Utility of Ferritin, Procalcitonin, and C-reactive Protein in Severe Patients with 2019 Novel Coronavirus Disease

Utility of Ferritin, Procalcitonin, and C-reactive Protein in Severe Patients with 2019 Novel Coronavirus Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Utility of Ferritin, Procalcitonin, and C-reactive Protein in Severe Patients with 2019 Novel Coronavirus Disease Bo Zhou, Jianqing She, Yadan Wang, Xiancang Ma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-18079/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives It is of clinical significance to evaluate the disease severity and investigate possible biomarkers of 2019 Novel coronavirus disease (COVID-19). In this study, we aim to describe the clinical characteristics of infection makers in severe and very severe patients with COVID-19. Methods This is a single center, observational analysis. We enrolled 48 in-hospital severe patients with COVID-19 admitted to the West District of Union Hospital of Tongji Medical College and analyzed infection biomarkers in 20 patients who had been tested for ferritin, PCT, CRP, etc. Results The median age was 59yrd (inter quartile range [IQR]:46-61) among severe COVID-19 group and 57yrd (IQR:45-71.5) among very severe group. We noted significantly increased CRP (1.48mg/L [IQR: 16.69-2.74] vs. 57.98mg/L [IQR: 38.335-77.565], P<0.05), PCT(0.05ng/ml [IQR: 0.03-0.06] vs. 0.21ng/ml [IQR: 0.11-0.42], P<0.05) and ferritin (291.13ng/ml [IQR: 102.1-648.42] vs. 1006.16ng/ml [IQR: 408.265-1988.25]). For blood count, significant increase was noticed in neutrophil percentage (67.6% [IQR: 61.8-76.4] vs. 86.7% [IQR: 82-92.35], P<0.01) and neutrophil count (3.75*10^9/L [IQR: 3.42-4.93] vs. 8.11*10^9/L [IQR: 5.675-8.905], P<0.05); and decrease was seen in lymphocyte percentage (22.7% [IQR: 17.4-27.4] vs. 8% [IQR: 4.85-13], P<0.05), lymphocyte count (1.62*10^9/L [IQR: 0.7-1.73] vs. 0.68*10^9/L [IQR: 0.385-1.04], P<0.05), and platelet count (214*10^9/L [IQR: 184-247] vs. 147*10^9/L [IQR: 126-202.5], P<0.05). Conclusions The serum levels of CRP, PCT and ferritin are markedly increased in very severe compared with severe COVID-19. Increased CRP, PCT and ferritin level might correlate to secondary bacterial infection and associated with poor clinical prognosis. Pulmonology Infectious Diseases COVID-19 Biomarkers C-reactive protein Ferritin Procalcitonin Background The outbreak of 2019 Novel coronavirus disease (COVID-19) has caused global attention 1 − 6 . Up to 12th March, 80981 laboratory-confirmed cases in China and 46728 outside China have been documented, with a total of 4734 deaths 7 . Due to its rapid spread worldwide 8 , COVID-19 was declared as a public health emergency by the World Health Organization 9 − 13 . Although most patients have mild symptoms and good prognosis, severe COVID-19 cases may present with acute respiratory distress syndrome (ARDS) and systemic inflammation. Thus, it is urgent to evaluate the disease severity and investigate possible biomarkers so as to make fast and correct clinical decisions. One recent study has pointed out that the patients with COVID-19 usually have increased serum C-reactive protein (CRP) (58.3%), lactate dehydrogenase (LDH) (57.0%) and erythrocyte sedimentation rate (ESR) (41.8%) 14 . But more evidence regarding other infection markers in COVID-19 needs further study. Of note, previous studies have established ferritin as a possible inflammation marker in pneumonia, associating with the progression of bacterial and viral infection. However, no evidence has been released how ferritin is altered in COVID-19. In the present single center, observational analysis, we explored the infection biomarkers, including ferritin, procalcitonin (PCT), and CRP in in-hospital patients with severe and very severe COVID-19. We aim to describe the clinical characteristics of infection makers in severe and very severe patients with COVID-19. Methods Study design and participants This is a single center, observational analysis. We enrolled 48 in-hospital severe patients with COVID-19 admitted to the West District of Union Hospital of Tongji Medical College in the 7th floor ward from February 5th to February 25th, 2020, and analyzed infection biomarkers in 20 patients who had been tested for ferritin, PCT, CRP, etc. COVID-19 was diagnosed upon admission based on the New Coronavirus Pneumonia Prevention and Control Program (4th edition) published by the National Health Commission of China 6 . Severe COVID-19 was defined as having either one of the flowing criteria: 1) Respiratory distress with respiratory rate more than 30 times/min; 2) Oxygen saturation ≤ 93% in resting state; 3) PaO2/FiO2 ≤ 300 mmHg (1mmHg = 0.133 kPa). And very severe COVID-19 was defined as having either one of the flowing criteria: 1) Respiratory failure in need of mechanical ventilation; 2) Shock; 3) Other organ dysfunction. Patients with previous medical history of acute coronary syndrome were excluded. The study was approved by the ethics committee of the local hospital and data were collected retrospectively. Data Collection And Infection Biomarker Measurement Demographic and epidemiological data including age, sex, and disease history were collected upon admission. Real-time polymerase chain reaction testing was used to detect COVID-19 according to the recommended protocol in the laboratory department of the hospital 15 . Serum samples were collected from the patients upon admission, and blood count, CRP, PCT, and ferritin were tested by the laboratory department. Statistical analysis All statistical analyses were performed by SPSS for Windows 25.0 (SPSS Inc. Chicago, IL). Data were presented as percentages for categorical variables and median ± IQR (Inter Quartile Range) for continuous variables, unless otherwise indicated. Simple t test was used to compare continuous variables which are in normal distribution. Mann-Whitney U test was used to compare continuous variables which do not conform to the normal distribution. Fisher’s exact test was used to compare categorical variables. Fisher’s exact test was used to compare categorical variables. A value of p < 0.05 was considered statistically significant. Results 9 patients with severe and 11 with very severe COVID-19 were included in this analysis. Baseline data for the cases enrolled were shown in Table 1 . The median age was 59yrd (inter quartile range [IQR]:46–61) among severe COVID-19 group and 57yrd (IQR:45-71.5) among very severe group. The male percentage was much higher (3 [33.33%] of 9 vs. 8 [72.73%] of 11) in very severe group. Kidney and liver function showed no statistical significance with regards to creatine (59.9 µmol/L [IQR: 53.3–60.9] vs. 71.8 µmol/L [IQR: 61.85–89.2]), aspartate Aminotransferase (AST) (27 U/L [IQR: 18 –30] vs. 45 U/L [IQR: 28.5–67]) and alanine aminotransferase (ALT) (36 U/L [IQR: 27–57] vs. 45 U/L [IQR: 27-97.5]). Table 1 Baseline Information of the Patients Enrolled Median(IQR) P Value Reference Variable Severe Very Severe Number 9 11 Sex(Male%) 33.33% 72.73% ns Age(yrs) 59(46–61) 57(45-71.5) ns CRE(µmol/L) 59.9(53.3–60.9) 71.8(61.85–89.2) ns 57.0-111.0 AST(U/L) 27(18–30) 45(28.5–67) ns 8–40 ALT(U/L) 36(27–57) 45(27-97.5) ns 5–40 CK(U/L) 98(90–112) 186(90.5-244.5) ns 24–194 CKMB(U/L) 9(9–17) 18(10–19) ns 0–25 Abbreviations : IQR: inter quartile range; CRE: Creatine; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; CK: Creatine Kinase; CKMB: Creatine kinase–MB; CK: Creatine Kinase; CKMB: Creatine kinase–MB. All patients were tested for infection markers including LDH, CRP, PCT, ferritin and blood count (Table 2 ). We noted significantly increased LDH (195 U/L [IQR: 170–226] vs. 411 U/L [IQR: 346.5–578], P < 0.001), CRP (1.48 mg/L [IQR: 16.69–2.74] vs. 57.98 mg/L [IQR: 38.335–77.565], P < 0.05), PCT(0.05 ng/ml [IQR: 0.03–0.06] vs. 0.21 ng/ml [IQR: 0.11–0.42], P < 0.05) and ferritin (291.13 ng/ml [IQR: 102.1-648.42] vs. 1006.16 ng/ml [IQR: 408.265-1988.25]). For blood count, significant increase was noticed in neutrophil percentage (67.6% [IQR: 61.8–76.4] vs. 86.7% [IQR: 82-92.35], P < 0.01) and neutrophil count (3.75*10^9/L [IQR: 3.42–4.93] vs. 8.11*10^9/L [IQR: 5.675–8.905], P < 0.05); and decrease was seen in lymphocyte percentage (22.7% [IQR: 17.4–27.4] vs. 8% [IQR: 4.85-13], P < 0.05), lymphocyte count (1.62*10^9/L [IQR: 0.7–1.73] vs. 0.68*10^9/L [IQR: 0.385–1.04], P < 0.05), and platelet count (214*10^9/L [IQR: 184–247] vs. 147*10^9/L [IQR: 126-202.5], P < 0.05). Table 2 LDH, CRP, PCT and Blood Count in Severe and Very Severe Patients with COVID-19 Median(IQR) P Value Reference Variable Severe Very Severe LDH(U/L) 195(170–226) 411(346.5–578) < 0.001 109–245 CRP(mg/L) 1.48(16.69–2.74) 57.98(38.335–77.565) < 0.05 0–8 PCT(ng/ml) 0.05(0.03–0.06) 0.21(0.11–0.42) < 0.05 < 0.05 FERR(ng/ml) 291.13(102.1-648.42) 1006.16(408.265-1988.25) < 0.05 4.62–204 WBC count(*10^9/L) 6.07(5.48–7.22) 8.94(6.46-10.525) ns 3.5–9.5 NE% 67.6(61.8–76.4) 86.7(82-92.35) < 0.01 40–75 LY% 22.7(17.4–27.4) 8(4.85-13) < 0.05 20–50 NE count(*10^9/L) 3.75(3.42–4.93) 8.11(5.675–8.905) < 0.05 1.8–6.3 LY count(*10^9/L) 1.62(0.7–1.73) 0.68(0.385–1.04) < 0.05 1.1–3.2 PLT count(*10^9/L) 214(184–247) 147(126-202.5) < 0.05 125–350 Abbreviations : IQR: inter quartile range; LDH: Lactate dehydrogenase; CRP: C reactive protein; PCT: Procalcitonin; FERR: Ferritin; WBC: White Blood Cell; NE%: Neutrophil percentage; LY%: Lymphocyte percentage; NE count: Neutrophil count; LY count: Lymphocyte count; PLT count: platelet count. Fisher’s exact test was then applied to compare the rate with abnormal LDH, CRP, PCT, ferritin and blood count between severe and very severe COVID-19, and relative risk was calculated. The results showed that PCT and PLT count had statistical significance (P < 0.05), and CRP, ferritin and LY% had towards statistical significance (P = 0.07) (Table 3 ), indicating that PCT, CRP, ferritin, LY% and PLT count might be possible markers for the progression of disease in severe and very severe COVID-19. Table 3 Risk ratio for severity of COVID-19 Variable Odds Ratio 95% Confidence Interval P value LDH(U/L) 21.33 1.81 ~ 251.26 0.65 CRP(mg/L) 6.67 0.61 ~ 73.03 0.07 PCT(ng/ml) 4.57 0.41 ~ 51.14 0.03 FERR(ng/ml) 2.00 0.27 ~ 14.70 0.07 NE% 9.60 0.88 ~ 105.17 0.18 LY% 0.45 0.24 ~ 0.87 0.07 NE count(*10^9/L) 3.50 0.55 ~ 22.30 1.00 LY count(*10^9/L) 6.13 0.83 ~ 45.02 0.65 PLT count(*10^9/L) 1.50 0.95 ~ 2.38 0.00 Abbreviations : IQR: inter quartile range; LDH: Lactate dehydrogenase; CRP: C reactive protein; PCT: Procalcitonin; FERR: Ferritin; NE%: Neutrophil percentage; LY%: Lymphocyte percentage; NE count: Neutrophil count; LY count: Lymphocyte count; PLT count: platelet count. Discussion In this observational study, we have focused on the infection markers in severe and very severe patients with COVID-19. The serum levels of LDH, CRP, PCT and ferritin are markedly increased in very severe patients compared with severe COVID-19, suggesting that increased LDH, CRP, PCT and ferritin level might stand for more severe secondary bacterial infection and exacerbated COVID-19. Moreover, lymphocyte count is decreased in very severe patients compared with severe COVID-19, indicating that lower lymphocyte count correlate to poor prognosis in COVID-19. In the present analysis, we firstly evaluated serum ferritin levels in COVID-19, which are significantly elevated during critical infection. The function of ferritin including iron binding and storage is associated with the immune and inflammatory response 16 . The reasons of increased ferritin include bacterial and/or viral infection, hemochromatosis and long-term transfusion 17 . When bacterial and/or viral infection takes place, the increase of serum ferritin is related to the release of iron in the reticuloendothelial system, the decrease of the ability of transporting ferritin in liver and spleen, and increased synthesis and release of intracellular ferritin 18, 19 . Some studies showed that patients with bacterial infection had higher ferritin level compared to viral infection 20, 21 . Previous review has also proposed a model that the inflammatory response to viral (IL-18/ferritin) presents as specific plasma patterns of immune biomarkers 17 . Moreover, elevation of serum ferritin levels predicts a poor outcome in hospitalized patients with influenza infection 16 . In the present study, the patients in severe and very severe COVID-19 both exhibits increase serum ferritin level, but the serum ferritin in very severe COVID-19 group is significantly higher than that of severe COVID-19 group. The increased ferritin might indicate severe secondary bacterial infection in COVID-19, and might be utilized as a marker of poor prognosis. As we known, when inflammation or tissue