One year after ICU admission for severe community-acquired pneumonia of bacterial, viral or unidentified etiology. What are the outcomes?

INTRODUCTION: Multiplex polymerase chain reaction (mPCR) for respiratory virus testing is increasingly used in community-acquired pneumonia (CAP), however data on one-year outcome in intensive care unit (ICU) patients with reference to the causative pathogen are scarce. MATERIALS AND METHODS: We performed a single-center retrospective study in 123 ICU patients who had undergone respiratory virus testing for CAP by mPCR and with known one-year survival status. Functional status including dyspnea (mMRC score), autonomy (ADL Katz score) and need for new home-care ventilatory support was assessed at a one-year post-ICU follow-up. Mortality rates and functional status were compared in patients with CAP of a bacterial, viral or unidentified etiology one year after ICU admission. RESULTS: The bacterial, viral and unidentified groups included 19 (15.4%), 37 (30.1%), and 67 (54.5%) patients, respectively. In multivariate analysis, one-year mortality in the bacterial group was higher compared to the viral group (HR 2.92, 95% CI 1.71-7.28, p = 0.02) and tended to be higher compared to the unidentified etiology group (p = 0.06); but no difference was found between the viral and the unidentified etiology group (p = 0.43). In 64/83 one-year survivors with a post-ICU follow-up consultation, there were no differences in mMRC score, ADL Katz score and new home-care ventilatory support between the groups (p = 0.52, p = 0.37, p = 0.24, respectively). Severe dyspnea (mMRC score = 4 or death), severe autonomy deficiencies (ADL Katz score ≤ 2 or death), and major adverse respiratory events (new home-care ventilatory support or death) were observed in 52/104 (50.0%), 47/104 (45.2%), and 65/104 (62.5%) patients, respectively; with no difference between the bacterial, viral and unidentified group: p = 0.58, p = 0.06, p = 0.61, respectively. CONCLUSIONS: CAP of bacterial origin had a poorer outcome than CAP of viral or unidentified origin. At one-year, impairment of functional status was frequently observed, with no difference according to the etiology.

Automated detection of COVID-19 through convolutional neural network using chest x-ray images.

The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the COVID-19, timely and accurate classification of healthy and infected patients is essential to control and treat COVID-19. We aim to develop a deep learning-based system for the persuasive classification and reliable detection of COVID-19 using chest radiography. Firstly, we evaluate the performance of various state-of-the-art convolutional neural networks (CNNs) proposed over recent years for medical image classification. Secondly, we develop and train CNN from scratch. In both cases, we use a public X-Ray dataset for training and validation purposes. For transfer learning, we obtain 100% accuracy for binary classification (i.e., Normal/COVID-19) and 87.50% accuracy for tertiary classification (Normal/COVID-19/Pneumonia). With the CNN trained from scratch, we achieve 93.75% accuracy for tertiary classification. In the case of transfer learning, the classification accuracy drops with the increased number of classes. The results are demonstrated by comprehensive receiver operating characteristics (ROC) and confusion metric analysis with 10-fold cross-validation.

A functionally distinct neutrophil landscape in severe COVID-19 reveals opportunities for adjunctive therapies.

Acute respiratory distress syndrome (ARDS) is a life-threatening syndrome, constituted by respiratory failure and diffuse alveolar damage that results from dysregulated local and systemic immune activation, causing pulmonary vascular, parenchymal, and alveolar damage. SARS-CoV-2 infection has become the dominant cause of ARDS worldwide, and emerging evidence implicates neutrophils and their cytotoxic arsenal of effector functions as central drivers of immune-mediated lung injury in COVID-19 ARDS. However, key outstanding questions are whether COVID-19 drives a unique program of neutrophil activation or effector functions that contribute to the severe pathogenesis of this pandemic illness and whether this unique neutrophil response can be targeted to attenuate disease. Using a combination of high-dimensional single-cell analysis and ex vivo functional assays of neutrophils from patients with COVID-19 ARDS, compared with those with non-COVID ARDS (caused by bacterial pneumonia), we identified a functionally distinct landscape of neutrophil activation in COVID-19 ARDS that was intrinsically programmed during SARS-CoV-2 infection. Furthermore, neutrophils in COVID-19 ARDS were functionally primed to produce high amounts of neutrophil extracellular traps. Surprisingly, this unique pathological program of neutrophil priming escaped conventional therapy with dexamethasone, thereby revealing a promising target for adjunctive immunotherapy in severe COVID-19.

Diagnostic value of using a combination of nucleic acid and specific antibody tests for SARS-CoV-2 in coronavirus disease 2019.

Coronavirus disease 2019 (COVID-19) is a newly emerged disease with various clinical manifestations and imaging features. The diagnosis of COVID-19 depends on a positive nucleic acid amplification test by real-time reverse transcription-polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the clinical manifestations and imaging features of COVID-19 are non-specific, and nucleic acid test for SARS-CoV-2 can have false-negative results. It is presently believed that detection of specific antibodies to SARS-CoV-2 is an effective screening and diagnostic indicator for SARS-CoV-2 infection. Thus, a combination of nucleic acid and specific antibody tests for SARS-CoV-2 will be more effective to diagnose COVID-19, especially to exclude suspected cases.

COVID-19 Is Distinct From SARS-CoV-2-Negative Community-Acquired Pneumonia.

Background: Corona virus disease (COVID-19) is an infectious respiratory disease that has spread rapidly across the world. Many studies have already evaluated the clinical features of COVID-19, but how it compares with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-negative community-acquired pneumonia (SN-CAP) is still unclear. Moreover, COVID-19 mortality is correlated with disease severity, but indicators for severity grading have not been specified. We aimed to analyze the clinical characteristics of COVID-19 in comparison with SN-CAP and find indicators for disease severity in COVID-19. Methods: Patients diagnosed with COVID-19 and SN-CAP were enrolled. Clinical, radiological, and laboratory data were analyzed. Results: The numbers of COVID-19 and SN-CAP patients enrolled were 304 and 138, respectively. The age of the patients was not significantly different between the groups. Compared with SN-CAP, COVID-19 patients had more symptoms of fever and dyspnea; and showed significant difference in blood count results. Computed tomography (CT) imaging of COVID-19 patients showed patchy ground-glass opacities that correlated with disease severity, whereas the CT imaging of SN-CAP patients showed patchy high-density shadows. COVID-19 patients were classified into moderate, severe, and critically severe groups. The severe and critically severe groups had elevated levels of white blood cells (WBC), neutrophils, platelets, C-reaction protein (CRP), lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), troponin-I, creatinine, and blood urea nitrogen (BUN). However, they had decreased levels of lymphocytes, lymphocyte ratio, and albumin. Compared with the younger patients, the older COVID-19 individuals had more chronic diseases and significantly elevated levels of WBC, neutrophil, and CRP levels. Conclusion: SN-CAP showed more inflammatory reaction than COVID-19. Old people with chronic diseases are more susceptible to COVID-19 and have a high likelihood of developing severe and critically severe infection. Levels of WBC, lymphocytes, neutrophils, CRP, NLR, PLR, troponin-I, creatinine, and BUN are important indicators for severity grading in COVID-19.