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MeSH Disease

Pneumonia (98)

COVID-19 (97)

Fever (30)

Death (19)

Lymphopenia (18)


HGNC Genes

SARS-CoV-2 proteins

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    Prognostic factors for COVID-19 MESHD pneumonia progression to severe symptom based on the earlier clinical features: a retrospective analysis

    Authors: Huang Huang; Shuijiang Cai; Yueping Li; Youxia Li; Yinqiang Fan; Linghua Li; Chunliang Lei; Xiaoping Tang; Fengyu Hu; Feng Li; Xilong Deng

    doi:10.1101/2020.03.28.20045989 Date: 2020-03-30 Source: medRxiv

    Background Approximately 15-20% of COVID-19 MESHD patients will develop severe pneumonia MESHD, about 10 % of which will die if not properly managed. Methods 125 COVID-19 MESHD patients enrolled in this study were classified into mild (93 cases) and severe (32 cases) groups, basing on their 3 to 7-days clinical outcomes. Patients' gender, age, comorbid with underlying diseases, epidemiological history, clinical manifestations, and laboratory tests on admission were collected and subsequently analyzed with single-factor and multivariate logistic regression methods. Finally, we evaluate their prognostic values with the receiver operating characteristic curve (ROC) analysis. Results Seventeen factors on admission differed significantly between mild and severe groups. Next, only four factors, including the comorbid with underlying diseases, increased respiratory rate (>24/min), elevated C-reactive protein HGNC (CRP >10mg/liter), and lactate dehydrogenase (LDH >250U/liter), were found to be independently associated with the later disease development. Prognostic value analysis by ROC indicated that individual factors could not confidently predict the occurrence of severe pneumonia MESHD, but that the combination of fast respiratory rate and elevated LDH significantly increase the predictive confidence (AUC= 0.944, sensitivity= 0.941, and specificity= 0.902). Three- or four-factors combinations, including elevated LDH and fast respiratory rate, further increased the prognostic value. Additionally, measurable serum viral RNA post-admission could independently predict the severe illness occurrence. Conclusions General clinical characteristics and laboratory tests, such as combinations consisting of elevated LDH and fast respiratory rate, and detectable viral RNA in serum post-admission could provide high confident prognostic value for identifying potential severe COVID-19 MESHD pneumonia MESHD patients.

    A New Predictor of Disease Severity in Patients with COVID-19 MESHD in Wuhan, China

    Authors: Ying Zhou; Zhen Yang; Yanan Guo; Shuang Geng; Shan Gao; Shenglan Ye; Yi Hu; Yafei Wang

    doi:10.1101/2020.03.24.20042119 Date: 2020-03-27 Source: medRxiv

    Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke MESHD out in Wuhan, Hubei, China. This study sought to elucidate a novel predictor of disease severity in patients with coronavirus disease-19 MESHD ( COVID-19 MESHD) cased by SARS-CoV-2. Methods: Patients enrolled in this study were all hospitalized with COVID-19 MESHD in the Central Hospital of Wuhan, China. Clinical features, chronic comorbidities, demographic data, and laboratory and radiological data were reviewed. The outcomes of patients with severe pneumonia MESHD and those with non-severe pneumonia MESHD were compared using the Statistical Package for the Social Sciences (IBM Corp., Armonk, NY, USA) to explore clinical characteristics and risk factors. The receiver operating characteristic curve was used to screen optimal predictors from the risk factors and the predictive power was verified by internal validation. Results: A total of 377 patients diagnosed with COVID-19 MESHD were enrolled in this study, including 117 with severe pneumonia MESHD and 260 with non-severe pneumonia MESHD. The independent risk factors for severe pneumonia MESHD were age [odds ratio (OR): 1.059, 95% confidence interval (CI): 1.036-1.082; p < 0.001], N/L (OR: 1.322, 95% CI: 1.180-1.481; p < 0.001), CRP HGNC (OR: 1.231, 95% CI: 1.129-1.341; p = 0.002), and D-dimer (OR: 1.059, 95% CI: 1.013-1.107; p = 0.011). We identified a product of N/L* CRP HGNC*D-dimer as having an important predictive value for the severity of COVID-19 MESHD. The cutoff value was 5.32. The negative predictive value of less than 5.32 for the N/L* CRP HGNC*D-dimer was 93.75%, while the positive predictive value was 46.03% in the test sets. The sensitivity and specificity were 89.47% and 67.42%. In the training sets, the negative and positive predictive values were 93.80% and 41.32%, respectively, with a specificity of 70.76% and a sensitivity of 89.87%. Conclusions: A product of N/L* CRP HGNC*D-dimer may be an important predictor of disease severity in patients with COVID-19 MESHD.

    Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 MESHD infection

    Authors: Laure Wynants; Ben Van Calster; Marc MJ Bonten; Gary S Collins; Thomas PA Debray; Maarten De Vos; Maria C Haller; Georg Heinze; Karel GM Moons; Richard D Riley; Ewoud Schuit; Luc Smits; Kym IE Snell; Ewout W Steyerberg; Christine Wallisch; Maarten van Smeden

    doi:10.1101/2020.03.24.20041020 Date: 2020-03-27 Source: medRxiv

    Objective To review and critically appraise published and preprint reports of models that aim to predict either (i) presence of existing COVID-19 MESHD infection, (ii) future complications in individuals already diagnosed with COVID-19 MESHD, or (iii) models to identify individuals at high risk for COVID-19 MESHD in the general population. Design Rapid systematic review and critical appraisal of prediction models for diagnosis or prognosis of COVID-19 MESHD infection. Data sources PubMed, EMBASE via Ovid, Arxiv, medRxiv and bioRxiv until 24th March 2020. Study selection Studies that developed or validated a multivariable COVID-19 MESHD related prediction model. Two authors independently screened titles, abstracts and full text. Data extraction Data from included studies were extracted independently by at least two authors based on the CHARMS checklist, and risk of bias was assessed using PROBAST. Data were extracted on various domains including the participants, predictors, outcomes, data analysis, and prediction model performance. Results 2696 titles were screened. Of these, 27 studies describing 31 prediction models were included for data extraction and critical appraisal. We identified three models to predict hospital admission from pneumonia MESHD and other events (as a proxy for covid-19 MESHD pneumonia MESHD) in the general population; 18 diagnostic models to detect COVID-19 MESHD infection in symptomatic individuals (13 of which were machine learning utilising computed tomography (CT) results); and ten prognostic models for predicting mortality risk, progression to a severe state, or length of hospital stay. Only one of these studies used data on COVID-19 MESHD cases outside of China. Most reported predictors of presence of COVID-19 MESHD in suspected patients included age, body temperature, and signs and symptoms. Most reported predictors of severe prognosis in infected MESHD patients included age, sex, features derived from CT, C-reactive protein, lactic dehydrogenase HGNC, and lymphocyte count. Estimated C-index estimates for the prediction models ranged from 0.73 to 0.81 in those for the general population (reported for all 3 general population models), from 0.81 to > 0.99 in those for diagnosis (reported for 13 of the 18 diagnostic models), and from 0.85 to 0.98 in those for prognosis (reported for 6 of the 10 prognostic models). All studies were rated at high risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, and poor statistical analysis, including high risk of model overfitting. Reporting quality varied substantially between studies. A description of the study population and intended use of the models was absent in almost all reports, and calibration of predictions was rarely assessed. Conclusion COVID-19 MESHD related prediction models are quickly entering the academic literature, to support medical decision making at a time where this is urgently needed. Our review indicates proposed models are poorly reported and at high risk of bias. Thus, their reported performance is likely optimistic and using them to support medical decision making is not advised. We call for immediate sharing of the individual participant data from COVID-19 MESHD studies to support collaborative efforts in building more rigorously developed prediction models and validating (evaluating) existing models. The aforementioned predictors identified in multiple included studies could be considered as candidate predictors for new models. We also stress the need to follow methodological guidance when developing and validating prediction models, as unreliable predictions may cause more harm than benefit when used to guide clinical decisions. Finally, studies should adhere to the TRIPOD statement to facilitate validating, appraising, advocating and clinically using the reported models. Systematic review registration protocol: osf.io/ehc47/, registration: osf.io/wy245

