Respiratory mucosal vaccination of peptide-poloxamine-DNA nanoparticles provides complete protection against lethal SARS-CoV-2 challenge.

The ongoing SARS-CoV-2 pandemic represents a brutal reminder of the continual threat of mucosal infectious diseases. Mucosal immunity may provide robust protection at the predominant sites of SARS-CoV-2 infection. However, it remains unclear whether respiratory mucosal administration of DNA vaccines could confer protective immune responses against SARS-CoV-2 challenge due to insurmountable barriers posed by the airway. Here, we applied self-assembled peptide-poloxamine nanoparticles with mucus-penetrating properties for pulmonary inoculation of a COVID-19 DNA vaccine (pSpike/PP-sNp). The pSpike/PP-sNp not only displays superior gene transfection and favorable biocompatibility in the mouse airway, but also promotes a tripartite immunity consisting of systemic, cellular, and mucosal immune responses that are characterized by mucosal IgA secretion, high levels of neutralizing antibodies, and resident memory phenotype T-cell responses in the lungs of mice. Most importantly, immunization with pSpike/PP-sNp completely eliminates SARS-CoV-2 infection in both upper and lower respiratory tracts and enables 100% survival rate of mice following lethal SARS-CoV-2 challenge. Our findings indicate PP-sNp is a promising platform in mediating DNA vaccines to elicit all-around mucosal immunity against SARS-CoV-2.

The impact of traffic control measures on the spread of COVID-19 within urban agglomerations based on a modified epidemic model.

With the spatial structure of urban agglomerations, well-developed transportation networks and close economic ties can increase the risk of intercity transmission of infectious diseases. To reveal the epidemic transmission mechanism in urban agglomerations and to explore the effectiveness of traffic control measures, this study proposes an Urban-Agglomeration-based Epidemic and Mobility Model (UAEMM) based on the reality of urban transportation networks and population mobility factors. Since the model considers the urban population inflow, along with the active intracity population, it can be used to estimate the composition of urban cases. The model was applied to the Chang-Zhu-Tan urban agglomeration, and the results show that the model can better simulate the transmission process of the urban agglomeration for a certain scale of epidemic. The number of cases within the urban agglomeration is higher than the number of cases imported into the urban agglomeration from external cities. The composition of cases in the core cities of the urban agglomeration changes with the adjustment of prevention and control measures. In contrast, the number of cases imported into the secondary cities is consistently greater than the number of cases transmitted within the cities. A traffic control measures discount factor is introduced to simulate the development of the epidemic in the urban agglomeration under the traffic control measures of the first-level response to major public health emergency, traffic blockades in infected areas, and public transportation shutdowns. If none of those traffic control measures had been taken after the outbreak of COVID-19, the number of cases in the urban agglomeration would theoretically have increased to 3879, which is 11.61 times the actual number of cases that occurred. If only one traffic control measure had been used alone, each of the three measures would have reduced the number of cases in the urban agglomeration to 30.19 %-57.44 % of the theoretical values of infection cases, with the best blocking effect coming from the first-level response to major public health emergency. Traffic control measures have a significant effect in interrupting the spread of COVID-19 in urban agglomerations. The methodology and main findings presented in this paper are of general interest and can also be used in studies in other countries for similar purposes to help understand the spread of COVID-19 in urban agglomerations.

Rationale and design of the Effects of intensive Systolic blood Pressure lowering treatment in reducing RIsk of vascular evenTs (ESPRIT): A multicenter open-label randomized controlled trial.

BACKGROUND: Lowering blood pressure (BP) effectively reduces the risk of cardiovascular (CV) events in high CV risk individuals. The optimal target of BP lowering among high CV risk individuals remains unclear. METHODS: The Effects of intensive Systolic blood Pressure lowering treatment in reducing RIsk of vascular evenTs (ESPRIT) trial is a multi-center, open-label, randomized controlled trial to compare the efficacy and safety of intensive BP lowering strategy (Systolic BP target <120 mm Hg) and standard BP lowering strategy (Systolic BP target <140 mm Hg). Participants aged at least 50 years old with baseline systolic BP within 130 to 180 mm Hg at high CV risk, defined by established CV diseases or 2 major CV risk factors, were enrolled. The primary outcome is a composite CV outcome of myocardial infarction, coronary or non-coronary revascularization, hospitalization or emergency department visit from new-onset heart failure or acute decompensated heart failure, stroke, or death from CV diseases. Secondary outcomes include components of the primary composite outcome, all-cause death, a composite of the primary outcome or all-cause death, kidney outcomes, as well as cognitive outcomes. RESULTS: Despite of the interruption of COVID-19 outbreak, the ESPRIT trial successfully enrolled and randomized 11,255 participants from 116 hospitals or primary health care institutions. The mean age of the participants was 64.6 (standard deviation [SD], 7.1) years, 4,650 (41.3%) were women. Among them 28.9%, 26.9% and 38.7% had coronary heart disease, prior stroke and diabetes mellitus, respectively. COVID-19 outbreak affected the BP lowering titration process of the trial, and delayed the reach of BP target. CONCLUSIONS: The ESPRIT trial will address the important question on the optimal BP lowering target for individuals with high CV risk, and generate high quality evidence for treating millions of patients from East Asian countries.

