Serum Mycoplasma Pneumoniae IgG in COVID-19: A Protective Factor

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Panayi, Yuan Xiong, Guohui Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-27778/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 A correlation between prior exposure to Mycoplasma pneumoniae (IgG positive) and better clinical response to COVID-19 was elusive. In the present study, a retrospective review of 133 COVID-19 infected patients treated at Wuhan Union Hospital from Feb 1 to Mar 20 was carried out. Our data showed that COVID-19 infected patients with mycoplasma lgG positivity had a higher lymphocyte count and percentage (p = 0.026, p = 0.017), monocyte count and percentage (p = 0.028, p = 0.006) and eosinophil count and percentage (p = 0.039, p = 0.007), and a lower neutrophil count and percentage (p = 0.044, p = 0.006) than COVID-19 infected patients without mycoplasma lgG. Furthermore, requirement and use of a nasal catheter or oxygen mask was significantly lower in COVID-19 infected patients with mycoplasma lgG positivity (p = 0.029). Our findings indicate that mycoplasma IgG positivity is a potential protective factor for COVID-19. Infectious Diseases COVID-19 IgG Protective Mycoplasma Introduction Ever since its initial outbreak in Wuhan, Hubei province, China, in December 2019, the 2019 novel coronavirus disease (COVID-19) has quickly spread around the world. Currently, more than 1.3 million cases have been confirmed, with 76,420 deaths worldwide. 1 The clinical characteristics of patients with COVID-19 have been well described with some risk factors shown to increase the mortality of COVID-19 identified, including diabetes, cancer and aging. 2 , 3 Protective factors that may help patients with COVID-19 show fewer severe symptoms and better recovery remain elusive. As frontline medical personnel in the Wuhan Union Hospital—one of the biggest COVID-19 designated institutions in Wuhan—we have unique first-hand experience in dealing with this pandemic. Here, we report a correlation between prior exposure to Mycoplasma pneumoniae (IgG positivity) and better clinical response to COVID-19. This association has, to the best of our knowledge, not been previously shown. Methods A retrospective review of COVID-19 infected patients treated at Wuhan Union Hospital from Feb 1 to Mar 20 was carried out. COVID-19 was diagnosed in accordance with the New Coronavirus Pneumonia Prevention and Control Program, 7th edition, published by the National Health Commission of China. This retrospective study was approved by The Institutional Review Board at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Statistical analysis Clinical symptoms, medical records as well as laboratory tests were reviewed. Continuous variables were described as mean, median, and interquartile range (IQR), while categorical variables were compared by X 2 test or Fisher’s exact test between COVID-19 infected patients with mycoplasma lgG (-) and mycoplasma lgG (+). Data were expressed using frequency rates and percentages. The Kolmogorov-Smirnov test was used to establish whether continuous variables were normally distributed. Then independent group t test was used if normally distributed, otherwise, the Mann-Whitney test was used. A two-sided α of less than 0.05 was considered statistically significant. SPSS version 23.0 was used for all statistical analyses. Results A total of 133 patients with COVID-19 were identified, of which 38 displayed Mycoplasma IgG positivity. Comparison of COVID-19 patients with mycoplasma lgG positivity against those without mycoplasma IgG, showed no differences in the demographics (age, p = .105; female sex, p = .375) or common signs and symptoms of the patients (fever, p = 0.23; cough, p = 0.53; fatigue, p = 1.000; dyspnea, p = 0.67; diarrhea, p = 0.39; Table 1 ). Statistically significant differences were, however, shown in terms of laboratory test results. COVID-19 infected patients with mycoplasma lgG positivity had a higher lymphocyte count and percentage (p = 0.026, p = 0.017), monocyte count and percentage (p = 0.028, p = 0.006) and eosinophil count and percentage (p = 0.039, p = 0.007), and a lower neutrophil count and percentage (p = 0.044, p = 0.006) than COVID-19 infected patients without mycoplasma lgG. Other routine blood tests, including coagulation tests, blood