    Lactate dehydrogenase, a Risk Factor of Severe COVID-19 MESHD Patients

    Authors: Yi Han; Haidong Zhang; Sucheng Mu; Wei Wei; Chaoyuan Jin; Yuan Xue; Chaoyang Tong; Yunfei Zha; Zhenju Song; Guorong Gu

    doi:10.1101/2020.03.24.20040162 Date: 2020-03-27 Source: medRxiv

    BACKGROUND The World Health Organization (WHO) has recently declared coronavirus disease 2019 MESHD ( COVID-19 MESHD) a public health emergency of global concern. Updated analysis of cases might help identify the characteristic and risk factors of the illness severity. METHODS We extracted data regarding 47 patients with confirmed COVID-19 MESHD from Renmin Hospital of Wuhan University between February 1 and February 18, 2020. The degree of severity of COVID-19 MESHD patients (severe vs. non-severe) was defined at the time of admission according to American Thoracic Society (ATS) guidelines for community-acquired pneumonia MESHD (CAP). RESULTS The median age was 64.91 years, 26 cases (55.31%) were male of which, and 70.83% were severe cases. Severe patients had higher APACHE II (9.92 vs 4.74) and SOFA (3.0 vs 1.0) scores on admission, as well as the higher PSI (86.13 vs 61.39), Curb-65 (1.14 vs 0.48) and CT semiquantitative scores (5.0 vs 2.0) when compared with non-severe patients. Among all univariable parameters, APACHE II, SOFA, lymphocytes, CRP HGNC, LDH, AST HGNC, cTnI HGNC, BNP HGNC, et al were significantly independent risk factors of COVID-19 MESHD severity. Among which, LDH was most positively related both with APACHE II (R = 0.682) and SOFA (R = 0.790) scores, as well as PSI (R = 0.465) and CT (R = 0.837) scores. To assess the diagnostic value of these selected parameters, LDH (0.9727) had maximum sensitivity (100.00%) and specificity (86.67%), with the cutoff value of 283. As a protective factor, lymphocyte counts less than 1.045 x 109 /L showed a good accuracy for identification of severe patients with AUC = 0.9845 (95%CI 0.959-1.01), the maximum specificity (91.30%) and sensitivity (95.24%). In addition, LDH was positively correlated with CRP HGNC, AST HGNC, BNP HGNC and cTnI HGNC, while negatively correlated with lymphocyte cells and its subsets, including CD3+, CD4+ and CD8+ T cells (P < 0.01). CONCLUSIONS This study showed that LDH coule be identified as a powerful predictive factor for early recognition of lung injury MESHD and severe COVID-19 MESHD cases. And importantly, lymphocyte counts, especially CD3+, CD4+, and CD8+ T cells in the peripheral blood of COVID-19 MESHD patients, which was relevant with serum LDH, were also dynamically correlated with the severity of the disease. FUNDING Key Project of Shanghai Municipal Health Bureau (2016ZB0202)

    Core Outcome Set for Traditional Chinese and Western Medicine Clinical Trials of COVID-19 MESHD

    Authors: Ruijin Qiu; Chen Zhao; Tengxiao Liang; Xuezeng Hao; Ya Huang; Xiaoyu Zhang; Zhao Chen; Xuxu Wei; Mengzhu Zhao; Changming Zhong; Jiayuan Hu; Min Li; Songjie Han; Tianmai He; Jing Chen; Hongcai Shang

    doi:10.1101/2020.03.23.20041533 Date: 2020-03-27 Source: medRxiv

    Background: Development of a core outcome set (COS) for clinical trials for COVID-19 MESHD is urgent because of the pandemic wreaking havoc worldwide and the heterogeneity of outcomes in clinical trials. Methods: A preliminary list of outcomes were developed after a systematic review of protocols of clinical trials for COVID-19 MESHD. Then, two rounds of the Delphi survey were conducted. Stakeholders were traditional Chinese medicine (TCM) experts, Western medicine (WM) experts, nurses and the public. Patients with confirmed COVID-19 MESHD were also invited to participate in a questionnaire written in understandable language. Frontline clinicians, as well as nurse, methodologist, evidence based-medicine researcher, and staff from the Chinese Clinical Trials Registry participated by video conference to vote. Results: Ninety-seven eligible study protocols were identified from 160 clinical trials. Seventy-six outcomes were identified from TCM clinical trials and 126 outcomes were identified from WM clinical trials. Finally, 145 outcomes were included in the first round of the Delphi survey. Then, a COS for clinical trials of TCM and WM was developed. The COS include clinical outcomes (recovery/improvement/progression/death), etiology (SARS-CoV-2 nucleic-acid tests, viral load), inflammatory factor ( C-reactive protein HGNC), vital signs (temperature, respiration), blood and lymphatic-system parameters (lymphocytes, virus antibody), respiratory outcomes (Pulmonary imaging, blood oxygen saturation, PaO2/FiO2 ratio, arterial blood gas analysis, mechanical ventilation, oxygen intake, pneumonia MESHD severity index), clinical efficacy (prevalence of preventing patients with mild-to-moderate disease progressing to severe disease), symptoms (clinical symptom score). Outcomes were recommended according to different types of disease. Outcome measurement instrument/definition were also recommended. Conclusion: A COS for COVID-19 MESHD may improve consistency of outcome reporting in clinical trials.

