Mixed storm in SARS‐CoV‐2 infection: A narrative review and new term in the Covid‐19 era

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Abstract

Coronavirus disease 2019 (Covid‐19) is caused by a novel severe acute respiratory syndrome coronavirus virus type 2 (SARS‐CoV‐2) leading to the global pandemic worldwide. Systemic complications in Covid‐19 are mainly related to the direct SARS‐CoV‐2 cytopathic effects, associated hyperinflammation, hypercytokinemia, and the development of cytokine storm (CS). As well, Covid‐19 complications are developed due to the propagation of oxidative and thrombotic events which may progress to a severe state called oxidative storm and thrombotic storm (TS), respectively. In addition, inflammatory and lipid storms are also developed in Covid‐19 due to the activation of inflammatory cells and the release of bioactive lipids correspondingly. Therefore, the present narrative review aimed to elucidate the interrelated relationship between different storm types in Covid‐19 and the development of the mixed storm (MS). In conclusion, SARS‐CoV‐2 infection induces various storm types including CS, inflammatory storm, lipid storm, TS and oxidative storm. These storms are not developing alone since there is a close relationship between them. Therefore, the MS seems to be more appropriate to be related to severe Covid‐19 than CS, since it develops in Covid‐19 due to the intricate interface between reactive oxygen species, proinflammatory cytokines, complement activation, coagulation disorders, and activated inflammatory signaling pathway.

Abstract

SARS‐CoV‐2 infection induces various storm types including cytokine storm (CS), inflammatory storm, lipid storm, thrombotic storm (TS), and oxidative storm. These storms are not developing alone since there is a close relationship between them. Therefore, the mixed storm seems to be more appropriate to be related to severe Covid‐19 than CS, since it develops in Covid‐19 due to the intricate interface between reactive oxygen species, proinflammatory cytokines, complement activation, coagulation disorders, and activated inflammatory signaling pathway

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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

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COVID-19: consider cytokine storm syndromes and immunosuppression

Puja Mehta, Daniel McAuley, Michael Brown … (2020)

As of March 12, 2020, coronavirus disease 2019 (COVID-19) has been confirmed in 125 048 people worldwide, carrying a mortality of approximately 3·7%, 1 compared with a mortality rate of less than 1% from influenza. There is an urgent need for effective treatment. Current focus has been on the development of novel therapeutics, including antivirals and vaccines. Accumulating evidence suggests that a subgroup of patients with severe COVID-19 might have a cytokine storm syndrome. We recommend identification and treatment of hyperinflammation using existing, approved therapies with proven safety profiles to address the immediate need to reduce the rising mortality. Current management of COVID-19 is supportive, and respiratory failure from acute respiratory distress syndrome (ARDS) is the leading cause of mortality. 2 Secondary haemophagocytic lymphohistiocytosis (sHLH) is an under-recognised, hyperinflammatory syndrome characterised by a fulminant and fatal hypercytokinaemia with multiorgan failure. In adults, sHLH is most commonly triggered by viral infections 3 and occurs in 3·7–4·3% of sepsis cases. 4 Cardinal features of sHLH include unremitting fever, cytopenias, and hyperferritinaemia; pulmonary involvement (including ARDS) occurs in approximately 50% of patients. 5 A cytokine profile resembling sHLH is associated with COVID-19 disease severity, characterised by increased interleukin (IL)-2, IL-7, granulocyte-colony stimulating factor, interferon-γ inducible protein 10, monocyte chemoattractant protein 1, macrophage inflammatory protein 1-α, and tumour necrosis factor-α. 6 Predictors of fatality from a recent retrospective, multicentre study of 150 confirmed COVID-19 cases in Wuhan, China, included elevated ferritin (mean 1297·6 ng/ml in non-survivors vs 614·0 ng/ml in survivors; p 39·4°C 49 Organomegaly None 0 Hepatomegaly or splenomegaly 23 Hepatomegaly and splenomegaly 38 Number of cytopenias * One lineage 0 Two lineages 24 Three lineages 34 Triglycerides (mmol/L) 4·0 mmol/L 64 Fibrinogen (g/L) >2·5 g/L 0 ≤2·5 g/L 30 Ferritin ng/ml 6000 ng/ml 50 Serum aspartate aminotransferase <30 IU/L 0 ≥30 IU/L 19 Haemophagocytosis on bone marrow aspirate No 0 Yes 35 Known immunosuppression † No 0 Yes 18 The Hscore 11 generates a probability for the presence of secondary HLH. HScores greater than 169 are 93% sensitive and 86% specific for HLH. Note that bone marrow haemophagocytosis is not mandatory for a diagnosis of HLH. HScores can be calculated using an online HScore calculator. 11 HLH=haemophagocytic lymphohistiocytosis. * Defined as either haemoglobin concentration of 9·2 g/dL or less (≤5·71 mmol/L), a white blood cell count of 5000 white blood cells per mm3 or less, or platelet count of 110 000 platelets per mm3 or less, or all of these criteria combined. † HIV positive or receiving longterm immunosuppressive therapy (ie, glucocorticoids, cyclosporine, azathioprine).

