Literature DB >> 32242947

Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2: A systematic review and meta-analysis.

Yinghao Cao1, Xiaoling Liu2, Lijuan Xiong3, Kailin Cai1.   

Abstract

BACKGROUND: Currently, the epidemic of coronavirus disease 2019 (COVID-19) has begun to spread worldwide. We aim to explore reliable evidence for the diagnosis and treatment of the COVID-19 by analyzing all the published studies by Chinese scholars on the clinical and imaging features in novel coronavirus pneumonia caused by SARS-CoV-2.
METHODS: We searched five medical databases including two Chinese and three English databases for all published articles on COVID-19 since the outbreak. A random-effects model was designed, and the imaging and clinical data from all studies were collected for meta-analysis.
RESULTS: Overall, 31 articles and 46 959 patients were included, including 10 English articles and 21 Chinese articles. The results of meta-analysis showed that the most common clinical manifestations were fever (87.3%; 0.838-0.909), cough (58.1%; 0.502-0.660), dyspnea (38.3%; 0.246-0.520), muscle soreness or fatigue (35.5%; 0.253-0.456), and chest distress (31.2%; -0.024 to 0.648). The main imaging findings were bilateral pneumonia (75.7%; 0.639-0.871) and ground-glass opacification (69.9%; 0.602-0.796). Among the patients, the incidence that required intensive care unit (ICU) was (29.3%; 0.190-0.395), the incidence with acute respiratory distress syndrome was (28.8%; 0.147-0.429), the incidence with multiple organ dysfunction syndrome was (8.5%; -0.008 to 0.179), and the case fatality rate of patients with COVID-19 was (6.8%; 0.044-0.093).
CONCLUSION: COVID-19 is a new clinical infectious disease that mainly causes bilateral pneumonia and lung function deteriorates rapidly. Nearly a third of patients need to be admitted to the ICU, and patients are likely to present respiratory failure or even death.
© 2020 Wiley Periodicals, Inc.

Entities:  

Keywords:  2019 novel coronavirus pneumonia; SARS-CoV-2; clinical features; imaging finding

Mesh:

Year:  2020        PMID: 32242947      PMCID: PMC7228215          DOI: 10.1002/jmv.25822

Source DB:  PubMed          Journal:  J Med Virol        ISSN: 0146-6615            Impact factor:   20.693


INTRODUCTION

The 2019 novel coronavirus pneumonia (NCP) initially broke out in China, especially in Hubei province. The NCP is caused by a new coronavirus (SARS‐COV‐2) of the Sarbe virus subgenus, a member of orthocoronavirus subfamily. SARS‐COV‐2 is a member of the coronavirus family along with SARS‐CoV and MERS‐CoV. With the deepening of research, more and more evidence show that its transmission channels are diversified, and its transmission speed and infectivity are stronger than SARS‐CoV and MERS‐CoV. , , Since the outbreak of the epidemic, China has taken active prevention and control measures and achieved good results, but, recently, the epidemic situation abroad has begun to develop into an uncontrollable situation. As of 28 February 2020, the epidemic of NCP has affected six continents, and the epidemic situation in South Korea, Italy, Japan, and other countries is extremely serious. On 29 February, the “China‐WHO NCP (COVID‐19) Joint Inspection Report” stated that the NCP is almost susceptible to everyone on the same day. On 11 March, the WHO declared the SARS‐CoV‐2 outbreak as pandemic. Currently, published studies and case reports indicate that patients with NCP have very different clinical manifestations, laboratory tests, and imaging tests, making clinical diagnosis and treatment limited. Therefore, it is urgent to improve the understanding of the clinical characteristics of patients with NCP to further guide clinical and scientific research through evidence‐based medicine.