    A Multicentre Study of 2019 Novel Coronavirus Disease MESHD Outcomes of Cancer Patients in Wuhan, China

    Authors: Hong-Yan Zhang; Lin-Wei Wang; Yuan-Yuan Chen; Xiao-Kun Shen; Qun Wang; You-Qin Yan; Yi Yu; Qiuji Wu; Ya-Hua Zhong; Melvin Chua Lee Kiang; Cong-Hua Xie

    doi:10.1101/2020.03.21.20037127 Date: 2020-03-26 Source: medRxiv

    Background: At present, there is a global pandemic of coronavirus disease 2019 MESHD ( COVID-19 MESHD) pneumonia MESHD. Two previous case series from China have suggested that cancer MESHD patients are at a higher risk of COVID-19 MESHD pneumonia MESHD, but the reports were limited by small numbers and few clinical information. Objective: To study clinical characteristics and outcomes of cancer MESHD patients infected with COVID-19 MESHD. Design: Retrospective study. Setting: Four designated COVID-16 hospitals in Wuhan, Hubei province, China. Participants: Medical records of 67 cancer MESHD patients admitted to hospitals between Jan 5, 2020 to Feb 18, 2020 were included. Measurements: Demographic, clinical, laboratory, radiological and treatment data were collected. Survival data of the cohort was cut-off on Mar 10, 2020. Results: Of the 67 patients (median age: 66 years), the median age of patients who had severe illness was older than that of patients who had mild symptoms (P<0.001). Forty-three (64.2%) patients had other concurrent chronic diseases MESHD, and the proportion of severe patients had co-morbidities was higher than patients with mild disease (P=0.004). Twenty-three (34.3%) patients were still at the anticancer treatment phase, but no tumour MESHD progression and recurrence was observed for all the patients during the treatment of COVID-19 MESHD pneumonia MESHD. About 70% of these patients had fever MESHD (n=53, 79.1%) and/or cough (n=50, 74.6%). Lymphocytopenia MESHD was the main laboratory finding accompanying increased C-reactive protein HGNC and procalcitonin in cancer MESHD patients, especially in severe cases. By Mar 10, 2020, 18 (26.9%) patients died from COVID-19 MESHD, and 39 (58.2%) patients have been discharged. The median age of survivors was younger than that of deaths (P=0.014). Lung cancer MESHD (n=15, 22.4%) with COVID-19 MESHD was the most common cancer type and accounted for the highest proportion COVID-19 MESHD resulted deaths (33.3%, 5/15). We observed a tendency that patients at the follow-up phase had a better prognosis than that at anticancer treatment phase (P=0.095). Limitation: This is a retrospective study with only 67 cases from four hospitals. And some specific clinical information was insufficient. Conclusion: This study showed COVID-19 MESHD patients with cancer MESHD seem to have a higher proportion of severe cases and poorer prognosis. The tendency of poor prognosis was more obvious in patients at anticancer treatment phase. We should pay more intensive attentions to cancer MESHD patients infected with COVID-19 MESHD.