damage happens, CRP can be significantly increased in serum, which is usually used as a unique inflammatory marker in the current clinical practice 22 . On the other hand, PCT, as the precursor of calcitonin, is a kind of glycoprotein without hormone activity, which is significantly higher in bacterial infection, but remain normal or slightly increased in viral infection 22, 23 . Consistently, our study shows that CRP and PCT are markedly increased in severe and very severe COVID-19, and significantly higher in very severe COVID-19. This further correlates to the implication of the serum ferritin alteration, that most of severe patients in COVID-19 have viral infection and secondary bacterial infection. One important limitation of the present study is that we have only observed infection biomarkers in limited COVID-19 patients; the small sample size have prevented us from reaching diagnostic value of infection markers in very severe COVID-19. Secondly, the present study hasn’t evaluated the relationship between infection matkers and prognosis of all the patients enrolled. With more clinical information acquired from COVID-19 patients, further large population-based prospective studies coulf provide further evidence how infection biomarkers are altered and what it indicate in COVID-19. Conclusion In the present study, we investigated the infection markers in patients with severe and very severe COVID-19, including serum levels of CRP, PCT and serum ferritin. Higher levels of CRP, PCT and serum ferritin in very severe COVID-19 as compared to severe COVID-19 might be correlated to secondary bacterial infection, protection from which could be of vital importance for reducing the mortality rate in very severe COVID-19. Abbreviations ARDS Acute respiratory distress syndrome ALT Alanine aminotransferase AST Aspartate Aminotransferase CDC Chinese Center for Disease Control and Prevention CRP C-reactive protein COVID-19 2019 Novel coronavirus disease ESR Erythrocyte sedimentation rate IQR Inter quartile range LDH Lactate Dehydrogenase PCT Procalcitonin Declarations Ethics approval and consent to participate The study was approved by the ethics committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Written informed consent was obtained from all participants. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Funding This study was funded by the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University, China (No.XJTU1AF-CRF-2018-025). Competing interests The authors declare that they have no competing interests. Authors' contributions BZ, XM and YW collected the clinical and laboratory data. JS processed statistical analysis. JS and BZ drafted the manuscript. BZ, XM and YW revised the final manuscript. BZ, XM and YW is responsible for all clinical and laboratory data. Acknowledgments We thank all patients involved in the study. References Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X and Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA . 2020. 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Kawamata R, Yokoyama K, Sato M, Goto M, Nozaki Y, Takagi T, Kumagai H and Yamagata T. Utility of serum ferritin and lactate dehydrogenase as surrogate markers for steroid therapy for Mycoplasma pneumoniae pneumonia. J Infect Chemother . 2015;21:783-9. Choi YJ, Jeon JH and Oh JW. Critical combination of initial markers for predicting refractory Mycoplasma pneumoniae pneumonia in children: a case control study. Respir Res . 2019;20:193. Memar MY, Varshochi M, Shokouhi B, Asgharzadeh M and Kafil HS. Procalcitonin: The marker of pediatric bacterial infection. Biomed Pharmacother . 2017;96:936-943. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-18079","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":425609,"identity":"3afba186-a2a5-4c7f-9cd3-2a23595cb6a9","order_by":1,"name":"Bo Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYDACCQY2BsYGGxgHBBKI0pLGwAPmJBCv5TBECwMxWuRnN7A9+LjjvL29RAKbhOWPwwz87DkGDD934NbCOOcAu+HMM7cTeyQSmA0kEg4zSPa8MWDsPYNbCzPQcGnettsJPBIJjA9AWgxu5BgwM7bh1sIG0XLOHqiF4QBIiz0hLTwQLQcYe+C2SBDQIiED9ktyYs+Zh80GEmnpPBJnnhUc7MWjBRpidvbs7cnHpCVsrOX425M3PviJRwsDA/8HKIOxgRkY++D4OYBPAwpg/EBYzSgYBaNgFIxAAAD+FEdRozy3NgAAAABJRU5ErkJggg==","orcid":"","institution":"the First Affiliated Hospital of Medical School of Xi’an Jiaotong Universitythe First Affiliated Hospital of Medical School of Xi’an Jiaotong University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Zhou","suffix":""},{"id":425610,"identity":"61e4fc24-12a6-4478-8beb-ce7f3b251a63","order_by":2,"name":"Jianqing She","email":"","orcid":"","institution":"the First Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jianqing","middleName":"","lastName":"She","suffix":""},{"id":425611,"identity":"d174f5c3-b221-43e9-8501-d93b0215b35d","order_by":3,"name":"Yadan Wang","email":"","orcid":"","institution":"the First Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yadan","middleName":"","lastName":"Wang","suffix":""},{"id":425612,"identity":"dd85ec26-e4f6-48c3-a74c-d8787f9d74d5","order_by":4,"name":"Xiancang Ma","email":"","orcid":"","institution":"the First Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiancang","middleName":"","lastName":"Ma","suffix":""}],"badges":[],"createdAt":"2020-03-18 16:46:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-18079/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-18079/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13494627,"identity":"0259f7ca-3b64-495d-9be1-4e0fef713aff","added_by":"auto","created_at":"2021-09-16 22:41:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":262717,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-18079/v1/d4a5be57-6d35-44ff-bc9c-f32acb835b35.pdf"}],"financialInterests":"","formattedTitle":"Utility of Ferritin, Procalcitonin, and C-reactive Protein in Severe Patients with 2019 Novel Coronavirus Disease","fulltext":[{"header":"Background","content":" \u003cp\u003eThe outbreak of 2019 Novel coronavirus disease (COVID-19) has caused global attention\u003csup\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;6\u003c/sup\u003e. Up to 12th March, 80981 laboratory-confirmed cases in China and 46728 outside China have been documented, with a total of 4734 deaths\u003csup\u003e7\u003c/sup\u003e. Due to its rapid spread worldwide\u003csup\u003e8\u003c/sup\u003e, COVID-19 was declared as a public health emergency