biochemistry and infection-related biomarkers did not significantly differ except for thrombin time (p = 0.001) and lactate dehydrogenase (p = 0.008). Furthermore, requirement and use of a nasal catheter or oxygen mask was significantly lower in COVID-19 infected patients with mycoplasma lgG positivity (p = 0.029), suggesting a better prognosis. The rate of noninvasive ventilation and mortality did not differ; this may be due to lack of relevant clinical cases. Table 1 Demographic characteristics, laboratory findings, treatment and outcomes of COVID-19 infected patients categorized by mycoplasma lgG antibody presence. Mycoplasma lgG (-) (n = 95) Mycoplasma lgG (+) (n = 38) P value Demographics Age, y 66.0 (56.0–70.0) 61.0 (43.5–70.0) 0.105 Female sex 43 (45.3%) 14 (36.8%) 0.375 Signs and symptoms Fever 80 (84.2%) 35 (92.1%) 0.229 Cough 70 (73.7%) 30 (78.9%) 0.526 Fatigue 60 (63.2%) 24 (63.2%) 1.000 Dyspnea 18 (18.9%) 6 (15.8%) 0.669 Diarrhea 12 (12.6%) 7 (18.4%) 0.389 Laboratory test results White blood cell count, x10 9 /L 5.84 (4.38–7.58) 5.61 (3.73–7.07) 0.191 Hemoglobin, g/L 128.00 (116.00-135.00) 123.00 (113.50-134.25) 0.417 Neutrophils, % 73.40 ± 14.17 66.05 ± 12.28 0.006* Lymphocytes, % 16.50 (9.20-26.35) 21.55 (16.10–30.80) 0.017* Monocytes, % 6.83 ± 3.26 8.59 ± 3.40 0.006* Eosinophils, % 0.30 (0.10-1.00) 1.04 (0.20–1.68) 0.007* Neutrophil count, x10 9 /L 3.95 (2.92–6.47) 3.23 (2.40–4.95) 0.044* Lymphocyte count, x10 9 /L 0.86 (0.57–1.29) 1.09 (0.73–1.55) 0.026* Monocyte count, x10 9 /L 0.33 (0.25–0.55) 0.53 (0.30–0.64) 0.028* Eosinophils count, x10 9 /L 0.02 (0.00-0.075) 0.05 (0.30–0.64) 0.039* D-dimer, mg/L 0.67 (0.30–2.41) 0.58 (0.32–1.41) 0.279 PT, s 13.40 (12.70–14.20) 12.95 (12.50-13.63) 0.069 APPT, s 37.90 (34.20–42.60) 35.7 (33.25–40.55) 0.104 TT, s 16.03 ± 1.32 16.96 ± 1.52 0.001* K, mmol/L 3.83 ± 0.56 3.81 ± 0.53 0.824 Na, mmol/L 138.30 (135.75–140.40) 138.60 (135.35-142.25) 0.430 ALT, U/L 33.00 (19.50–55.50) 31.00 (20.00-46.25) 0.784 AST, U/L 36.00 (24.00-53.50) 29.00 (20.75–39.50) 0.053 LDH, U/L 299.00 (215.00-402.25) 236.00 (192.25-303.75) 0.008* Total bilirubin, µmol/L 12.10 (8.65–15.80) 10.90 (9.88–15.83) 0.945 Direct Bilirubin, µmol/L 3.80 (2.75–5.50) 3.90 (2.78–5.25) 0.743 Indirect Bilirubin, µmol/L 7.70 (5.50–9.80) 7.40 (6.00-10.50) 0.757 Total Protein, g/L 62.79 ± 5.62 63.18 ± 7.58 0.748 Creatinine, µmol/L 73.10 (58.25–89.45) 70.00 (62.50-81.83) 0.632 Blood Urea Nitrogen, mmol/L 4.41 (3.71–5.96) 4.23 (3.50–5.04) 0.181 Ferritin, ng/ml 644.99 (334.94-1318.25) 307.16 (202.51-706.99) 0.136 Treatment and outcomes Nasal catheter or oxygen mask 62 (65.3%) 17 (44.7%) 0.029* NIV 6 (6.3%) 1 (2.6%) 0.667 Death 5 (5.3%) 1 (2.6%) 0.843 NIV = noninvasive ventilation; Data are presented as n/N (%) or median (IQR). P values were calculated using independent group t test, X 2 test, Fisher’s exact test or Mann-Whitney U test. *p < 0.05. Normal ranges for the laboratory values are as follows: white blood-cell count, 3.5–9.5 × 10 9 /L; hemoglobin, 130–175 g/L; neutrophil %, 40–75; lymphocyte %, 20–50; monocyte %, 3–10; eosinophils %, 0.4-8; neutrophil count, 1.8–6.3 × 10 9 /L; lymphocyte count, 1.1–3.2 × 10 9 /L; monocyte count, 0.1–0.6 × 10 9 /L; eosinophils count, 0.02–0.52 × 10 9 /L; D-dimer, < 0.5 ug/ml; PT, 11.0–16.0 s; APTT, 27.0–45.0 s; TT, 14.0–20.0 s; K, 3.5–5.3 mmol/L; Na, 137–147 mmol/L; alanine aminotransferase (ALT), 5–40 U/L; aspartate aminotransferase (AST), 8–40 U/L; lactate dehydrogenase (LDH), 109–245 U/L; total bilirubin, 3.0–20.0 µmol/L; direct bilirubin, 1.7–6.8 µmol/L; Total Protein, 60–83 g/L; creatinine, 57.0-111.0 µmol/L; Blood Urea Nitrogen, 2.9–8.2 mmol/L; ferritin, 21.81-274.66 ng/ml. Discussion Patients with prior exposure to Mycoplasma pneumoniae (IgG positive) showed stronger resistance and better recovery from the SARS-CoV-2 viral infection than patients without exposure. Of particular note, the immune response rendered against the virus was noted to be stronger in the IgG positive group, evident through an overall higher leukocyte count. This can partially be explained by reprogrammed immune cells. 4 Prior evidence has supported that when the lungs recover from infection they develop new alveolar macrophage biology, which can protect the lungs of adults against pneumonia. 