    Metabolic disturbances and inflammatory dysfunction predict severity of coronavirus disease 2019 MESHD ( COVID-19 MESHD): a retrospective study

    Authors: Shuke Nie; Xueqing Zhao; Kang Zhao; Zhaohui Zhang; Zhentao Zhang; Zhan Zhang

    doi:10.1101/2020.03.24.20042283 Date: 2020-03-26 Source: medRxiv

    Background: The coronavirus disease 2019 MESHD ( COVID-19 MESHD) is spreading worldwide with 16,558 deaths till date. Serum albumin HGNC, high-density lipoprotein (HDL-C), and C-reactive protein HGNC have been known to be associated with the severity and mortality of community-acquired pneumonia MESHD. However, the characteristics and role of metabolic and inflammatory indicators in COVID-19 MESHD is unclear. Methods: We included 97 hospitalized patients with laboratory-confirmed COVID-19 MESHD. Epidemiological, clinical, and laboratory indices; radiological features; and treatment were analysed. The differences in the clinical and laboratory parameters between mild and severe COVID-19 MESHD patients and the role of these indicators in severity prediction of COVID-19 MESHD were investigated. Results: All were Wuhan residents with contact with confirmed COVID-19 MESHD cases. The median age was 39 years (IQR: 30-59). The most common presenting symptoms were fever MESHD (58.8%), cough (55.7%), and fatigue MESHD (33%). Other features were lymphopenia MESHD, impaired fasting glucose, hypoproteinaemia MESHD, hypoalbuminemia MESHD, low high-density lipoproteinemia MESHD. Decrease in lymphocyte count, serum total protein, serum albumin HGNC, high-density lipoprotein cholesterol (HDL-C), ApoA1 HGNC, CD3+T%, and CD8+T% were found to be valuable in predicting the transition of COVID-19 MESHD from mild to severe illness. Chest computed tomography (CT) images showed that the absorption of bilateral lung lesions synchronized with the recovery of metabolic and inflammatory indicators. Conclusions: Hypoproteinaemia, hypoalbuminemia MESHD, low high-density lipoproteinemia MESHD, and decreased ApoA1 HGNC, CD3+T%, and CD8+T% could predict severity of COVID-19 MESHD. Lymphocyte count, total serum protein, and HDL-C may be potentially useful for the evaluation of COVID-19 MESHD.

    Quantified CT Evaluation in coronavirus disease ( COVID-19 MESHD): A study of 30 Patients in Chongqing, China

    Authors: Wei Zhao; Ji Li; Jia Yang; Sikuan Ye; Ying Xiang; Yixi Bao

    doi:10.21203/rs.3.rs-18932/v1 Date: 2020-03-22 Source: ResearchSquare

    Background Chest computed tomography (CT) provides insight into the progression and prognosis of COVID-19 MESHD pneumonia MESHD. Purpose To quantify the chest CT scans of patients with CODIV-19 pneumonia MESHD using the pulmonary inflammation MESHD index (PII)and associate it with the severity of pneumonia MESHD. Methods A total of thirty inpatients admitted between January 30 and February 29, 2020 with confirmed COVID-19 MESHD infection were enrolled in this retrospective review. Patients were classified as “severe”(those who met the severe pneumonia criteria MESHD) or “mild”. Chest CT scans and clinical statistics data were obtained at four milestones (the date of admission, 3 days after treatment, 1 week after treatment and the time the last CT scan was obtained before discharge orthe completionof our research). Results Thirty patients (18 males and 12 females, age 20–74 years) with confirmed COVID-19 MESHDpneumonia were evaluated. Increased neutrophilswere noted in 11 (36.7%) patients and decreased in 3 (10%) patients. Elevation of C-reactive protein HGNC ( CRP HGNC) in 22 (73.3%) patients and erythrocyte sedimentation rate in 27 (90%) patient were observed, but elevation of procalcitonin was not obvious. Seven (53.8%) patients had elevation of lactate dehydrogenase (LDH).The presentation of CT opacities was mainly in the form of distribution in both the severe andmild groups. The mean PII score in the severe group was 58% and 13.7% in the mild group. The score in the severe group was more than 50%and less than 20%in the mild group at every milestone. The score in the severe group was always higher than the mild group, therefore, the severity of the disease may be positively correlated with PII score. Conclusion The pulmonary inflammation MESHD index (PII) score of chest CT scans correlated with coronavirus disease MESHD ( COVID-19 MESHD) progression and could be used to indicate severity in patients.