MATERIALS AND METHODS

Search strategy and study selection

This study was approved by the Ethics Committee of the Tongji Medical College, Huazhong University of Science and Technology. The literature search was performed according to the PRISMA (preferred reporting items for systematic reviews and meta‐analyses) process. The search was conducted in five popular medical databases including three English databases (PubMed, Cochrane Library, and Embase) and two Chinese databases (National Knowledge Infrastructure [CNKI] and China Biology Medicine disc [CBMdisc]). The searches were concluded by 1 March 2020. The language limit is English and Chinese. The retrieval is a combination of subject words and free words, and the keywords are as follows: “2019 novel coronavirus pneumonia,” “COVID‐19,” “Coronavirus,” “SARS‐CoV‐2,” “Wuhan Coronavirus,” “clinical features,” “2019 novel coronavirus pneumonia,” and “imaging features.”

Inclusion/exclusion criteria

Inclusive criteria are as follows: (a) research types: cross‐sectional studies and case series; (b) research subjects: patients with confirmed NCP, including patients with clinical diagnosis; and (c) data items: including clinical characteristics, biochemical indicators, and imaging signs. Exclusive criteria are as follows: (a) the type of study is case report, review, and so forth; (b) repeated research; and (c) lack of the above case data.

Data extraction and paper quality evaluation

The titles and abstracts of all retrieved references were independently reviewed by two investigators, and if there was any ambiguity in the search process, the decision was made by a third investigator. (a) The basic characteristics of the included literature are as follows: author, publication date, journal, research type, number of patients, quality score, and so forth. (b) The basic characteristics of the research subjects are as follows: age, sex, comorbidities, clinical manifestations, laboratory test results, imaging manifestations, and so on. The quality of all included literature was assessed using the Institute of Health Economics (IHE) scale.

Statistical analysis

The statistical software Stata version 14.0 and Open Meta‐Analyst were used for meta‐analysis of single‐arm studies. We first unified all units of variables and, then, expressed classified variables as percentages and expressed continuous variables as mean ± standard deviation. The combined prevalence and 95% CI were calculated using a random‐effects model. We performed the Egger test to assess publication bias in all literature works, and P < .05 was considered as publication bias.

RESULTS

Literature inclusion and characteristics

A total of 956 articles were retrieved. After deleting duplicates, 96 studies remained, of which 860 were excluded based on the title or abstract. Finally, 65 were eliminated after reading the full text, and a total of 31 articles , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and 46 959 patients were included in this meta‐analysis (Figure 1). The main characteristics of the included studies are shown in Table 1. Publication bias was assessed with a funnel plot for the standard error by logit event, with no evidence of bias. Additionally, the Egger test (P = .091) suggested that there was no notable evidence of publication bias.
Figure 1

Diagram of documents retrieval

Table 1

The characteristics of the included literature

ReferencesJournalYearDate (M/D)CountryNo. patientSex (male)Average ageResearch typeQuality
Huang et al 6 Lancet 202001/24China413049Retrospective study8
Chen et al 7 Lancet 202001/30China996755.5Retrospective study8
Yu et al 35 J Pract Med 202001/31China402245.9Retrospective study5
Michael et al 8 Radiology 202002/04China211351Retrospective study5
Wang et al 9 JAMA 202002/07China1387556Retrospective study8
Liu et al 10 Chin J Pediatr 202002/07China1376157Retrospective study5
Chang et al 11 JAMA 202002/07China131034Retrospective study6
Zheng et al 12 Shanghai Med J 202002/10China70Retrospective study4
Liu et al 13 Sci China Life Sci 202002/12China128Retrospective study6
Gao et al 14 J Xi'an Jiaotong Univ (Med Sci) 202002/13China10641.8Retrospective study5
Gong et al 15 Radiol Prac 202002/13China331351Retrospective study5
Pan et al 16 Eur Radiol 202002/13China6333Retrospective study6
Liu et al 17 Preprint Lancet 202002/13China24843Retrospective study6
Pan et al 18 Radiology 202002/13China21640.9Retrospective study5
Zhang et al 19 Chin J Tuberc Respir Dis 202002/15China9536Case series5
Feng et al 20 Chin J Pediatr 202002/17China155Case series5
Wang et al 21 Chin J Pediatr 202002/17China34148Retrospective study5
Zhang et al 22 J. Chin Epi 202002/17China44 67222 981Retrospective study6
Liu et al 23 Radiol Prac 202002/18China413248.45Retrospective study5
Zhuang et al 24 Chin J Nosocomiology 202002/19China2618Retrospective study6
Wang et al 25 J Clin Med 202002/19China3016Retrospective study5
Chen et al 26 Herald Med 202002/19China542758.5Retrospective study5
Zhong et al 27 Med J Wuhan Univ 202002/19China301850.17Retrospective study5
Fu et al 28 Med J Wenzhou Univ 202002/20China352147Retrospective study5
Yang et al 29 Lancet Respir Med 202002/21China523559.7Retrospective study7
Ji et al 30 Chin J Med Imaging Technol 202002/24China452745.4Retrospective study6
Chen et al 36 Chin J Tuberc Respir Dis 202002/25China292156Retrospective study5
Chen et al 31 J Clin Med 202002/26China12863Retrospective study4
Zeng et al 32 J Emerg Tradit Chin Med 202002/27China181045.94Retrospective study5
Cao et al 33 Med J Wuhan Univ 202002/28China362072.45Retrospective study5
Guan et al 34 NEJM 202002/29China109964047Retrospective study8
Diagram of documents retrieval The characteristics of the included literature