5 Our retrospective patient review highlighted a similar phenomenon: COVID-19 patients with IgG positivity displayed milder symptoms and rarely experienced severe disease (OR, 2.31; 95% CI, 1.89–3.02). To eliminate the interference of age, we compared the outcomes of elder patients (> 60 years) and younger patients (< 30 years) with IgG positivity and found them to be similar (OR, 2.31; 95% CI, 1.89–3.02). Thus, our findings indicate that mycoplasma IgG positivity is a potential protective factor for SARS-CoV-2 infection. Although these promising observations require further investigation, our study demonstrate that previous Mycoplasma pneumoniae infection is an important part of a patient’s medical history as patients without prior infection are more vulnerable to COVID-19. Declarations Funding: This study was supported by the National Science Foundation of China (grant No. 81772345), National Key Research & Development Program of China (grants Nos. 2018YF2001502 and 2018YFB1105705), Wuhan Science and Technology Bureau (grant No. 2017060201010192), the National Health Commission of the People’s Republic of China (grants Nos. ZX-01-018 and ZX-01-C2016153), and the Health Commission of Hubei Province (grant No. WJ2019Z009). Conflict of Interest Disclosures: None reported. References The Center for Systems Science and Engineering at Johns Hopkins University. https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6 . Retrieved 04.07.2020. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507–13. Liang W, Guan W, Chen R, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol. 2020;21(3):335–7. Jokinen C, Heiskanen L, Juvonen H, et al. Microbial etiology of community-acquired pneumonia in the adult population of 4 municipalities in eastern Finland. Clin Infect Dis. 2001;32(8):1141–54. Bhagwat SP, Gigliotti F, Wang J, et al. Intrinsic Programming of Alveolar Macrophages for Protective Antifungal Innate Immunity Against Pneumocystis Infection. Front Immunol. 2018;9:2131. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-27778","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":585618,"identity":"544e43dc-2bc4-4a38-b068-7cd4bf7c2d73","order_by":1,"name":"Bobin Mi","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bobin","middleName":"","lastName":"Mi","suffix":""},{"id":585619,"identity":"8b6e0e26-5e96-4ef9-ad06-153f9e874244","order_by":2,"name":"Lang Chen","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lang","middleName":"","lastName":"Chen","suffix":""},{"id":585620,"identity":"9c239243-46b0-428e-ad3b-43e6babc48f8","order_by":3,"name":"Adriana C. Panayi","email":"","orcid":"","institution":"Brigham and Women's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adriana","middleName":"C.","lastName":"Panayi","suffix":""},{"id":585621,"identity":"9b31ee2a-e4a1-4e2b-9c46-0e73344ce001","order_by":4,"name":"Yuan Xiong","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Xiong","suffix":""},{"id":585622,"identity":"86ac4ace-8fca-4de4-bf73-31ad6394f073","order_by":5,"name":"Guohui Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACPmYwdYCBjb0HKnSAgBY2uBaeM0A6gRgtcJMlcojVws5j/Jqn4k5in+TbY5I/fzDI8d1IYPxcgNdhPGbWPGeeJbZJ56VJ8yQwGEveSGCWnkFAizFv22GglhwzaaDDEjfcSAAKEqVF8oyZ5I8EhnpitBg/BmuR4DGTADoswYCwFrYyxjlnDhu38eQYW/OkSRjOPPOwWRqfFn7+w5s/vKk4LDu//YzhzR82NvJ8x5MPfsanBWSRBBIHxGZswK+BgYH5AyEVo2AUjIJRMMIBAENKQoKNWh5NAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2013-1396","institution":"Wuhan Union Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Guohui","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2020-05-08 08:27:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-27778/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-27778/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13504618,"identity":"142469cc-58ed-4e00-b529-2050d7441914","added_by":"auto","created_at":"2021-09-16 23:24:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":220808,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-27778/v1/cf9623de-fee8-4877-8744-9346666bd633.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eSerum Mycoplasma Pneumoniae IgG in COVID-19: A Protective Factor\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eEver since its initial outbreak in Wuhan, Hubei province, China, in December 2019, the 2019 novel coronavirus disease (COVID-19) has quickly spread around the world. Currently, more than 1.3\u0026nbsp;million cases have been confirmed, with 76,420 deaths worldwide.