13
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      When Does the Cytokine Storm Begin in COVID-19 Patients? A Quick Score to Recognize It

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that is responsible for coronavirus disease 2019 (COVID-19), which has rapidly spread across the world, becoming a pandemic. The “cytokine storm” (CS) in COVID-19 leads to the worst stage of illness, and its timely control through immunomodulators, corticosteroids, and cytokine antagonists may be the key to reducing mortality. After reviewing published studies, we proposed a Cytokine Storm Score (CSs) to identify patients who were in this hyperinflammation state, and at risk of progression and poorer outcomes. We retrospectively analyzed 31 patients admitted to Infectious Disease Department in “St. Maria” Hospital in Terni with confirmed SARS-CoV-2 infections, and analyzed the “CS score” (CSs) and the severity of COVID-19. Then we conducted a prospective study of COVID-19 patients admitted after the definition of the CSscore. This is the first study that proposes and applies a new score to quickly identify COVID-19 patients who are in a hyperinflammation stage, to rapidly treat them in order to reduce the risk of intubation. CSs can accurately identify COVID-19 patients in the early stages of a CS, to conduct timely, safe, and effect administration of immunomodulators, corticosteroids, and cytokine antagonists, to prevent progression and reduce mortality.

          Related collections

          Most cited references58

          • Record: found
          • Abstract: found
          • Article: not found

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

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Clinical Characteristics of Coronavirus Disease 2019 in China

            Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

              Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
                Bookmark

                Author and article information

                Journal
                J Clin Med
                J Clin Med
                jcm
                Journal of Clinical Medicine
                MDPI
                2077-0383
                15 January 2021
                January 2021
                : 10
                : 2
                : 297
                Affiliations
                [1 ]Clinical Infectious Disease, Department of medicine, St. Maria Hospital, 05100 Terni, Italy; m.palumbo@ 123456aospterni.it (M.P.); giulia.priante1989@ 123456gmail.com (G.P.); l.martella@ 123456aospterni.it (L.A.M.); lavitrinity@ 123456libero.it (L.M.S.); francesco.sicari@ 123456studenti.unipg.it (F.S.); c.vernelli@ 123456aospterni.it (C.V.); c.digiuli@ 123456aospterni.it (C.D.G.); tiri.beatrice@ 123456gmail.com (B.T.)
                [2 ]Department of General Surgery, Royal Perth Hospital, Perth 6000, Australia; sherm.k@ 123456live.com
                [3 ]Hematology and Microbiology Laboratory, St. Maria Hospital, 05100 Terni, Italy; p.andreani@ 123456aospterni.it (P.A.); a.mariottini@ 123456aospterni.it (A.M.)
                [4 ]Department of General and Oncologic Surgery, St. Maria Hospital, 05100 Terni, Italy; m.francucci@ 123456aospterni.it
                [5 ]Department of Critical Care Medicine and Anesthesiology, St. Maria Hospital, 05100 Terni, Italy; e.sensi@ 123456aospterni.it
                [6 ]Pharmacy Unit, St. Maria Hospital, 05100 Terni, Italy; m.costantini@ 123456aospterni.it
                [7 ]Department of General and Specialist Surgery “Paride Stefanini”, 00185 Rome, Italy; paolo.bruzzone@ 123456uniroma1.it
                [8 ]Department of Surgical Sciences, Sapienza University of Rome, 00161 Rome, Italy; vito.dandrea@ 123456uniroma1.it
                [9 ]Legal Medicine, University of Perugia, 06123 Perugia, Italy; sara.gioia@ 123456unipg.it
                [10 ]Department of General and Oncologic Surgery, University of Perugia, St. Maria Hospital, 05100 Terni, Italy; roberto.cirocchi@ 123456unipg.it
                Author notes
                [* ]Correspondence: s.cappanera@ 123456aospterni.it ; Tel.: +39-074-420-5089
                Author information
                https://orcid.org/0000-0001-5610-5539
                https://orcid.org/0000-0002-7124-1245
                https://orcid.org/0000-0001-5709-2530
                https://orcid.org/0000-0002-2457-0636
                https://orcid.org/0000-0001-5574-7812
                Article
                jcm-10-00297
                10.3390/jcm10020297
                7830161
                33467466
                52d2284f-fc4c-46a3-956a-0bcce7dc0d67
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 December 2020
                : 13 January 2021
                Categories
                Article

                covid-19,cytokine storm,ards
                covid-19, cytokine storm, ards

                Comments

                Comment on this article