Meta‐analysis results

Demographical characteristics and comorbidities

The mean age of the patients with SARS‐COV‐2 infection was 46.62 (95% CI, 31.710‐61.531) and 55.6% (95% CI, 0.530‐0.602) were male. About 35.6% (0.267‐0.444) of patients had comorbidities, including 18.3% (0.130‐0.236) with hypertension, 11.2% (0.078‐0.145) with cardiovascular disease, 10.3% (0.069‐0.136) with diabetes, 3.9% (0.011‐0.067) with chronic obstructive pulmonary disease, 3.0% (0.021‐0.039) with chronic hepatonephropathy, and 1.1% (0.003‐0.020) with tumor (Table 2 and Figures 2 and 3).
Table 2

Meta‐analysis results of the incidence of demographical and comorbidities

Variable N a Estimate95% CIN b Standard error P T 2 Q P c I 2
Sex, male300.5560.530 to 0.60224 2500.018<.0010.004104.391<.00172.22
Age, mean1446.6231.71 to 61.5313347.608<.001801.9482756.956<.00199.528
ICU90.2930.190 to 0.39523710.052<.0010.022487.408<.00198.359
Comorbidities100.3560.267 to 0.4444640.045<.0010.01575.378<.00188.06
Tumor80.0110.003 to 0.0201350.004.0090.00022.143.00268.387
Diabetes130.1030.069 to 0.13612610.017<.0010.00297.488<.00187.691
Hypertension120.1830.130 to 0.23629640.027<.0010.006160.717<.00193.156
Cardiovascular disease110.1120.078 to 0.14510230.017<.0010.002136.694<.00192.684
Phthisis30.021−0.005 to 0.0475150.013.1200.0002.655.26524.672
COPD80.0390.011 to 0.067460.014.0060.00153.971<.00187.03
Chronic hepatonephropathy70.0300.021 to 0.039460.005<.0010.0005.144.5250

Abbreviations: CI, confidence interval; COPD, chronic obstructive pulmonary disease; ICU, intensive care unit.

Number of studies.

Number of patients.

Heterogeneity P value.

Figure 2

The forest plots of age and sex. A, age and (B) sex

Figure 3

The forest plots of the incidence of comorbidities and intensive care unit (ICU). A, Comorbidities; (B) tumor; (C) diabetes; (D) hypertension; (E) cardiovascular disease; (F) phthisis; (G) chronic obstructive pulmonary disease; (H) chronic hepatonephropathy; (I) ICU

Meta‐analysis results of the incidence of demographical and comorbidities Abbreviations: CI, confidence interval; COPD, chronic obstructive pulmonary disease; ICU, intensive care unit. Number of studies. Number of patients. Heterogeneity P value. The forest plots of age and sex. A, age and (B) sex The forest plots of the incidence of comorbidities and intensive care unit (ICU). A, Comorbidities; (B) tumor; (C) diabetes; (D) hypertension; (E) cardiovascular disease; (F) phthisis; (G) chronic obstructive pulmonary disease; (H) chronic hepatonephropathy; (I) ICU