by the World Health Organization\u003csup\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough most patients have mild symptoms and good prognosis, severe COVID-19 cases may present with acute respiratory distress syndrome (ARDS) and systemic inflammation. Thus, it is urgent to evaluate the disease severity and investigate possible biomarkers so as to make fast and correct clinical decisions. One recent study has pointed out that the patients with COVID-19 usually have increased serum C-reactive protein (CRP) (58.3%), lactate dehydrogenase (LDH) (57.0%) and erythrocyte sedimentation rate (ESR) (41.8%)\u003csup\u003e14\u003c/sup\u003e. But more evidence regarding other infection markers in COVID-19 needs further study. Of note, previous studies have established ferritin as a possible inflammation marker in pneumonia, associating with the progression of bacterial and viral infection. However, no evidence has been released how ferritin is altered in COVID-19.\u003c/p\u003e \u003cp\u003eIn the present single center, observational analysis, we explored the infection biomarkers, including ferritin, procalcitonin (PCT), and CRP in in-hospital patients with severe and very severe COVID-19. We aim to describe the clinical characteristics of infection makers in severe and very severe patients with COVID-19.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis is a single center, observational analysis. We enrolled 48 in-hospital severe patients with COVID-19 admitted to the West District of Union Hospital of Tongji Medical College in the 7th floor ward from February 5th to February 25th, 2020, and analyzed infection biomarkers in 20 patients who had been tested for ferritin, PCT, CRP, etc. COVID-19 was diagnosed upon admission based on the New Coronavirus Pneumonia Prevention and Control Program (4th edition) published by the National Health Commission of China\u003csup\u003e6\u003c/sup\u003e. Severe COVID-19 was defined as having either one of the flowing criteria: 1) Respiratory distress with respiratory rate more than 30 times/min; 2) Oxygen saturation\u0026thinsp;\u0026le;\u0026thinsp;93% in resting state; 3) PaO2/FiO2\u0026thinsp;\u0026le;\u0026thinsp;300\u0026nbsp;mmHg (1mmHg\u0026thinsp;=\u0026thinsp;0.133\u0026nbsp;kPa). And very severe COVID-19 was defined as having either one of the flowing criteria: 1) Respiratory failure in need of mechanical ventilation; 2) Shock; 3) Other organ dysfunction. Patients with previous medical history of acute coronary syndrome were excluded. The study was approved by the ethics committee of the local hospital and data were collected retrospectively.\u003c/p\u003e \u003c/div\u003e \n\u003ch2\u003eData Collection And Infection Biomarker Measurement\u003c/h2\u003e\n \u003cp\u003eDemographic and epidemiological data including age, sex, and disease history were collected upon admission. Real-time polymerase chain reaction testing was used to detect COVID-19 according to the recommended protocol in the laboratory department of the hospital\u003csup\u003e15\u003c/sup\u003e. Serum samples were collected from the patients upon admission, and blood count, CRP, PCT, and ferritin were tested by the laboratory department.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed by SPSS for Windows 25.0 (SPSS Inc. Chicago, IL). Data were presented as percentages for categorical variables and median\u0026thinsp;\u0026plusmn;\u0026thinsp;IQR (Inter Quartile Range) for continuous variables, unless otherwise indicated. Simple t test was used to compare continuous variables which are in normal distribution. Mann-Whitney U test was used to compare continuous variables which do not conform to the normal distribution. Fisher\u0026rsquo;s exact test was used to compare categorical variables. Fisher\u0026rsquo;s exact test was used to compare categorical variables. A value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003e9 patients with severe and 11 with very severe COVID-19 were included in this analysis. Baseline data for the cases enrolled were shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age was 59yrd (inter quartile range [IQR]:46\u0026ndash;61) among severe COVID-19 group and 57yrd (IQR:45-71.5) among very severe group. The male percentage was much higher (3 [33.33%] of 9 vs. 8 [72.73%] of 11) in very severe group. Kidney and liver function showed no statistical significance with regards to creatine (59.9\u0026nbsp;\u0026micro;mol/L [IQR: 53.3\u0026ndash;60.9] vs. 71.8\u0026nbsp;\u0026micro;mol/L [IQR: 61.85\u0026ndash;89.2]), aspartate Aminotransferase (AST) (27\u0026nbsp;U/L [IQR: \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;30] vs. 45\u0026nbsp;U/L [IQR: 28.5\u0026ndash;67]) and alanine aminotransferase (ALT) (36\u0026nbsp;U/L [IQR: 27\u0026ndash;57] vs. 45\u0026nbsp;U/L [IQR: 27-97.5]).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eBaseline Information of the Patients Enrolled\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eMedian(IQR)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eP Value\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eVariable\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eSevere\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eVery Severe\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNumber\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e9\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e11\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eSex(Male%)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e33.33%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e72.73%\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAge(yrs)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e59(46\u0026ndash;61)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e57(45-71.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eCRE(\u0026micro;mol/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e59.9(53.3\u0026ndash;60.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e71.8(61.85\u0026ndash;89.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.0-111.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAST(U/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e27(18\u0026ndash;30)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e45(28.5\u0026ndash;67)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e8\u0026ndash;40\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eALT(U/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e36(27\u0026ndash;57)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e45(27-97.