    Chest CT imaging features of critically ill COVID-19 MESHD patients  

    Authors: Nan Zhang; Xunhua Xu; Ling-Yan Zhou; Gang Chen; Yu Li; Huiming Yin; Zhonghua Sun

    doi:10.21203/rs.3.rs-18094/v1 Date: 2020-03-19 Source: ResearchSquare

    Objectives To analyze the findings of computed tomography (CT) imaging in critically ill patients diagnosed with coronavirus disease 2019 MESHD ( COVID-19 MESHD).Methods This retrospective study reviewed 60 cr itically ill p MESHDatients (43 males and 17 females, mean age 64.4±11.0 years) with COVID-19 MESHD pn eumonia w MESHDho were admitted to two different clinical centers. Their clinical and medical records were analyzed, and the chest CT images were assessed to determine the involvement of lobes and the distribution of lesions in the lungs between the patients who recovered from the illness and those who died.Results Patients were significantly older in the death group (10/60, 16.67%) than in the recovery group (50/60, 83.33%) (p=0.044). C- reactive protein ( HGNCCR P) HGNC(67.9±50.5 mg/L) was significantly elevated in the death group as opposed to the recovery group (p<0.001). The neutrophil-to-lymphocyte ratio (NLR) was higher in the death group when compared with the recovery group (p=0.030). Involvement of five lung lobes was found in 98% of the patients, with medial or parahilar area involvement observed in all the de ath p MESHDatients. Ground-glass opacities (97%), crazy-paving pattern (92%) and air bronchogram (93%) were the most common radiological findings. Presence of em physema w MESHDas more prevalent in the death group than in the recovery group (30% vs 2%, p=0.011).Conclusions The degree of lung involvement and lesion distribution with dominance in the medial and parahilar pulmonary areas were more severe in the de ath p MESHDatients than in those who recovered. Patient’s age, em physema, MESHDCR P a HGNCnd NLR could be combined with CT to predict the disease outcomes.

    Clinical characteristics of 2019 novel coronavirus pneumonia and risk factors for severe cases: a meta-analysis involving 5,729 patients

    Authors: Zhongheng Zhang; Lin Chen; Hongying Ni; Min Yao; Casarotta Erika; Donati Abele; Carsetti Andrea; Yizhan Guo; Qing Wang

    doi:10.21203/rs.3.rs-17871/v1 Date: 2020-03-17 Source: ResearchSquare

    Objective: 2019 novel coronavirus (2019-nCov) has become a global health emergency. However, the clinical presentations are not well characterized. The study aimed to describe clinical characteristics of 2019-nCov pneumonia MESHD with meta-analytic approach, and to identify risk factors for developing severe cases.Methods: The electronic databases of PubMed, Google Scholar and MedRxiv were searched from December 2019 to February 2020. Records were included if they reported clinical characteristics of 2019-nCov pneumonia MESHD. Studies using crowd sourcing data for mathematical modeling but not reporting clinical data were excluded. The study was reported according to the PRISMA guideline. Data were extracted by independent reviewers. Proportions and mean values were pooled across component studies by using the meta-analytic approach. Data were pooled with fixed or random-effects model as appropriate. Clinical characteristics such as age, gender, symptoms, treatment and mortality outcome were pooled across studies if appropriate. Risk factors for development of severe cases were reported.Results: A total of 13 studies involving 5,729 patients were included for quantitative analysis. The mean age of the study population was 50 years (95% CI: 47 to 53). The most common initial symptoms were cough (68.0%; 95% CI: 65.6 to 70.4%), followed by fever MESHD (56.5%; 95% CI: 53.9 to 58.9%), fatigue MESHD (42.5%; 95% CI: 39.9 to 45.1%) and anorexia MESHD (31.7%; 95% CI: 26.5 to 38.4%). The severe cases accounts for 22.5% of the whole population (95% CI: 21.4 to 23.6%). The overall mortality rate was 1.8% (95% CI: 1.5 to 2.2%), which was consistent with the real time epidemic tracking data. There was substantial heterogeneity across included studies (O = 0.84; p < 0.001). A number of comorbidities and symptoms such as hypertension MESHD, COPD, dyspnea MESHD, elevated C-reactive protein HGNC and procalcitonin were found to be associated with increased risk of developing severe cases.Conclusions: Our study described clinical characteristics of the 2019-nCov pneumonia MESHD in a systematic way. Multiple risk factors were identified for severe cases.

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HGNC Genes
SARS-CoV-2 Proteins


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