Clinical features

The incidence of fever was 87.3% (0.838‐0.909), that of cough was 58.1% (0.502‐0.660), that of sore throat was 12% (0.062‐0.177), that of expectoration was 29.4% (0.171‐0.417), that of chest distress was 31.2% (−0.024 to 0.648), that of muscle soreness or fatigue was 35.5% (0.253‐0.456), that of headache was 9.4% (0.063‐0.126), that of diarrhea was 6.8% (0.044‐0.092), and that of dyspnea was 38.3% (0.246‐0.520) (Table 3 and Figure 4).
Table 3

Meta‐analysis results of the incidence of clinical manifestations

Variable N a Estimate95% CIN b Standard error P T 2 Q P c I 2
Fever270.8730.838 to 0.90918420.018<.0010.006177.086<.00185.318
Cough270.5810.502 to 0.66013540.040<.0010.037332.025<.00192.169
Sore throat90.1200.062 to 0.1772000.029<.0010.00558.432<.00186.309
Expectoration100.2940.171 to 0.4174660.063<.0010.035266.04<.00196.617
Chest distress50.312−0.024 to 0.648380.172.0690.144204.480<.00198.044
Muscle soreness or fatigue180.3550.253 to 0.4567810.052<.0010.038220.594<.00192.747
Headache140.0940.063 to 0.1262140.016<.0010.00237.648<.00165.47
Diarrhea150.0680.044 to 0.0921030.012<.0010.00132.263.00456.607
Dyspnea110.3830.246 to 0.5204090.070<.0010.051351.966<.00197.159

Abbreviation: CI, confidence interval.

Number of studies.

Number of patients.

Heterogeneity P value.

Figure 4

The forest plots of the incidence of clinical features. A, Fever; (B) cough; (C) sore throat; (D) expectoration; (E) chest distress; (F) muscle soreness or fatigue; (G) headache; (H) diarrhea; (I) dyspnea

Meta‐analysis results of the incidence of clinical manifestations Abbreviation: CI, confidence interval. Number of studies. Number of patients. Heterogeneity P value. The forest plots of the incidence of clinical features. A, Fever; (B) cough; (C) sore throat; (D) expectoration; (E) chest distress; (F) muscle soreness or fatigue; (G) headache; (H) diarrhea; (I) dyspnea

Laboratory tests

The laboratory findings showed leukocytosis in 11.0% (0.070‐0.150), leukopenia in 36.9% (0.146‐0.593), lymphocytopenia in 57.4% (0.410‐0.737), high C‐reactive protein (CRP) in 61.3% (0.451‐0.774), high lactate dehydrogenase (LDH) in 57.0% (0.360‐0.780), and high erythrocyte sedimentation rate (ESR) in 42.2% (0.076‐0.767) (Table 4 and Figure 5).
Table 4

Meta‐analysis results of the incidence of laboratory tests

Variable N a Estimate95% CIN b Standard error P T 2 Q P c I 2
Leukocytosis130.1100.070‐0.1501410.020<.0010.003115.035<.00189.568
Leukopenia160.3690.146‐0.5935410.114.0010.2045837.766<.00199.743
Lymphocytopenia160.5740.410‐0.73711570.083<.0010.1051113.409<.00198.653
High CRP150.6130.451‐0.7749100.082<.0010.089564.423<.00197.697
High LDH70.5700.360‐0.7804770.107<.0010.076236.597<.00197.464
High ESR50.4220.076‐0.7671320.176.0170.151188.792<.00197.881

Abbreviations: CI, confidence interval; CRP, C‐reactive protein; ESR, erythrocyte sedimentation rate; LDH, lactate dehydrogenase.

Number of studies.

Number of patients.

Heterogeneity P value.