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e5\u0026ndash;40\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eCK(U/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e98(90\u0026ndash;112)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e186(90.5-244.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e24\u0026ndash;194\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eCKMB(U/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e9(9\u0026ndash;17)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e18(10\u0026ndash;19)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u0026ndash;25\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAbbreviations\u003c/span\u003e: IQR: inter quartile range; CRE: Creatine; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; CK: Creatine Kinase; CKMB: Creatine kinase\u0026ndash;MB; CK: Creatine Kinase; CKMB: Creatine kinase\u0026ndash;MB.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll patients were tested for infection markers including LDH, CRP, PCT, ferritin and blood count (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We noted significantly increased LDH (195\u0026nbsp;U/L [IQR: 170\u0026ndash;226] vs. 411\u0026nbsp;U/L [IQR: 346.5\u0026ndash;578], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CRP (1.48\u0026nbsp;mg/L [IQR: 16.69\u0026ndash;2.74] vs. 57.98\u0026nbsp;mg/L [IQR: 38.335\u0026ndash;77.565], P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), PCT(0.05\u0026nbsp;ng/ml [IQR: 0.03\u0026ndash;0.06] vs. 0.21\u0026nbsp;ng/ml [IQR: 0.11\u0026ndash;0.42], P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and ferritin (291.13\u0026nbsp;ng/ml [IQR: 102.1-648.42] vs. 1006.16\u0026nbsp;ng/ml [IQR: 408.265-1988.25]). For blood count, significant increase was noticed in neutrophil percentage (67.6% [IQR: 61.8\u0026ndash;76.4] vs. 86.7% [IQR: 82-92.35], P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and neutrophil count (3.75*10^9/L [IQR: 3.42\u0026ndash;4.93] vs. 8.11*10^9/L [IQR: 5.675\u0026ndash;8.905], P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); and decrease was seen in lymphocyte percentage (22.7% [IQR: 17.4\u0026ndash;27.4] vs. 8% [IQR: 4.85-13], P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), lymphocyte count (1.62*10^9/L [IQR: 0.7\u0026ndash;1.73] vs. 0.68*10^9/L [IQR: 0.385\u0026ndash;1.04], P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and platelet count (214*10^9/L [IQR: 184\u0026ndash;247] vs. 147*10^9/L [IQR: 126-202.5], P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eLDH, CRP, PCT and Blood Count in Severe and Very Severe Patients with COVID-19\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eMedian(IQR)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eP Value\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cdiv class=\"SimplePara\"\u003eReference\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eVariable\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eSevere\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eVery Severe\u003c/span\u003e\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eLDH(U/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e195(170\u0026ndash;226)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e411(346.5\u0026ndash;578)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e109\u0026ndash;245\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eCRP(mg/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.48(16.69\u0026ndash;2.74)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e57.98(38.335\u0026ndash;77.565)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0\u0026ndash;8\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePCT(ng/ml)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.05(0.03\u0026ndash;0.06)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.21(0.11\u0026ndash;0.42)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eFERR(ng/ml)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e291.13(102.1-648.42)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1006.16(408.265-1988.25)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e4.62\u0026ndash;204\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eWBC count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.07(5.48\u0026ndash;7.22)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e8.94(6.46-10.525)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003ens\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.5\u0026ndash;9.5\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNE%\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e67.6(61.8\u0026ndash;76.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e86.7(82-92.35)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.01\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e40\u0026ndash;75\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eLY%\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e22.7(17.4\u0026ndash;27.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e8(4.85-13)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e20\u0026ndash;50\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNE count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.75(3.42\u0026ndash;4.93)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e8.11(5.675\u0026ndash;8.905)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.8\u0026ndash;6.3\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eLY count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.62(0.7\u0026ndash;1.73)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.68(0.385\u0026ndash;1.04)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.1\u0026ndash;3.2\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePLT count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e214(184\u0026ndash;247)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e147(126-202.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.05\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e125\u0026ndash;350\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAbbreviations\u003c/span\u003e: IQR: inter quartile range; LDH: Lactate dehydrogenase; CRP: C reactive protein; PCT: Procalcitonin; FERR: Ferritin; WBC: White Blood Cell; NE%: Neutrophil percentage; LY%: Lymphocyte percentage; NE count: Neutrophil count; LY count: Lymphocyte count; PLT count: platelet count.