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The clinical characteristics of patients with COVID-19 have been well described with some risk factors shown to increase the mortality of COVID-19 identified, including diabetes, cancer and aging.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Protective factors that may help patients with COVID-19 show fewer severe symptoms and better recovery remain elusive. As frontline medical personnel in the Wuhan Union Hospital\u0026mdash;one of the biggest COVID-19 designated institutions in Wuhan\u0026mdash;we have unique first-hand experience in dealing with this pandemic.\u003c/p\u003e \u003cp\u003eHere, we report a correlation between prior exposure to \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e (IgG positivity) and better clinical response to COVID-19. This association has, to the best of our knowledge, not been previously shown.\u003c/p\u003e "},{"header":"Methods","content":" \u003cp\u003eA retrospective review of COVID-19 infected patients treated at Wuhan Union Hospital from Feb 1 to Mar 20 was carried out. COVID-19 was diagnosed in accordance with the New Coronavirus Pneumonia Prevention and Control Program, 7th edition, published by the National Health Commission of China. This retrospective study was approved by The Institutional Review Board at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eClinical symptoms, medical records as well as laboratory tests were reviewed. Continuous variables were described as mean, median, and interquartile range (IQR), while categorical variables were compared by X\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e test or Fisher\u0026rsquo;s exact test between COVID-19 infected patients with mycoplasma lgG (-) and mycoplasma lgG (+). Data were expressed using frequency rates and percentages. The Kolmogorov-Smirnov test was used to establish whether continuous variables were normally distributed. Then independent group t test was used if normally distributed, otherwise, the Mann-Whitney test was used. A two-sided α of less than 0.05 was considered statistically significant. SPSS version 23.0 was used for all statistical analyses.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003eA total of 133 patients with COVID-19 were identified, of which 38 displayed Mycoplasma IgG positivity. Comparison of COVID-19 patients with mycoplasma lgG positivity against those without mycoplasma IgG, showed no differences in the demographics (age, p\u0026thinsp;=\u0026thinsp;.105; female sex, p\u0026thinsp;=\u0026thinsp;.375) or common signs and symptoms of the patients (fever, p\u0026thinsp;=\u0026thinsp;0.23; cough, p\u0026thinsp;=\u0026thinsp;0.53; fatigue, p\u0026thinsp;=\u0026thinsp;1.000; dyspnea, p\u0026thinsp;=\u0026thinsp;0.67; diarrhea, p\u0026thinsp;=\u0026thinsp;0.39; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Statistically significant differences were, however, shown in terms of laboratory test results. COVID-19 infected patients with mycoplasma lgG positivity had a higher lymphocyte count and percentage (p\u0026thinsp;=\u0026thinsp;0.026, p\u0026thinsp;=\u0026thinsp;0.017), monocyte count and percentage (p\u0026thinsp;=\u0026thinsp;0.028, p\u0026thinsp;=\u0026thinsp;0.006) and eosinophil count and percentage (p\u0026thinsp;=\u0026thinsp;0.039, p\u0026thinsp;=\u0026thinsp;0.007), and a lower neutrophil count and percentage (p\u0026thinsp;=\u0026thinsp;0.044, p\u0026thinsp;=\u0026thinsp;0.006) than COVID-19 infected patients without mycoplasma lgG. Other routine blood tests, including coagulation tests, blood biochemistry and infection-related biomarkers did not significantly differ except for thrombin time (p\u0026thinsp;=\u0026thinsp;0.001) and lactate dehydrogenase (p\u0026thinsp;=\u0026thinsp;0.008). Furthermore, requirement and use of a nasal catheter or oxygen mask was significantly lower in COVID-19 infected patients with mycoplasma lgG positivity (p\u0026thinsp;=\u0026thinsp;0.029), suggesting a better prognosis. The rate of noninvasive ventilation and mortality did not differ; this may be due to lack of relevant clinical cases.\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 \u003cp\u003eDemographic characteristics, laboratory findings, treatment and outcomes of COVID-19 infected patients categorized by mycoplasma lgG antibody presence.