Temporal dynamic characteristics of human monkeypox epidemic in 2022 around the world under the COVID-19 pandemic background.

Background: The reemergence of the monkeypox epidemic has aroused great concern internationally. Concurrently, the COVID-19 epidemic is still ongoing. It is essential to understand the temporal dynamics of the monkeypox epidemic in 2022 and its relationship with the dynamics of the COVID-19 epidemic. In this study, we aimed to explore the temporal dynamic characteristics of the human monkeypox epidemic in 2022 and its relationship with those of the COVID-19 epidemic. Methods: We used publicly available data of cumulative monkeypox cases and COVID-19 in 2022 and COVID-19 at the beginning of 2020 for model validation and further analyses. The time series data were fitted with a descriptive model using the sigmoid function. Two important indices (logistic growth rate and semi-saturation period) could be obtained from the model to evaluate the temporal characteristics of the epidemic. Results: As for the monkeypox epidemic, the growth rate of infection and semi-saturation period showed a negative correlation (r = 0.47, p = 0.034). The growth rate also showed a significant relationship with the locations of the country in which it occurs [latitude (r = -0.45, p = 0.038)]. The development of the monkeypox epidemic did not show significant correlation compared with the that of COVID-19 in 2020 and 2022. When comparing the COVID-19 epidemic with that of monkeypox, a significantly longer semi-saturation period was observed for monkeypox, while a significant larger growth rate was found in COVID-19 in 2020. Conclusions: This novel study investigates the temporal dynamics of the human monkeypox epidemic and its relationship with the ongoing COVID-19 epidemic, which could provide more appropriate guidance for local governments to plan and implement further fit-for-purpose epidemic prevention policies.

A mathematical model reveals the influence of NPIs and vaccination on SARS-CoV-2 Omicron Variant.

An SVEIR SARS-CoV-2 Omicron variant model is proposed to provide some insights to coordinate non-pharmaceutical interventions (NPIs) and vaccination. Mathematically, we define the basic reproduction number R 0 and the effective reproduction number R e to measure the infection potential of Omicron variant and formulate an optimal disease control strategy. Our inversion results imply that the sick period of Omicron variant in the United States is longer than that of Delta variant in India. The decrease in the infectious period of the infection with infectiousness implies that the risk of hospitalization is reduced; but the increasing period of the infection with non-infectiousness signifies that Omicron variant lengthens the period of nucleic acid test being negative. Optimistically, Omicron's death rate is only a quarter of Delta's. Moreover, we forecast that the cumulative cases will exceed 100 million in the United States on February 28, 2022, and the daily confirmed cases will reach a peak on February 2, 2022. The results of parameters sensitivity analysis imply that NPIs are helpful to reduce the number of confirmed cases. In particular, NPIs are indispensable even if all the people were vaccinated when the efficiency of vaccine is relatively low. By simulating the relationships of the effective reproduction number R e , the vaccination rate and the efficacy of vaccine, we find that it is impossible to achieve the herd immunity without NPIs while the efficiency of vaccine is lower than 88.7 % . Therefore, the herd immunity area is defined by the evolution of relationships between the vaccination rate and the efficacy of vaccine. Finally, we present that the disease-induced mortality rate demonstrates the periodic oscillation and an almost periodic function is deduced to match the curve. A discussion completes the paper.

Chicken or Porcine Aminopeptidase N Mediates Cellular Entry of Pseudoviruses Carrying Spike Glycoprotein from the Avian Deltacoronaviruses HKU11, HKU13, and HKU17.