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Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China

Qiurong Ruan, Kun Yang, Wenxia Wang … (2020)

Dear Editor, The rapid emergence of COVID-19 in Wuhan city, Hubei Province, China, has resulted in thousands of deaths [1]. Many infected patients, however, presented mild flu-like symptoms and quickly recover [2]. To effectively prioritize resources for patients with the highest risk, we identified clinical predictors of mild and severe patient outcomes. Using the database of Jin Yin-tan Hospital and Tongji Hospital, we conducted a retrospective multicenter study of 68 death cases (68/150, 45%) and 82 discharged cases (82/150, 55%) with laboratory-confirmed infection of SARS-CoV-2. Patients met the discharge criteria if they had no fever for at least 3 days, significantly improved respiratory function, and had negative SARS-CoV-2 laboratory test results twice in succession. Case data included demographics, clinical characteristics, laboratory results, treatment options and outcomes. For statistical analysis, we represented continuous measurements as means (SDs) or as medians (IQRs) which compared with Student’s t test or the Mann–Whitney–Wilcoxon test. Categorical variables were expressed as numbers (%) and compared by the χ 2 test or Fisher’s exact test. The distribution of the enrolled patients’ age is shown in Fig. 1a. There was a significant difference in age between the death group and the discharge group (p < 0.001) but no difference in the sex ratio (p = 0.43). A total of 63% (43/68) of patients in the death group and 41% (34/82) in the discharge group had underlying diseases (p = 0.0069). It should be noted that patients with cardiovascular diseases have a significantly increased risk of death when they are infected with SARS-CoV-2 (p < 0.001). A total of 16% (11/68) of the patients in the death group had secondary infections, and 1% (1/82) of the patients in the discharge group had secondary infections (p = 0.0018). Laboratory results showed that there were significant differences in white blood cell counts, absolute values of lymphocytes, platelets, albumin, total bilirubin, blood urea nitrogen, blood creatinine, myoglobin, cardiac troponin, C-reactive protein (CRP) and interleukin-6 (IL-6) between the two groups (Fig. 1b and Supplementary Table 1). Fig. 1 a Age distribution of patients with confirmed COVID-19; b key laboratory parameters for the outcomes of patients with confirmed COVID-19; c interval from onset of symptom to death of patients with confirmed COVID-19; d summary of the cause of death of 68 died patients with confirmed COVID-19 The survival times of the enrolled patients in the death group were analyzed. The distribution of survival time from disease onset to death showed two peaks, with the first one at approximately 14 days (22 cases) and the second one at approximately 22 days (17 cases) (Fig. 1c). An analysis of the cause of death was performed. Among the 68 fatal cases, 36 patients (53%) died of respiratory failure, five patients (7%) with myocardial damage died of circulatory failure, 22 patients (33%) died of both, and five remaining died of an unknown cause (Fig. 1d). Based on the analysis of the clinical data, we confirmed that some patients died of fulminant myocarditis. In this study, we first reported that the infection of SARS-CoV-2 may cause fulminant myocarditis. Given that fulminant myocarditis is characterized by a rapid progress and a severe state of illness [3], our results should alert physicians to pay attention not only to the symptoms of respiratory dysfunction but also the symptoms of cardiac injury. Further, large-scale studies and the studies on autopsy are needed to confirm our analysis. In conclusion, predictors of a fatal outcome in COVID-19 cases included age, the presence of underlying diseases, the presence of secondary infection and elevated inflammatory indicators in the blood. The results obtained from this study also suggest that COVID-19 mortality might be due to virus-activated “cytokine storm syndrome” or fulminant myocarditis. Electronic supplementary material Below is the link to the electronic supplementary material. Supplementary material 1 (DOCX 38 kb)