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMycoplasma lgG (-)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMycoplasma lgG (+)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.0 (56.0\u0026ndash;70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.0 (43.5\u0026ndash;70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (45.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSigns and symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (84.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (73.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (78.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (18.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiarrhea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory test results\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell count, x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.84 (4.38\u0026ndash;7.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.61 (3.73\u0026ndash;7.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin, g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128.00 (116.00-135.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.00 (113.50-134.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.40\u0026thinsp;\u0026plusmn;\u0026thinsp;14.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.05\u0026thinsp;\u0026plusmn;\u0026thinsp;12.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.50 (9.20-26.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.55 (16.10\u0026ndash;30.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.017*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocytes, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophils, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30 (0.10-1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.20\u0026ndash;1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil count, x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.95 (2.92\u0026ndash;6.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.23 (2.40\u0026ndash;4.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.044*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte count, x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86 (0.57\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09 (0.73\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.026*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte count, x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33 (0.25\u0026ndash;0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53 (0.30\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophils count, x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02 (0.00-0.075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05 (0.30\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.039*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer, mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67 (0.30\u0026ndash;2.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58 (0.32\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.40 (12.70\u0026ndash;14.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.95 (12.50-13.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPPT, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.90 (34.20\u0026ndash;42.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.7 (33.25\u0026ndash;40.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNa, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138.30 (135.75\u0026ndash;140.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.60 (135.35-142.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.00 (19.50\u0026ndash;55.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.00 (20.00-46.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.00 (24.00-53.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.00 (20.75\u0026ndash;39.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299.00 (215.00-402.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e236.00 (192.25-303.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.10 (8.65\u0026ndash;15.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.90 (9.88\u0026ndash;15.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect Bilirubin, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.80 (2.75\u0026ndash;5.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.90 (2.78\u0026ndash;5.