The Contribution of Psychological Distress to Resting Palpitations in Patients Who Recovered from Severe COVID-19.

BACKGROUND: Increasing numbers of patients have recovered from severe coronavirus disease 2019 (COVID-19) in Wuhan, China. This study aimed to evaluate the association of psychological distress with resting palpitations in recovered patients. METHODS: In this prospective cohort study, consecutive patients who recovered from severe COVID-19 and complained of resting palpitations were included. Dynamic electrocardiogram (ECG) was continuously monitored for 2 hours while patients were at rest. A survey using a palpitation frequency scale and the Hospital Anxiety and Depression Scale (HADS) was administered to all participants. RESULTS: Of the 289 consecutive patients who recovered from severe COVID-19, 24 patients (8.3%) suffered resting palpitation symptoms, and 22 patients were finally included. Two-hour Holter monitoring showed that 18 (81.8%) patients had tachyarrhythmias, of which the most common was sinus tachycardia (17/22, 77.3%). However, patients with sinus tachycardia showed a similar frequency of palpitation episodes compared to those without sinus tachycardia. Anxiety (68.2%) and depression (59.1%) were prevalent among these recovered patients. Patients with anxiety or depression symptoms had a higher frequency of palpitation episodes than those without anxiety or depression symptoms. In addition, both the HADS-anxiety score (r =0.609, P<0.01) and HADS-depression score (r =0.516, P=0.01) were positively related to the frequency of palpitation episodes. CONCLUSION: Symptoms of resting palpitations, manifested mainly by sinus tachycardia, are not uncommon in patients who recovered from severe COVID-19. Psychological distress (anxiety and depression) may be responsible, at least in part, for resting palpitation symptoms.

Initial CT features of COVID-19 predicting clinical category.

PURPOSE: To analyze the initial CT features of different clinical categories of COVID-19. MATERIAL AND METHODS: A total of 86 patients with COVID-19 were analyzed, including the clinical, laboratory and imaging features. The following imaging features were analyzed, the lesion amount, location, density, lung nodule, halo sign, reversed-halo sign, distribution pattern, inner structures and changes of adjacent structures. Chi-square test, Fisher's exact test, or Mann-Whitney U test was used for the enumeration data. Binary logistic regression analysis was performed to draw a regression equation to estimate the likelihood of severe and critical category. The forward conditional method was employed for variable selection. RESULTS: Significant statistical differences were found in age (p = 0.001) and sex (p = 0.028) between mild and moderate and severe and critical category. No significant difference was found in clinical symptoms and WBC count between the two groups. The majority of cases (91.8%) showed multifocal lesions. The presence of GGO was higher in severe and critical category than in the mild and moderate category. (57.8% vs.31.7%, p = 0.015). Lymphocyte count was important indicator for the severe and critical category. CONCLUSION: The initial CT features of the different clinical category overlapped. Combining with laboratory test, especially the lymphocyte count, could help to predict the severity of COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42058-021-00056-4.

High-dimensional single-cell analysis reveals the immune characteristics of COVID-19.

Coronavirus disease 2019 (COVID-19), driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a global pandemic in March 2020. Pathogenic T cells and inflammatory monocytes are regarded as the central drivers of the cytokine storm associated with the severity of COVID-19. In this study, we explored the characteristic peripheral cellular profiles of patients with COVID-19 in both acute and convalescent phases by single-cell mass cytometry (CyTOF). Using a combination of algorithm-guided data analyses, we identified peripheral immune cell subsets in COVID-19 and revealed CD4+ T-cell depletion, T-cell differentiation, plasma cell expansion, and the reduced antigen presentation capacity of innate immunity. Notably, COVID-19 induces a dysregulation in the balance of monocyte populations by the expansion of the monocyte subsets. Collectively, our results represent a high-dimensional, single-cell profile of the peripheral immune response to SARS-CoV-2 infection.

A human circulating immune cell landscape in aging and COVID-19.

Age-associated changes in immune cells have been linked to an increased risk for infection. However, a global and detailed characterization of the changes that human circulating immune cells undergo with age is lacking. Here, we combined scRNA-seq, mass cytometry and scATAC-seq to compare immune cell types in peripheral blood collected from young and old subjects and patients with COVID-19. We found that the immune cell landscape was reprogrammed with age and was characterized by T cell polarization from naive and memory cells to effector, cytotoxic, exhausted and regulatory cells, along with increased late natural killer cells, age-associated B cells, inflammatory monocytes and age-associated dendritic cells. In addition, the expression of genes, which were implicated in coronavirus susceptibility, was upregulated in a cell subtype-specific manner with age. Notably, COVID-19 promoted age-induced immune cell polarization and gene expression related to inflammation and cellular senescence. Therefore, these findings suggest that a dysregulated immune system and increased gene expression associated with SARS-CoV-2 susceptibility may at least partially account for COVID-19 vulnerability in the elderly.

Erratum: Author Correction: Immune cell profiling of COVID-19 patients in the recovery stage by single-cell sequencing.

[This corrects the article DOI: 10.1038/s41421-020-0168-9.].

Immune cell profiling of COVID-19 patients in the recovery stage by single-cell sequencing.

COVID-19, caused by SARS-CoV-2, has recently affected over 1,200,000 people and killed more than 60,000. The key immune cell subsets change and their states during the course of COVID-19 remain unclear. We sought to comprehensively characterize the transcriptional changes in peripheral blood mononuclear cells during the recovery stage of COVID-19 by single-cell RNA sequencing technique. It was found that T cells decreased remarkably, whereas monocytes increased in patients in the early recovery stage (ERS) of COVID-19. There was an increased ratio of classical CD14++ monocytes with high inflammatory gene expression as well as a greater abundance of CD14++IL1ß+ monocytes in the ERS. CD4+ T cells and CD8+ T cells decreased significantly and expressed high levels of inflammatory genes in the ERS. Among the B cells, the plasma cells increased remarkably, whereas the naïve B cells decreased. Several novel B cell-receptor (BCR) changes were identified, such as IGHV3-23 and IGHV3-7, and isotypes (IGHV3-15, IGHV3-30, and IGKV3-11) previously used for virus vaccine development were confirmed. The strongest pairing frequencies, IGHV3-23-IGHJ4, indicated a monoclonal state associated with SARS-CoV-2 specificity, which had not been reported yet. Furthermore, integrated analysis predicted that IL-1ß and M-CSF may be novel candidate target genes for inflammatory storm and that TNFSF13, IL-18, IL-2, and IL-4 may be beneficial for the recovery of COVID-19 patients. Our study provides the first evidence of an inflammatory immune signature in the ERS, suggesting COVID-19 patients are still vulnerable after hospital discharge. Identification of novel BCR signaling may lead to the development of vaccines and antibodies for the treatment of COVID-19.