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFisher\u0026rsquo;s exact test was then applied to compare the rate with abnormal LDH, CRP, PCT, ferritin and blood count between severe and very severe COVID-19, and relative risk was calculated. The results showed that PCT and PLT count had statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and CRP, ferritin and LY% had towards statistical significance (P\u0026thinsp;=\u0026thinsp;0.07) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), indicating that PCT, CRP, ferritin, LY% and PLT count might be possible markers for the progression of disease in severe and very severe COVID-19.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cdiv class=\"SimplePara\"\u003eRisk ratio for severity of COVID-19\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eVariable\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eOdds Ratio\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e95% Confidence Interval\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003eP value\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eLDH(U/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e21.33\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.81\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e251.26\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.65\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eCRP(mg/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.67\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.61\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e73.03\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.07\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePCT(ng/ml)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e4.57\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.41\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e51.14\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.03\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eFERR(ng/ml)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2.00\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.27\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e14.70\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.07\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNE%\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e9.60\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.88\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e105.17\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.18\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eLY%\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.45\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.24\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.87\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.07\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNE count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e3.50\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.55\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e22.30\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.00\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eLY count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e6.13\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.83\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e45.02\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.65\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePLT count(*10^9/L)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e1.50\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.95\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e~\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e2.38\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cdiv class=\"SimplePara\"\u003e0.00\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAbbreviations\u003c/span\u003e: IQR: inter quartile range; LDH: Lactate dehydrogenase; CRP: C reactive protein; PCT: Procalcitonin; FERR: Ferritin; NE%: Neutrophil percentage; LY%: Lymphocyte percentage; NE count: Neutrophil count; LY count: Lymphocyte count; PLT count: platelet count.\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eIn this observational study, we have focused on the infection markers in severe and very severe patients with COVID-19. The serum levels of LDH, CRP, PCT and ferritin are markedly increased in very severe patients compared with severe COVID-19, suggesting that increased LDH, CRP, PCT and ferritin level might stand for more severe secondary bacterial infection and exacerbated COVID-19. Moreover, lymphocyte count is decreased in very severe patients compared with severe COVID-19, indicating that lower lymphocyte count correlate to poor prognosis in COVID-19.\u003c/p\u003e \u003cp\u003eIn the present analysis, we firstly evaluated serum ferritin levels in COVID-19, which are significantly elevated during critical infection. The function of ferritin including iron binding and storage is associated with the immune and inflammatory response\u003csup\u003e16\u003c/sup\u003e. The reasons of increased ferritin include bacterial and/or viral infection, hemochromatosis and long-term transfusion\u003csup\u003e17\u003c/sup\u003e. When bacterial and/or viral infection takes place, the increase of serum ferritin is related to the release of iron in the reticuloendothelial system, the decrease of the ability of transporting ferritin in liver and spleen, and increased synthesis and release of intracellular ferritin\u003csup\u003e18, 19\u003c/sup\u003e. Some studies showed that patients with bacterial infection had higher ferritin level compared to viral infection\u003csup\u003e20, 21\u003c/sup\u003e. Previous review has also proposed a model that the inflammatory response to viral (IL-18/ferritin) presents as specific plasma patterns of immune biomarkers\u003csup\u003e17\u003c/sup\u003e. Moreover, elevation of serum ferritin levels predicts a poor outcome in hospitalized patients with influenza infection\u003csup\u003e16\u003c/sup\u003e. In the present study, the patients in severe and very severe COVID-19 both exhibits increase serum ferritin level, but the serum ferritin in very severe COVID-19 group is significantly higher than that of severe COVID-19 group. The increased ferritin might indicate severe secondary bacterial infection in COVID-19, and might be utilized as a marker of poor prognosis.