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect Bilirubin, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.70 (5.50\u0026ndash;9.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.40 (6.00-10.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Protein, g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.79\u0026thinsp;\u0026plusmn;\u0026thinsp;5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.18\u0026thinsp;\u0026plusmn;\u0026thinsp;7.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.10 (58.25\u0026ndash;89.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.00 (62.50-81.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Urea Nitrogen, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.41 (3.71\u0026ndash;5.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.23 (3.50\u0026ndash;5.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerritin, ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e644.99 (334.94-1318.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e307.16 (202.51-706.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTreatment and outcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNasal catheter or oxygen mask\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (65.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (44.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNIV\u0026thinsp;=\u0026thinsp;noninvasive ventilation; Data are presented as n/N (%) or median (IQR). P values were calculated using independent group t test, X\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e test, Fisher\u0026rsquo;s exact test or Mann-Whitney U test. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNormal ranges for the laboratory values are as follows: white blood-cell count, 3.5\u0026ndash;9.5\u0026thinsp;\u0026times;\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e/L; hemoglobin, 130\u0026ndash;175\u0026nbsp;g/L; neutrophil %, 40\u0026ndash;75; lymphocyte %, 20\u0026ndash;50; monocyte %, 3\u0026ndash;10; eosinophils %, 0.4-8; neutrophil count, 1.8\u0026ndash;6.3\u0026thinsp;\u0026times;\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e/L; lymphocyte count, 1.1\u0026ndash;3.2\u0026thinsp;\u0026times;\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e/L; monocyte count, 0.1\u0026ndash;0.6\u0026thinsp;\u0026times;\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e/L; eosinophils count, 0.02\u0026ndash;0.52\u0026thinsp;\u0026times;\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e/L; D-dimer, \u0026lt;\u0026thinsp;0.5 ug/ml; PT, 11.0\u0026ndash;16.0\u0026nbsp;s; APTT, 27.0\u0026ndash;45.0\u0026nbsp;s; TT, 14.0\u0026ndash;20.0\u0026nbsp;s; K, 3.5\u0026ndash;5.3\u0026nbsp;mmol/L; Na, 137\u0026ndash;147\u0026nbsp;mmol/L; alanine aminotransferase (ALT), 5\u0026ndash;40\u0026nbsp;U/L; aspartate aminotransferase (AST), 8\u0026ndash;40\u0026nbsp;U/L; lactate dehydrogenase (LDH), 109\u0026ndash;245\u0026nbsp;U/L; total bilirubin, 3.0\u0026ndash;20.0\u0026nbsp;\u0026micro;mol/L; direct bilirubin, 1.7\u0026ndash;6.8\u0026nbsp;\u0026micro;mol/L; Total Protein, 60\u0026ndash;83\u0026nbsp;g/L; creatinine, 57.0-111.0\u0026nbsp;\u0026micro;mol/L; Blood Urea Nitrogen, 2.9\u0026ndash;8.2\u0026nbsp;mmol/L; ferritin, 21.81-274.66\u0026nbsp;ng/ml.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003ePatients with prior exposure to \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e (IgG positive) showed stronger resistance and better recovery from the SARS-CoV-2 viral infection than patients without exposure. Of particular note, the immune response rendered against the virus was noted to be stronger in the IgG positive group, evident through an overall higher leukocyte count. This can partially be explained by reprogrammed immune cells.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Prior evidence has supported that when the lungs recover from infection they develop new alveolar macrophage biology, which can protect the lungs of adults against pneumonia.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Our retrospective patient review highlighted a similar phenomenon: COVID-19 patients with IgG positivity displayed milder symptoms and rarely experienced severe disease (OR, 2.31; 95% CI, 1.89\u0026ndash;3.02). To eliminate the interference of age, we compared the outcomes of elder patients (\u0026gt;\u0026thinsp;60\u0026nbsp;years) and younger patients (\u0026lt;\u0026thinsp;30\u0026nbsp;years) with IgG positivity and found them to be similar (OR, 2.31; 95% CI, 1.89\u0026ndash;3.02). Thus, our findings indicate that mycoplasma IgG positivity is a potential protective factor for SARS-CoV-2 infection.