Pathophysiological characteristics and therapeutic approaches for pulmonary injury and cardiovascular complications of coronavirus disease 2019

Geng, Yong–Jian; Wei, Zhi Yao; Qian, Hai; Huang, Jian; Lodato, Robert F.; Castriotta, Richard J.

doi:10.1016/j.carpath.2020.107228

Cited by 112 publications

(212 citation statements)

References 72 publications

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“…SARS-CoV-2 infects alveolar epithelial cells in the lungs and causes pneumonia or ARDS (in severe cases). 23 In our study, the degree of hypoxia of the patients was assessed using the PaO 2 /FiO 2 ratio. Severely ill patients had a lower baseline PaO 2 /FiO 2 ratio values than did nonseverely ill patients.…”

Section: Discussionmentioning

confidence: 99%

Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data

Baratella¹,

Crivelli²,

Marrocchio³

et al. 2020

J Bras Pneumol.

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Section: Discussionmentioning

confidence: 99%

Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data

Baratella¹,

Crivelli²,

Marrocchio³

et al. 2020

J Bras Pneumol.

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“…While most cases of COVID-19 are nonfatal, a significant fraction of those infected require extensive supportive care, and the mortality rate is substantially higher than more common infectious diseases such as seasonal influenza (2). Even for survivors, infection can lead to long-term damage to the lungs and other organs, leading to long convalescence times and enhanced risk of secondary complications (3,4). By early March of 2020, COVID-19 outbreaks had appeared on almost every continent, including significant clusters within many cities (5).…”

Section: Standard Epidemiological Models For Covid-19 Employ Variantsmentioning

confidence: 99%

Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity

Thomas

Huang

Yin

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

111

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Standard epidemiological models for COVID-19 employ variants of compartment (SIR or susceptible–infectious–recovered) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion. Based on simulations of unrestricted COVID-19 diffusion in 19 US cities, we conclude that heterogeneity in population distribution can have large impacts on local pandemic timing and severity, even when aggregate behavior at larger scales mirrors a classic SIR-like pattern. Impacts observed include severe local outbreaks with long lag time relative to the aggregate infection curve, and the presence of numerous areas whose disease trajectories correlate poorly with those of neighboring areas. A simple catchment model for hospital demand illustrates potential implications for health care utilization, with substantial disparities in the timing and extremity of impacts even without distancing interventions. Likewise, analysis of social exposure to others who are morbid or deceased shows considerable variation in how the epidemic can appear to individuals on the ground, potentially affecting risk assessment and compliance with mitigation measures. These results demonstrate the potential for spatial network structure to generate highly nonuniform diffusion behavior even at the scale of cities, and suggest the importance of incorporating such structure when designing models to inform health care planning, predict community outcomes, or identify potential disparities.

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“…Such an expression pattern explains the reason why infected ICU patients are afflicted not only with ARDS but also other complications of multiple organ dysfunction syndromes [110]. The mechanisms that account for the improvement observed following MSC infusion in COVID-19 patients seem to be indicative of the strong anti-inflammatory activity of these cells [80].…”

Section: Msc-based Therapy In Covid-19 Patientsmentioning

confidence: 99%

The role of mesenchymal stromal cells in immune modulation of COVID-19: focus on cytokine storm

2020

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The outbreak of coronavirus disease 2019 (COVID-19) pandemic is quickly spreading all over the world. This virus, which is called SARS-CoV-2, has infected tens of thousands of people. Based on symptoms, the pathogenesis of acute respiratory illness is responsible for highly homogenous coronaviruses as well as other pathogens. Evidence suggests that high inflammation rates, oxidation, and overwhelming immune response probably contribute to pathology of COVID-19. COVID-19 causes cytokine storm, which subsequently leads to acute respiratory distress syndrome (ARDS), often ending up in the death of patients. Mesenchymal stem cells (MSCs) are multipotential stem cells that are recognized via self-renewal capacity, generation of clonal populations, and multilineage differentiation. MSCs are present in nearly all tissues of the body, playing an essential role in repair and generation of tissues. Furthermore, MSCs have broad immunoregulatory properties through the interaction of immune cells in both innate and adaptive immune systems, leading to immunosuppression of many effector activities. MSCs can reduce the cytokine storm produced by coronavirus infection. In a number of studies, the administration of these cells has been beneficial for COVID-19 patients. Also, MSCs may be able to improve pulmonary fibrosis and lung function. In this review, we will review the newest research findings regarding MSC-based immunomodulation in patients with COVID-19.

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Pathophysiological characteristics and therapeutic approaches for pulmonary injury and cardiovascular complications of coronavirus disease 2019

Cited by 112 publications

References 72 publications

Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data

Severity of lung involvement on chest X-rays in SARS-coronavirus-2 infected patients as a possible tool to predict clinical progression: an observational retrospective analysis of the relationship between radiological, clinical, and laboratory data

Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity

The role of mesenchymal stromal cells in immune modulation of COVID-19: focus on cytokine storm

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