID-19 caused a pandemic, due to its ease of transmission and high number of infections. The evolution of the pandemic and its consequences for the mortality and morbidity of populations, especially the elderly, generated several scientific studies and many research projects. Among them, we have the Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine (PREMO) research project. For such a project with many data records, it is necessary to provide a smooth graphical analysis to extract value from it. Methods: In this paper, we present the development of a full-stack Web application for the PREMO project, consisting of a dashboard providing statistical analysis, data visualization, data import, and data export. The main aspects of the application are described, as well as the diverse types of graphical representations and the possibility to use filters to extract relevant information for clinical practice. Results: The application, accessible through a browser, provides an interactive visualization of data from patients admitted to the intensive care unit (ICU), throughout the six waves of COVID-19 in two hospitals in Lisbon, Portugal. The analysis can be isolated per wave or can be seen in an aggregated view, allowing clinicians to create many views of the data and to study the behavior and consequences of different waves. For instance, the experimental results show clearly the effect of vaccination as well as the changes on the most relevant clinical parameters on each wave. Conclusions: The dashboard allows clinicians to analyze many variables of each of the six waves as well as aggregated data for all the waves. The application allows the user to extract information and scientific knowledge about COVID-19’s evolution, yielding insights for this pandemic and for future pandemics.
- The characteristics and laboratory findings of SARS-CoV-2 infected patients during the first three COVID-19 waves in Portugal – a retrospective single-center studyPublication . Von Rekowski, Cristiana; Fonseca, Tiago AH; Araújo, Rúben; Brás-Geraldes, Carlos; Calado, Cecília; Bento, Luís; Pinto, IolaBackground and Objectives: Given the wide spectrum of clinical and laboratory manifestations of the coronavirus disease 2019 (COVID-19), it is imperative to identify potential contributing factors to patients’ outcomes. However, a limited number of studies have assessed how the different waves affected the progression of the disease, more so in Portugal. Therefore, our main purpose was to study the clinical and laboratory patterns of COVID-19 in an unvaccinated population admitted to the intensive care unit, identifying characteristics associated with death, in each of the first three waves of the pandemic. Materials and Methods: This study included 337 COVID-19 patients admitted to the intensive care unit of a single-center hospital in Lisbon, Portugal, between March 2020 and March 2021. Comparisons were made between three COVID-19 waves, in the second (n = 325) and seventh (n = 216) days after admission, and between discharged and deceased patients. Results: Deceased patients were considerably older (p = 0.021) and needed greater ventilatory assistance (p = 0.023), especially in the first wave. Differences between discharged and deceased patients’ biomarkers were minimal in the first wave, on both analyzed days. In the second wave significant differences emerged in troponins, lactate dehydrogenase, procalcitonin, C-reactive protein, and white blood cell subpopulations, as well as platelet-to-lymphocyte and neutrophil-to-lymphocyte ratios (all p < 0.05). Furthermore, in the third wave, platelets and D-dimers were also significantly different between patients’ groups (all p < 0.05). From the second to the seventh days, troponins and lactate dehydrogenase showed significant decreases, mainly for discharged patients, while platelet counts increased (all p < 0.01). Lymphocytes significantly increased in discharged patients (all p < 0.05), while white blood cells rose in the second (all p < 0.001) and third (all p < 0.05) waves among deceased patients. Conclusions: This study yields insights into COVID-19 patients’ characteristics and mortality-associated biomarkers during Portugal’s first three COVID-19 waves, highlighting the importance of considering wave variations in future research due to potential significant outcome differences.