\u003c/p\u003e \u003cp\u003eAlthough these promising observations require further investigation, our study demonstrate that previous \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e infection is an important part of a patient\u0026rsquo;s medical history as patients without prior infection are more vulnerable to COVID-19.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003eThis study was supported by the National Science Foundation of China (grant No. 81772345), National Key Research \u0026amp; Development Program of China (grants Nos. 2018YF2001502 and 2018YFB1105705), Wuhan Science and Technology Bureau (grant No. 2017060201010192), the National Health Commission of the People\u0026rsquo;s Republic of China (grants Nos. ZX-01-018 and ZX-01-C2016153), and the Health Commission of Hubei Province (grant No. WJ2019Z009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosures:\u003c/strong\u003e None reported.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003eThe Center for Systems Science and Engineering at Johns Hopkins University. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6\u003c/span\u003e\u003c/span\u003e. Retrieved 04.07.2020.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507\u0026ndash;13.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLiang W, Guan W, Chen R, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol. 2020;21(3):335\u0026ndash;7.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eJokinen C, Heiskanen L, Juvonen H, et al. Microbial etiology of community-acquired pneumonia in the adult population of 4 municipalities in eastern Finland. Clin Infect Dis. 2001;32(8):1141\u0026ndash;54.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBhagwat SP, Gigliotti F, Wang J, et al. Intrinsic Programming of Alveolar Macrophages for Protective Antifungal Innate Immunity Against Pneumocystis Infection. Front Immunol. 2018;9:2131.\u003c/span\u003e \u003c/li\u003e\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, IgG, Protective, Mycoplasma","lastPublishedDoi":"10.21203/rs.3.rs-27778/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-27778/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA correlation between prior exposure to Mycoplasma pneumoniae (IgG positive) and better clinical response to COVID-19 was elusive. In the present study, a retrospective review of 133 COVID-19 infected patients treated at Wuhan Union Hospital from Feb 1 to Mar 20 was carried out. Our data showed that COVID-19 infected patients with mycoplasma lgG positivity had a higher lymphocyte count and percentage (p\u0026thinsp;=\u0026thinsp;0.026, p\u0026thinsp;=\u0026thinsp;0.017), monocyte count and percentage (p\u0026thinsp;=\u0026thinsp;0.028, p\u0026thinsp;=\u0026thinsp;0.006) and eosinophil count and percentage (p\u0026thinsp;=\u0026thinsp;0.039, p\u0026thinsp;=\u0026thinsp;0.007), and a lower neutrophil count and percentage (p\u0026thinsp;=\u0026thinsp;0.044, p\u0026thinsp;=\u0026thinsp;0.006) than COVID-19 infected patients without mycoplasma lgG. Furthermore, requirement and use of a nasal catheter or oxygen mask was significantly lower in COVID-19 infected patients with mycoplasma lgG positivity (p\u0026thinsp;=\u0026thinsp;0.029). Our findings indicate that mycoplasma IgG positivity is a potential protective factor for COVID-19.\u003c/p\u003e","manuscriptTitle":"Serum Mycoplasma Pneumoniae IgG in COVID-19: A Protective Factor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-05-20 17:52:35","doi":"10.21203/rs.3.rs-27778/v1","editorialEvents":[{"type":"communityComments","content":0}],"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":"7f0051d6-979a-45d7-b0c6-ff15fbdc3c29","owner":[],"postedDate":"May 20th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":103602,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2020-07-11T17:27:42+00:00","versionOfRecord":[],"versionCreatedAt":"2020-05-20 17:52:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-27778","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-27778","identity":"rs-27778","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}