Members of deltacoronavirus (DCoV) have mostly been identified in diverse avian species as natural reservoirs, though the porcine DCoV (PDCoV) is a major swine enteropathogenic virus with global spread. The important role of aminopeptidase N (APN) orthologues from various mammalian and avian species in PDCoV cellular entry and interspecies transmission has been revealed recently. In this study, comparative analysis indicated that three avian DCoVs, bulbul DCoV HKU11, munia DCoV HKU13, and sparrow DCoV HKU17 (Chinese strain), and PDCoV in the subgenera Buldecovirus are grouped together at whole-genome levels; however, the spike (S) glycoprotein and its S1 subunit of HKU17 are more closely related to night heron DCoV HKU19 in Herdecovirus. Nevertheless, the S1 protein of HKU11, HKU13, or HKU17 bound to or interacted with chicken APN (chAPN) or porcine APN (pAPN) by flow cytometry analysis of cell surface expression of APN and by coimmunoprecipitation in APN-overexpressing cells. Expression of chAPN or pAPN allowed entry of pseudotyped lentiviruses with the S proteins from HKU11, HKU13 and HKU17 into nonsusceptible cells and natural avian and porcine cells, which could be inhibited by the antibody against APN or anti-PDCoV-S1. APN knockdown by siRNA or knockout by CRISPR/Cas9 in chicken or swine cell lines significantly or almost completely blocked infection of these pseudoviruses. Hence, we demonstrate that HKU11, HKU13, and HKU17 with divergent S genes likely engage chAPN or pAPN to enter the cells, suggesting a potential interspecies transmission from wild birds to poultry and from birds to mammals by certain avian DCoVs. IMPORTANCE The receptor usage of avian deltacoronaviruses (DCoVs) has not been investigated thus far, though porcine deltacoronavirus (PDCoV) has been shown to utilize aminopeptidase N (APN) as a cell receptor. We report here that chicken or porcine APN also mediates cellular entry by three avian DCoV (HKU11, HKU13, and HKU17) spike pseudoviruses, and the S1 subunit of three avian DCoVs binds to APN in vitro and in the surface of avian and porcine cells. The results fill the gaps in knowledge about the avian DCoV receptor and elucidate important insights for the monitoring and prevention of potential interspecies transmission of certain avian DCoVs. In view of the diversity of DCoVs, whether this coronavirus genus will cause novel virus to emerge in other mammals from birds, are worthy of further surveillance and investigation.

Mechanistic studies of MALAT1 in respiratory diseases.

Background: The incidence of respiratory diseases and the respiratory disease mortality rate have increased in recent years. Recent studies have shown that long non-coding RNA (lncRNA) MALAT1 is involved in various respiratory diseases. In vascular endothelial and cancer cells, MALAT1 expression triggers various changes such as proinflammatory cytokine expression, cancer cell proliferation and metastasis, and increased endothelial cell permeability. Methods: In this review, we performed a relative concentration index (RCI) analysis of the lncRNA database to assess differences in MALAT1 expression in different cell lines and at different locations in the same cell, and summarize the molecular mechanisms of MALAT1 in the pathophysiology of respiratory diseases and its potential therapeutic application in these conditions. Results: MALAT1 plays an important regulatory role in lncRNA with a wide range of effects in respiratory diseases. The available evidence shows that MALAT1 plays an important role in the regulation of multiple respiratory diseases. Conclusion: MALAT1 is an important regulatory biomarker for respiratory disease. Targeting the regulation MALAT1 could have important applications for the future treatment of respiratory diseases.

Physical Activity and Interpersonal Adaptation in Chinese Adolescents After COVID-19: The Mediating Roles of Self-Esteem and Psychological Resilience.

Previous studies have implied that physical activity profoundly influences interpersonal adaptation. However, this effect and its mechanisms have not been directly verified, especially for adolescents. This study examines the association between physical activity and interpersonal adaptation in adolescents through self-esteem and psychological resilience after the coronavirus disease 2019 (COVID-19) pandemic. Participants included 542 Chinese adolescents (aged 13-18 years; 242 boys and 300 girls). Adolescents in China anonymously completed a series of questionnaires, including the PARS-3 Scale of PE Activity Grade (PARS-3), the Self-esteem Scale (SES), the Resilience Scale for Adolescents (RSCA), and the Interpersonal Adaptation Scale. The results showed that physical activity positively correlated with self-esteem, psychological resilience, and interpersonal adaptation. Additionally, self-esteem and psychological resilience serially mediated the impact of physical activity on interpersonal adaptation. The findings highlight the positive impact of physical activity on adolescent interpersonal adaptation by strengthening positive psychological resources in the post-pandemic era.