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Author and article information

Contributors

Marios Papadakis: marios_papadakis@yahoo.gr

Journal

Journal ID (nlm-ta): Immun Inflamm Dis

Journal ID (iso-abbrev): Immun Inflamm Dis

Journal ID (doi): 10.1002/(ISSN)2050-4527

Journal ID (publisher-id): IID3

Title: Immunity, Inflammation and Disease

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Electronic): 2050-4527

Publication date (Electronic): 26 April 2023

Publication date Collection: April 2023

Volume: 11

Issue: 4 ( doiID: 10.1002/iid3.v11.4 )

Electronic Location Identifier: e838

Affiliations

[ ¹ ] Department of Medicine, College of Medicine, Internal Medicine and Endocrinology Jouf University Al‐Jouf Saudi Arabia

[ ² ] Department of Clinical Pharmacology and Medicine, College of Medicine Al‐Mustansiriya University Baghdad Iraq

[ ³ ] Department of Clinical Pharmacology, Medicine, and Therapeutic, Medical Faculty, College of Medicine Al‐Mustansiriyah University Baghdad Iraq

[ ⁴ ] Department of Science and Engineering Novel Global Community Educational Foundation Hebersham New South Wales Australia

[ ⁵ ] AFNP Med Wien Austria

[ ⁶ ] Department of Surgery II, University Hospital Witten‐Herdecke University of Witten‐Herdecke Wuppertal Germany

[ ⁷ ] Department of Medicine Prince Mohammed Bin Abdulaziz Medical City Sakaka Al‐Jouf Saudi Arabia

[ ⁸ ] Department of Pathology, Faculty of Veterinary Medicine Matrouh University Marsa Matruh Egypt

[ ⁹ ] Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine Damanhour University Damanhour Egypt

Author notes

[*] [* ] Correspondence Marios Papadakis, Department of Surgery II, University Hospital Witten‐Herdecke, Heusnerstrasse 40, University of Witten‐Herdecke, 42283 Wuppertal, Germany.

Email: marios_papadakis@ 123456yahoo.gr

Author information

Athanasios Alexiou http://orcid.org/0000-0002-2206-7236

Majed Ayed Alshammari http://orcid.org/0000-0001-5980-7106

Hebatallah M. Saad http://orcid.org/0000-0001-9555-7300

Article

Publisher ID: IID3838

DOI: 10.1002/iid3.838

PMC ID: 10132185

PubMed ID: 37102645

SO-VID: 8b865203-8686-4f74-ab48-c6a6e9a236fd

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

History

Date revision received : 22 March 2023

Date received : 30 November 2022

Date accepted : 27 March 2023

Page count

Figures: 8, Tables: 2, Pages: 20, Words: 12530

Funding

Funded by: University of Witten‐Herdecke Germany

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source-schema-version-number 2.0

cover-date April 2023

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.7 mode:remove_FC converted:26.04.2023

Keywords: covid‐19,cytokine storm,inflammatory storm,lipid storm,mixed storm,oxidative storm

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Keywords: covid‐19, cytokine storm, inflammatory storm, lipid storm, mixed storm, oxidative storm

Mixed storm in SARS‐CoV‐2 infection: A narrative review and new term in the Covid‐19 era

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Novel Coronavirus Disease COVID-19

Most cited references 193

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

COVID-19: consider cytokine storm syndromes and immunosuppression

Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China

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