Molecular pathogenesis of secondary bacterial infection associated to viral infections including SARS-CoV-2

Manna, Sounik; Baindara, Piyush; Mandal, Santi M.

doi:10.1016/j.jiph.2020.07.003

Cited by 67 publications

(61 citation statements)

References 94 publications

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“…(Manna et al, 2020) provide an overview of viral infections with secondary bacterial infection. They cite evidence of an elevated risk of secondary bacterial infection with viral infection and also outline some of the mechanisms by which this may occur.…”

Section: Resultsmentioning

confidence: 99%

Characterising COVID-19 as a Viral Clotting Fever: A Mixed Methods Scoping Review

Marley

2020

Preprint

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BackgroundThe COVID-19 pandemic has claimed over 1 million lives globally and results from the SARS-COV2 virus. COVID-19 is associated with a coagulopathy. In this mixed-methods PRISMA-compliant scoping review, we set out to determine if ARDS, sepsis and DIC could account for the coagulopathy and if there were any other features of the coagulopathy we could determine so as to inform future research. Methods: We used a search strategy to identify papers with clinically relevant thromboembolic events in COVID-19. We then developed a technique referred to as an Abridged Thematic Analysis (ATA) to quickly identify themes in the papers so as to increase the yield of clinically relevant information. We further developed Validated Abridged Thematic Analysis (VATA) to validate the resulting taxonomy of themes. Finally we developed a number of methods that can be used by other researchers to take forwards this work. Results: We identified 56 studies with 10,523 patients, 456 patients with COVID-19 and thromboembolic events (TBE’s) and 586 thrombembolic events. There were an average of 1.3 TBE’s per patient. There were five main arterial territories with corresponding clinical sequelae: Acute limb ischaemia, myocardial infarcts, strokes, mesenteric ischaemia and pulmonary embolism. We also identified DVT’s. There were two further groups: medical-device-related coagulopathy and dermal lesions. In a subgroup of 119 patients we found mortality ranged from 26% in DVT to 79% in acute limb ischaemia although there was evidence of selection bias in the latter group. All patients were hospitalised and the average age of survivors was 63 versus 73 for those who died. 91/150 patients with TE’s had fever. From the ATA, we identified 16 characteristics of the clotting pathology in COVID-19. From the VATA, we identified 34 mechanisms leading to coagulopathy and grouped them according to Virchow’s triad of vascular damage, stasis and hypercoagulability. Coagulopathy occurred with and without each of ARDS, Sepsis and DIC. We conclude that COVID-19 leads to the syndrome of a viral clotting fever in a subgroup of patients and that the presentation of coagulopathy and fever should raise the possibility of COVID-19 as a differential. We make recommendations for future research studies.

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Section: Resultsmentioning

confidence: 99%

Characterising COVID-19 as a Viral Clotting Fever: A Mixed Methods Scoping Review

Marley

2020

Preprint

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“…Pneumonia caused by viral infections usually has secondary bacterial infection 22 . COVID-19 may also be associated with secondary bacterial infections 23 , 24 . Now, the demonstrated antiviral activity to HCoVs, including SARS-CoV-2, as well as the preferential distribution in lungs via oral administration warranted the clinical trials of carrimycin for the treatment of COVID-19 in China (ChiCTR2000029867 and ChiCTR2000032242).…”

Section: Discussionmentioning

confidence: 99%

Repurposing carrimycin as an antiviral agent against human coronaviruses, including the currently pandemic SARS-CoV-2

Yan

Sun

Wang

et al. 2021

Acta Pharmaceutica Sinica B

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COVID-19 pandemic caused by SARS-CoV-2 infection severely threatens global health and economic development. No effective antiviral drug is currently available to treat COVID-19 and any other human coronavirus infections. We report herein that a CFDA-approved macrolide antibiotic, carrimycin, potently inhibited the cytopathic effects (CPE) and reduced the levels of viral protein and RNA in multiple cell types infected by human coronavirus 229E, OC43, and SARS-CoV-2. Time-of-addition and pseudotype virus infection studies indicated that carrimycin inhibited one or multiple post-entry replication events of human coronavirus infection. In support of this notion, metabolic labelling studies showed that carrimycin significantly inhibited the synthesis of viral RNA. Our studies thus strongly suggest that carrimycin is an antiviral agent against a broad-spectrum of human coronaviruses and its therapeutic efficacy to COVID-19 is currently under clinical investigation.

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“…Viral infections predispose patients to secondary bacterial infections, which often have a more severe clinical course. Secondary bacterial infection has been considered as a critical risk factor for the severity and mortality rates of COVID-19 despite antimicrobial therapies [20,21]. Lymphopenia, leukocytosis, high concentrations of CRP and LDH may indicate severe acute lung inflammatory reaction and cell damage [22][23][24], which has been reported to be risk factors for severe patients with COVID-19 [25].…”

Section: Discussionmentioning

confidence: 99%

Risk Factors Analysis of COVID-19 Patients with ARDS and Prediction Based on Machine Learning

Xu¹,

Sun²,

Gao

et al. 2020

Preprint

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COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute respiratory distress syndrome (ARDS) is one of the common clinical manifestations of severe COVID-19 and it is also responsible for the current shortage of ventilators worldwide. This study aims to analyze the clinical characteristics of COVID-19 ARDS patients and establish a diagnostic system based on artificial intelligence (AI) method to predict the probability of ARDS in COVID-19 patients. We collected clinical data of 659 COVID-19 patients from 11 regions in China. The clinical characteristics of the two groups were elaborately compared and both traditional machine learning algorithms and deep learning-based methods were used to build the prediction models. Results indicated the median age of ARDS patients was 56.5 years old, which was significantly older than those with non-ARDS by 7.5 years. Male and patients with BMI>25 were more likely to develop ARDS. The clinical features of ARDS patients included cough (80.3%), polypnea (59.2%), lung consolidation (53.9%), secondary bacterial infection (30.3%), and comorbidities such as hypertension (48.7%). Abnormal biochemical indicators such as lymphocyte count, leukocyte counting, CK, NLR, AST, LDH, and CRP were all strongly related to the aggravation of ARDS. Furthermore, through various AI methods for modeling and prediction effect evaluation based on the above risk factors, decision tree achieved the best AUC, sensitivity, and specificity in identifying the mild patients who were easy to develop ARDS, which undoubtedly helps to optimize the treatment strategy, reduce mortality, and relieve the medical pressure.

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Molecular pathogenesis of secondary bacterial infection associated to viral infections including SARS-CoV-2

Cited by 67 publications

References 94 publications

Characterising COVID-19 as a Viral Clotting Fever: A Mixed Methods Scoping Review

Characterising COVID-19 as a Viral Clotting Fever: A Mixed Methods Scoping Review

Repurposing carrimycin as an antiviral agent against human coronaviruses, including the currently pandemic SARS-CoV-2

Risk Factors Analysis of COVID-19 Patients with ARDS and Prediction Based on Machine Learning

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