Small GTPase-A Key Role in Host Cell for Coronavirus Infection and a Potential Target for Coronavirus Vaccine Adjuvant Discovery.

Small GTPases are signaling molecules in regulating key cellular processes (e.g., cell differentiation, proliferation, and motility) as well as subcellular events (e.g., vesicle trafficking), making them key participants, especially in a great array of coronavirus infection processes. In this review, we discuss the role of small GTPases in the coronavirus life cycle, especially pre-entry, endocytosis, intracellular traffic, replication, and egress from the host cell. Furthermore, we also suggest the molecules that have potent adjuvant activity by targeting small GTPases. These studies provide deep insights and references to understand the pathogenesis of coronavirus as well as to propose the potential of small GTPases as targets for adjuvant development.

Expression Profile and Localization of SARS-CoV-2 Nonstructural Replicase Proteins in Infected Cells.

Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 is responsible for the COVID-19 pandemic that has caused unprecedented loss of life and economic trouble all over the world, though the mechanism of its replication remains poorly understood. In this study, antibodies were generated and used to systematically determine the expression profile and subcellular distribution of 11 SARS-CoV-2 nonstructural replicase proteins (nsp1, nsp2, nsp3, nsp5, nsp7, nsp8, nsp9, nsp10, nsp13, nsp14, and nsp15) by Western blot and immunofluorescence assay. Nsp3, nsp5, and nsp8 were detected in perinuclear foci at different time points, with diffusion and stronger fluorescence observed over time. In particular, colocalization of nsp8 and nsp13 with different replicase proteins suggested viral protein-protein interaction, which may be key to understanding their functions and potential molecular mechanisms. Viral intermediate dsRNA was detected in perinuclear foci as early as 2-h postinfection, indicating the initiation of virus replication. With the passage of time, these perinuclear dsRNA foci became larger and brighter, and nearly all colocalized with N protein, consistent with viral growth over time. Thus, the development of these anti-nsp antibodies provides basic tools for the further study of replication and diagnosis of SARS-CoV-2. IMPORTANCE The intracellular localization of SARS-CoV-2 replicase nonstructural proteins (nsp) during infection has not been fully elucidated. In this study, we systematically analyzed the expression and subcellular localization of 11 distinct viral nsp and dsRNA over time in SARS-CoV-2-infected cells by using individual antibody against these replicase proteins. The data indicated that nsp gene expression is highly regulated in space and time, which could be useful to understand the function of viral replicases and future development of diagnostics and potential antiviral strategies against SARS-CoV-2.

Alterations in microbiota of patients with COVID-19: potential mechanisms and therapeutic interventions.

The global coronavirus disease 2019 (COVID-19) pandemic is currently ongoing. It is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A high proportion of COVID-19 patients exhibit gastrointestinal manifestations such as diarrhea, nausea, or vomiting. Moreover, the respiratory and gastrointestinal tracts are the primary habitats of human microbiota and targets for SARS-CoV-2 infection as they express angiotensin-converting enzyme-2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) at high levels. There is accumulating evidence that the microbiota are significantly altered in patients with COVID-19 and post-acute COVID-19 syndrome (PACS). Microbiota are powerful immunomodulatory factors in various human diseases, such as diabetes, obesity, cancers, ulcerative colitis, Crohn's disease, and certain viral infections. In the present review, we explore the associations between host microbiota and COVID-19 in terms of their clinical relevance. Microbiota-derived metabolites or components are the main mediators of microbiota-host interactions that influence host immunity. Hence, we discuss the potential mechanisms by which microbiota-derived metabolites or components modulate the host immune responses to SARS-CoV-2 infection. Finally, we review and discuss a variety of possible microbiota-based prophylaxes and therapies for COVID-19 and PACS, including fecal microbiota transplantation (FMT), probiotics, prebiotics, microbiota-derived metabolites, and engineered symbiotic bacteria. This treatment strategy could modulate host microbiota and mitigate virus-induced inflammation.

Evaluation of NOx emissions before, during, and after the COVID-19 lockdowns in China: A comparison of meteorological normalization methods.