\u003c/p\u003e \u003cp\u003eAs we known, when inflammation or tissue damage happens, CRP can be significantly increased in serum, which is usually used as a unique inflammatory marker in the current clinical practice\u003csup\u003e22\u003c/sup\u003e. On the other hand, PCT, as the precursor of calcitonin, is a kind of glycoprotein without hormone activity, which is significantly higher in bacterial infection, but remain normal or slightly increased in viral infection\u003csup\u003e22, 23\u003c/sup\u003e. Consistently, our study shows that CRP and PCT are markedly increased in severe and very severe COVID-19, and significantly higher in very severe COVID-19. This further correlates to the implication of the serum ferritin alteration, that most of severe patients in COVID-19 have viral infection and secondary bacterial infection.\u003c/p\u003e \u003cp\u003eOne important limitation of the present study is that we have only observed infection biomarkers in limited COVID-19 patients; the small sample size have prevented us from reaching diagnostic value of infection markers in very severe COVID-19. Secondly, the present study hasn\u0026rsquo;t evaluated the relationship between infection matkers and prognosis of all the patients enrolled. With more clinical information acquired from COVID-19 patients, further large population-based prospective studies coulf provide further evidence how infection biomarkers are altered and what it indicate in COVID-19.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eIn the present study, we investigated the infection markers in patients with severe and very severe COVID-19, including serum levels of CRP, PCT and serum ferritin. Higher levels of CRP, PCT and serum ferritin in very severe COVID-19 as compared to severe COVID-19 might be correlated to secondary bacterial infection, protection from which could be of vital importance for reducing the mortality rate in very severe COVID-19.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eARDS Acute respiratory distress syndrome\u003c/p\u003e \u003cp\u003eALT Alanine aminotransferase\u003c/p\u003e \u003cp\u003eAST Aspartate Aminotransferase\u003c/p\u003e \u003cp\u003eCDC Chinese Center for Disease Control and Prevention\u003c/p\u003e \u003cp\u003eCRP C-reactive protein\u003c/p\u003e \u003cp\u003eCOVID-19 2019 Novel coronavirus disease\u003c/p\u003e \u003cp\u003eESR Erythrocyte sedimentation rate\u003c/p\u003e \u003cp\u003eIQR Inter quartile range\u003c/p\u003e \u003cp\u003eLDH Lactate Dehydrogenase\u003c/p\u003e \u003cp\u003ePCT Procalcitonin\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethics committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University, China (No.XJTU1AF-CRF-2018-025).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBZ, XM and YW collected the clinical and laboratory data. JS processed statistical analysis. JS and BZ drafted the manuscript. BZ, XM and YW revised the final manuscript. BZ, XM and YW is responsible for all clinical and laboratory data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all patients involved in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X and Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. \u003cem\u003eJAMA\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eWu F, Zhao S, Yu B, Chen YM, Wang W, Song ZG, Hu Y, Tao ZW, Tian JH, Pei YY, Yuan ML, Zhang YL, Dai FH, Liu Y, Wang QM, Zheng JJ, Xu L, Holmes EC and Zhang YZ. A new coronavirus associated with human respiratory disease in China. \u003cem\u003eNature\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eSpecial Expert Group for Control of the Epidemic of Novel Coronavirus Pneumonia of the Chinese Preventive Medicine A. [An update on the epidemiological characteristics of novel coronavirus pneumoniaCOVID-19]. \u003cem\u003eZhonghua Liu Xing Bing Xue Za Zhi\u003c/em\u003e. 2020;41:139-144.\u003c/li\u003e\n\u003cli\u003eChen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J, Yu T, Zhang X and Zhang L. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. \u003cem\u003eLancet\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eLi Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, Ren R, Leung KSM, Lau EHY, Wong JY, Xing X, Xiang N, Wu Y, Li C, Chen Q, Li D, Liu T, Zhao J, Li M, Tu W, Chen C, Jin L, Yang R, Wang Q, Zhou S, Wang R, Liu H, Luo Y, Liu Y, Shao G, Li H, Tao Z, Yang Y, Deng Z, Liu B, Ma Z, Zhang Y, Shi G, Lam TTY, Wu JTK, Gao GF, Cowling BJ, Yang B, Leung GM and Feng Z. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eNational Health Commission of China. New coronavirus pneumonia prevention and control program (4th edn). Jan 22, 2020. \u003ca href=\"http://www.gov.cn/zhengce/zhengceku/2020-01/28/5472673/files/0f96c10cc09d4d36a6f9a9f0b42d972b.pdf\"\u003ehttp://www.gov.cn/zhengce/zhengceku/2020-01/28/5472673/files/0f96c10cc09d4d36a6f9a9f0b42d972b.pdf\u003c/a\u003e (in Chinese).\u003c/li\u003e\n\u003cli\u003eNational Health Commission of the People\u0026rsquo;s Republic of China. \u003ca href=\"http://www.nhc.gov.cn\"\u003ehttp://www.nhc.gov.cn\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003eLiu Y, Gayle AA, Wilder-Smith A and Rocklov J. The reproductive number of COVID-19 is higher compared to SARS coronavirus. \u003cem\u003eJ Travel Med\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eThompson RN. Novel Coronavirus Outbreak in Wuhan, China, 2020: Intense Surveillance Is Vital for Preventing Sustained Transmission in New Locations. \u003cem\u003eJ Clin Med\u003c/em\u003e. 2020;9.\u003c/li\u003e\n\u003cli\u003eDu Z, Wang L, Cauchemez S, Xu X, Wang X, Cowling BJ and Meyers LA. Risk for Transportation of 2019 Novel Coronavirus Disease from Wuhan to Other Cities in China. \u003cem\u003eEmerg Infect Dis\u003c/em\u003e. 2020;26.\u003c/li\u003e\n\u003cli\u003eBacker JA, Klinkenberg D and Wallinga J. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. \u003cem\u003eEuro Surveill\u003c/em\u003e. 2020;25.\u003c/li\u003e\n\u003cli\u003eLiao X, Wang B and Kang Y. Novel coronavirus infection during the 2019-2020 epidemic: preparing intensive care units-the experience in Sichuan Province, China. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eEurosurveillance Editorial T. Note from the editors: World Health Organization declares novel coronavirus (2019-nCoV) sixth public health emergency of international concern. \u003cem\u003eEuro Surveill\u003c/em\u003e. 2020;25.\u003c/li\u003e\n\u003cli\u003eRodriguez-Morales AJC-O, J.A.; Guti\u0026eacute;rrez-Ocampo, E.; Villamizar-Pe\u0026ntilde;a, R.; Holguin-Rivera, Y.; Escalera-Antezana, J.P.; Alvarado-Arnez, L.E.; Bonilla-Aldana, D.K.; Franco-Paredes, C.; Henao-Martinez, A.F.; Paniz-Mondolfi, A.; Lagos-Grisales, G.J.; Ram\u0026iacute;rez-Vallejo, E.; Su\u0026aacute;rez, J.A.; Zambrano, L.I.; Villamil-G\u0026oacute;mez, W.E.; Balbin-Ramon, G.J.; Rabaan, A.A.; Harapan, H.; Dhama, K.; Nishiura, H.; Kataoka, H.; Ahmad, T.; Sah, R. . Clinical, Laboratory and Imaging Features of COVID-19: A Systematic Review and Meta-analysis. Preprints 2020, 2020020378 (doi: 10.20944/preprints202002.0378.v3). .\u003c/li\u003e\n\u003cli\u003eCorman VM, Landt O, Kaiser M, Molenkamp R, Meijer A, Chu DK, Bleicker T, Brunink S, Schneider J, Schmidt ML, Mulders DG, Haagmans BL, van der Veer B, van den Brink S, Wijsman L, Goderski G, Romette JL, Ellis J, Zambon M, Peiris M, Goossens H, Reusken C, Koopmans MP and Drosten C. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. \u003cem\u003eEuro Surveill\u003c/em\u003e. 2020;25.\u003c/li\u003e\n\u003cli\u003eLalueza A, Ayuso B, Arrieta E, Trujillo H, Folgueira D, Cueto C, Serrano A, Laureiro J, Arevalo-Canas C, Castillo C, Diaz-Pedroche C, Lumbreras C and group I. Elevation of serum ferritin levels for predicting a poor outcome in hospitalized patients with influenza infection. \u003cem\u003eClin Microbiol Infect\u003c/em\u003e. 2020.\u003c/li\u003e\n\u003cli\u003eSlaats J, Ten Oever J, van de Veerdonk FL and Netea MG. IL-1beta/IL-6/CRP and IL-18/ferritin: Distinct Inflammatory Programs in Infections. \u003cem\u003ePLoS Pathog\u003c/em\u003e. 2016;12:e1005973.\u003c/li\u003e\n\u003cli\u003eKernan KF and Carcillo JA. Hyperferritinemia and inflammation. \u003cem\u003eInt Immunol\u003c/em\u003e. 2017;29:401-409.\u003c/li\u003e\n\u003cli\u003eSenjo H, Higuchi T, Okada S and Takahashi O. Hyperferritinemia: causes and significance in a general hospital. \u003cem\u003eHematology\u003c/em\u003e. 2018;23:817-822.\u003c/li\u003e\n\u003cli\u003eSanaei Dashti A, Alizadeh S, Karimi A, Khalifeh M and Shoja SA. Diagnostic value of lactate, procalcitonin, ferritin, serum-C-reactive protein, and other biomarkers in bacterial and viral meningitis: A cross-sectional study. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e. 2017;96:e7637.\u003c/li\u003e\n\u003cli\u003eKawamata R, Yokoyama K, Sato M, Goto M, Nozaki Y, Takagi T, Kumagai H and Yamagata T. Utility of serum ferritin and lactate dehydrogenase as surrogate markers for steroid therapy for Mycoplasma pneumoniae pneumonia. \u003cem\u003eJ Infect Chemother\u003c/em\u003e. 2015;21:783-9.\u003c/li\u003e\n\u003cli\u003eChoi YJ, Jeon JH and Oh JW. Critical combination of initial markers for predicting refractory Mycoplasma pneumoniae pneumonia in children: a case control study. \u003cem\u003eRespir Res\u003c/em\u003e. 2019;20:193.\u003c/li\u003e\n\u003cli\u003eMemar MY, Varshochi M, Shokouhi B, Asgharzadeh M and Kafil HS. Procalcitonin: The marker of pediatric bacterial infection. \u003cem\u003eBiomed Pharmacother\u003c/em\u003e. 2017;96:936-943.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Biomarkers, C-reactive protein, Ferritin, Procalcitonin","lastPublishedDoi":"10.21203/rs.3.rs-18079/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-18079/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjectives \u003c/p\u003e\u003cp\u003eIt is of clinical significance to evaluate the disease severity and investigate possible biomarkers of 2019 Novel coronavirus disease (COVID-19). In this study, we aim to describe the clinical characteristics of infection makers in severe and very severe patients with COVID-19.\u0026nbsp;\u003c/p\u003e\u003cp\u003eMethods \u003c/p\u003e\u003cp\u003eThis is a single center, observational analysis. We enrolled 48 in-hospital severe patients with COVID-19 admitted to the West District of Union Hospital of Tongji Medical College and analyzed infection biomarkers in 20 patients who had been tested for ferritin, PCT, CRP, etc.\u0026nbsp;\u003c/p\u003e\u003cp\u003eResults \u003c/p\u003e\u003cp\u003eThe median age was 59yrd (inter quartile range [IQR]:46-61) among severe COVID-19 group and 57yrd (IQR:45-71.5) among very severe group. We noted significantly increased CRP (1.48mg/L [IQR: 16.69-2.74] vs. 57.98mg/L [IQR: 38.335-77.565], P\u0026lt;0.05), PCT(0.05ng/ml [IQR: 0.03-0.06] vs. 0.21ng/ml [IQR: 0.11-0.42], P\u0026lt;0.05) and ferritin (291.13ng/ml [IQR: 102.1-648.42] vs. 1006.16ng/ml [IQR: 408.265-1988.25]). For blood count, significant increase was noticed in neutrophil percentage (67.6% [IQR: 61.8-76.4] vs. 86.7% [IQR: 82-92.35], P\u0026lt;0.01) and neutrophil count (3.75*10^9/L [IQR: 3.42-4.93] vs. 8.11*10^9/L [IQR: 5.675-8.905], P\u0026lt;0.05); and decrease was seen in lymphocyte percentage (22.7% [IQR: 17.4-27.4] vs. 8% [IQR: 4.85-13], P\u0026lt;0.05), lymphocyte count (1.62*10^9/L [IQR: 0.7-1.73] vs. 0.68*10^9/L [IQR: 0.385-1.04], P\u0026lt;0.05), and platelet count (214*10^9/L [IQR: 184-247] vs. 147*10^9/L [IQR: 126-202.5], P\u0026lt;0.05).\u0026nbsp;\u003c/p\u003e\u003cp\u003eConclusions \u003c/p\u003e\u003cp\u003eThe serum levels of CRP, PCT and ferritin are markedly increased in very severe compared with severe COVID-19. Increased CRP, PCT and ferritin level might correlate to secondary bacterial infection and associated with poor clinical prognosis.\u003c/p\u003e","manuscriptTitle":"Utility of Ferritin, Procalcitonin, and C-reactive Protein in Severe Patients with 2019 Novel Coronavirus Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-03-19 21:21:19","doi":"10.21203/rs.3.rs-18079/v1","editorialEvents":[{"type":"communityComments","content":2}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e1f42142-7e86-4d99-a1d3-2f869e755246","owner":[],"postedDate":"March 19th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":72599,"name":"Pulmonology"},{"id":72600,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2020-03-19 21:21:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-18079","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-18079","identity":"rs-18079","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}