Background The outbreak and the rampant spread of SARS-CoV-2-infected pneumonia (COVID-19) first identified in Wuhan, China, has infected thousands of patients and killed more than two thousand. We aimed to find indicators that could predict the progression of SARS-CoV-2 pneumonia. Methods Medical history, clinical features, laboratory and radiological results were retrospectively reviewed from 112 patients with clinically diagnosed SARS-CoV-2 pneumonia in Renmin Hospital of Wuhan University from Jan 1 to Jan 31, 2020. Clinical outcomes were followed up to Feb 9, 2020. Results Based on their outcomes, we divided these patients into groups of remission, deterioration and death respectively, and analyzed the counts of lymphocyte and its subsets. A decreased combination of CD3+, CD4+ and CD8+ T lymphocyte counts was observed as the SARS-CoV-2 pneumonia progressed. Among them, the CD4+ T lymphocyte counts were reduced at the early stage, while CD8+ counts were decreased at advanced stage or end stage. Conclusions We identified in our study of 112 hospitalized patients that CD3+, CD4+ and CD8+ T lymphocyte counts were useful markers to predict the clinical progression of SARS-CoV-2 pneumonia at different stages. Considering the large number of patients with severe pneumonia, and the urgency of this ongoing global public health emergency, the counts of lymphocyte and its subsets from laboratory examinations could be easy and useful indicators for physicians to determine a timely and proper therapeutic strategy for patients and an early warning sign for predicting or reducing mortality in SARS-CoV-2-infected pneumonia.
In order to improve the accuracy of the image segmentation in video surveillance sequences and to overcome the limits of the traditional clustering algorithms that can not accurately model the image data sets which Contains noise data, the paper presents an automatic and accurate video image segmentation algorithm, according to the spatial properties, which uses the Gaussian mixture models to segment the image. But the expectation-maximization algorithm is very sensitive to initial values, and easy to fall into local optimums, so the paper presents a differential evolution-based parameters estimation for Gaussian mixture models. The experiment result shows that the segmentation accuracy has been improved greatly than by the traditional segmentation algorithms.
Background The outbreak and the rampant spread of SARS-CoV-2-infected pneumonia (COVID-19) rst identi ed in Wuhan, China, has infected thousands of patients and killed more than two thousand. We aimed to nd indicators that could predict the progression of SARS-CoV-2 pneumonia. Methods Medical history, clinical features, laboratory and radiological results were retrospectively reviewed from 112 patients with clinically diagnosed SARS-CoV-2 pneumonia in Renmin Hospital of Wuhan University from Jan 1 to Jan 31, 2020. Clinical outcomes were followed up to Feb 9, 2020.Results Based on their outcomes, we divided these patients into groups of remission, deterioration and death respectively, and analyzed the counts of lymphocyte and its subsets. A decreased combination of CD3+, CD4+ and CD8+ T lymphocyte counts was observed as the SARS-CoV-2 pneumonia progressed.Among them, the CD4+ T lymphocyte counts were reduced at the early stage, while CD8+ counts were decreased at advanced stage or end stage.
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