Meteorological normalization refers to the removal of meteorological effects on air pollutant concentrations for evaluating emission changes. There currently exist various meteorological normalization methods, yielding inconsistent results. This study aims to identify the state-of-the-art method of meteorological normalization for characterizing the spatiotemporal variation of NOx emissions caused by the COVID-19 pandemic in China. We obtained the hourly data of NO2 concentrations and meteorological conditions for 337 cities in China from January 1, 2019, to December 31, 2020. Three random-forest based meteorological normalization methods were compared, including (1) the method that only resamples meteorological variables, (2) the method that resamples meteorological and temporal variables, and (3) the method that does not need resampling, denoted as Resample-M, Resample-M&T, and Resample-None, respectively. The comparison results show that Resample-M&T considerably underestimated the emission reduction of NOx during the lockdowns, Resample-None generates widely fluctuating estimates that blur the emission recovery trend during work resumption, and Resample-M clearly delineates the emission changes over the entire period. Based on the Resample-M results, the maximum emission reduction occurred during January to February 2020, for most cities, with an average decrease of 19.1 ± 9.4% compared to 2019. During April of 2020 when work resumption initiated to the end of 2020, the emissions rapidly bounced back for most cities, with an average increase of 12.6 ± 15.8% relative to those during the strict lockdowns. Consequently, we recommend using Resample-M for meteorological normalization, and the normalized NO2 concentration dynamics for each city provide important implications for future emission reduction.

Identification of a promiscuous conserved CTL epitope within the SARS-CoV-2 spike protein.

ABSTRACTThe COVID-19 disease caused by infection with SARS-CoV-2 and its variants is devastating to the global public health and economy. To date, over a hundred COVID-19 vaccines are known to be under development, and the few that have been approved to fight the disease are using the spike protein as the primary target antigen. Although virus-neutralizing epitopes are mainly located within the RBD of the spike protein, the presence of T cell epitopes, particularly the CTL epitopes that are likely to be needed for killing infected cells, has received comparatively little attention. This study predicted several potential T cell epitopes with web-based analytic tools and narrowed them down from several potential MHC-I and MHC-II epitopes by ELIspot and cytolytic assays to a conserved MHC-I epitope. The epitope is highly conserved in current viral variants and compatible with a presentation by most HLA alleles worldwide. In conclusion, we identified a CTL epitope suitable for evaluating the CD8+ T cell-mediated cellular response and potentially for addition into future COVID-19 vaccine candidates to maximize CTL responses against SARS-CoV-2.

Ruxolitinib attenuates secondary injury after traumatic spinal cord injury.

Excessive inflammation post-traumatic spinal cord injury (SCI) induces microglial activation, which leads to prolonged neurological dysfunction. However, the mechanism underlying microglial activation-induced neuroinflammation remains poorly understood. Ruxolitinib (RUX), a selective inhibitor of JAK1/2, was recently reported to inhibit inflammatory storms caused by SARS-CoV-2 in the lung. However, its role in disrupting inflammation post-SCI has not been confirmed. In this study, microglia were treated with RUX for 24 hours and then activated with interferon-γ for 6 hours. The results showed that interferon-γ-induced phosphorylation of JAK and STAT in microglia was inhibited, and the mRNA expression levels of pro-inflammatory cytokines tumor necrosis factor-α, interleukin-1ß, interleukin-6, and cell proliferation marker Ki67 were reduced. In further in vivo experiments, a mouse model of spinal cord injury was treated intragastrically with RUX for 3 successive days, and the findings suggest that RUX can inhibit microglial proliferation by inhibiting the interferon-γ/JAK/STAT pathway. Moreover, microglia treated with RUX centripetally migrated toward injured foci, remaining limited and compacted within the glial scar, which resulted in axon preservation and less demyelination. Moreover, the protein expression levels of tumor necrosis factor-α, interleukin-1ß, and interleukin-6 were reduced. The neuromotor function of SCI mice also recovered. These findings suggest that RUX can inhibit neuroinflammation through inhibiting the interferon-γ/JAK/STAT pathway, thereby reducing secondary injury after SCI and producing neuroprotective effects.

Biosynthesis of Self-Assembled Proteinaceous Nanoparticles for Vaccination.

Recent years have seen enormous advances in nanovaccines for both prophylactic and therapeutic applications, but most of these technologies employ chemical or hybrid semi-biosynthetic production methods. Thus, production of nanovaccines has to date failed to exploit biology-only processes like complex sequential post-translational biochemical modifications and scalability, limiting the realization of the initial promise for offering major performance advantages and improved therapeutic outcomes over conventional vaccines. A Nano-B5 platform for in vivo production of fully protein-based, self-assembling, stable nanovaccines bearing diverse antigens including peptides and polysaccharides is presented here. Combined with the self-assembly capacities of pentamer domains from the bacterial AB5 toxin and unnatural trimer peptides, diverse nanovaccine structures can be produced in common Escherichia coli strains and in attenuated pathogenic strains. Notably, the chassis of these nanovaccines functions as an immunostimulant. After showing excellent lymph node targeting and immunoresponse elicitation and safety performance in both mouse and monkey models, the strong prophylactic effects of these nanovaccines against infection, as well as their efficient therapeutic effects against tumors are further demonstrated. Thus, the Nano-B5 platform can efficiently combine diverse modular components and antigen cargos to efficiently generate a potentially very large diversity of nanovaccine structures using many bacterial species.

Characteristics of asymptomatic COVID-19 infection and progression: A multicenter, retrospective study.

Novel coronavirus disease 2019 (COVID-19), caused by novel coronavirus SARS-CoV-2, has spread globally since the end of 2019. Asymptomatic carriers are of great concern as they can undermine the interventions to stop the pandemic. However, there is limited information about the characteristics and outcomes of the asymptomatic patients. Therefore, we conducted this retrospective study and retrieved data of 79 asymptomatic COVID-19 patients at admission from three designated hospitals in Wuhan, China. The asymptomatic patients could happen at any age, ranged from 9 to 96 years. These patients also had lower levels of alanine aminotransferase and C-reactive protein. Patchy shadowing was the most common manifestation in computed tomography scan. Some asymptomatic carriers developed mild or moderate symptoms during hospitalization. Age and comorbidities, especially hypertension, may be predictive factors for symptom development in the initially asymptomatic carriers at admission. Early detection and treatment for these presymptomatic patients before symptom onset can shorten the communicable period for the coronavirus and reduce the occurrence of severe cases.

Prognostic Value of Right Ventricular Ejection Fraction Assessed by 3D Echocardiography in COVID-19 Patients.

Background: RVEF (right ventricular ejection fraction) measured by three-dimensional echocardiography (3DE) has been used in evaluating right ventricular (RV) function and can provide useful prognostic information in other various cardiovascular diseases. However, the prognostic value of 3D-RVEF in coronavirus disease 2019 (COVID-19) remains unknown. We aimed to investigate whether 3D-RVEF can predict the mortality of COVID-19 patients. Methods: A cohort of 128 COVID-19-confirmed patients who had undergone echocardiography were studied. Thirty-one healthy volunteers were also enrolled as controls. COVID-19 patients were divided into three subgroups (general, severe, and critical) according to COVID-19 severity-of-illness. Conventional RV structure and function parameters, RV free wall longitudinal strain (FWLS) and 3D-RVEF were acquired. RVFWLS was measured by two-dimensional speckle tracking echocardiography. RVEF was acquired by 3DE. Results: Compared with controls, 2D-RVFWLS and 3D-RVEF were both significantly decreased in COVID-19 patients (-27.2 ± 4.4% vs. -22.9 ± 4.8%, P < 0.001; 53.7 ± 4.5% vs. 48.5 ± 5.8%, P < 0.001). Critical patients were more likely to have a higher incidence of acute cardiac injury and acute respiratory distress syndrome (ARDS), and worse prognosis than general and severe patients. The critical patients exhibited larger right-heart chambers, worse RV fractional area change (RVFAC), 2D-RVFWLS, and 3D-RVEF and higher proportion of pulmonary hypertension than general and severe patients. Eighteen patients died during a median follow-up of 91 days. The multivariate Cox regression analysis revealed the acute cardiac injury, ARDS, RVFAC, RVFWLS, and 3D-RVEF were independent predictors of death. 3D-RVEF (chi-square to improve 18.3; P < 0.001), RVFAC (chi-square to improve 4.5; P = 0.034) and 2D-RVFWLS (chi-square to improve 5.1; P = 0.024) all provided additional prognostic value of higher mortality over clinical risk factors. Moreover, the incremental predictive value of 3D-RVEF was significantly (P < 0.05) higher than RVFAC and RVFWLS. Conclusion: 3D-RVEF was the most robust independent predictor of mortality in COVID-19 patients and provided a higher predictive value over conventional RV function parameters and RVFWLS, which may be helpful to identify COVID-19 patients at a higher risk of death.