Figure 5

The forest plots of the incidence of laboratory test features. A, Leukocytosis; (B) leukopenia; (C) lymphocytopenia; (D) high C‐reactive protein; (E) high lactate dehydrogenase; (F) high erythrocyte sedimentation rate

Meta‐analysis results of the incidence of laboratory tests Abbreviations: CI, confidence interval; CRP, C‐reactive protein; ESR, erythrocyte sedimentation rate; LDH, lactate dehydrogenase. Number of studies. Number of patients. Heterogeneity P value. The forest plots of the incidence of laboratory test features. A, Leukocytosis; (B) leukopenia; (C) lymphocytopenia; (D) high C‐reactive protein; (E) high lactate dehydrogenase; (F) high erythrocyte sedimentation rate

Imaging features

At the chest computed tomography (CT), the pneumonia compromise was predominantly bilateral in 75.5% (0.639‐0.871) and unilateral 20.4% (0.106‐0.302). The most common patterns on chest CT were ground‐glass (69.9%, 0.602‐0.796), followed by irregular or halo sign (54.4%, 0.255‐0.833), air bronchogram (51.3%, 0.326‐0.701), bronchovascular bundle thickening (39.5%, 0.082‐0.708), grid‐form shadow (24.4%, 0.116‐0.371), and hydrothorax (18.5%, 0.001‐0.370) (Table 5 and Figure 6).
Table 5

Meta‐analysis results of the incidence of chest imaging

Variable N a Estimate95% CIN b Standard error P T 2 Q P c I 2
Unilateral190.2040.106‐0.3025220.050<.0010.043751.641<.00197.605
Bilateral210.7550.639‐0.87111960.059<.0010.0681582.357<.00198.736
Lung consolidation90.3690.215‐0.5231220.079<.0010.05096.579<.00191.717
Ground‐glass210.6990.602‐0.79614130.049<.0010.0471482.862<.00198.651
Air bronchogram60.5130.326‐0.7011190.096<.0010.04849.183<.00189.834
Grid‐form shadow60.2440.116‐0.371640.065<.0010.02239.574<.00187.365
Bronchovascular bundles thickening40.3950.082‐0.708410.160.0130.09768.065<.00195.592
Hydrothorax70.1850.001‐0.370230.094.0490.059281.788<.00197.871
Irregular or halo sign50.5440.255‐0.8331070.148<.0010.104105.731<.00196.217

Abbreviation: CI, confidence interval.

Number of studies.

Number of patients.

Heterogeneity P value.

Figure 6

The forest plots of the incidence of imaging features. A, Unilateral; (B) bilateral; (C) lung consolidation; (D) ground‐glass; (E) air bronchogram; (F) grid‐form shadow; (G) bronchovascular bundles thickening; (H) hydrothorax; (I) irregular or halo sign

Meta‐analysis results of the incidence of chest imaging Abbreviation: CI, confidence interval. Number of studies. Number of patients. Heterogeneity P value. The forest plots of the incidence of imaging features. A, Unilateral; (B) bilateral; (C) lung consolidation; (D) ground‐glass; (E) air bronchogram; (F) grid‐form shadow; (G) bronchovascular bundles thickening; (H) hydrothorax; (I) irregular or halo sign

Complications and outcomes

Among the infected patients, severe cases who required intensive care unit (ICU) were 29.3% (0.190‐0.395), and the incidence of acute respiratory distress syndrome (ARDS) was 28.8% (0.147‐0.429), that of acute cardiac injury was 14.1% (0.079‐0.204), that of acute renal injury was 7.1% (0.031‐0.110), that of shock was 4.7% (0.009‐0.086), that of multiple organ dysfunction syndrome (MODS) was 8.5% (−0.008 to 0.179), and the case fatality rate was 6.8% (0.044‐0.093) (Table 6 and Figure 7).
Table 6

Meta‐analysis results of the incidence of complications

Variable N a Estimate95% CIN b Standard error P T 2 Q P c I 2
ARDS80.2880.147 to 0.4291600.072<.0010.037195.606<.00196.421
ACI70.1410.079 to 0.2041510.032<.0010.00549.732<.00187.935
ARI80.0710.031 to 0.110580.02<.0010.00236.801<.00180.979
Shock50.0470.009 to 0.086310.020.0160.00115.319.00473.889
MODS40.085−0.008 to 0.17990.048.0740.0045.050.08060.392
Mortality80.0680.044 to 0.09311110.012<.0010.001110.944<.00193.69

Abbreviations: ACI, acute cardiac injury; ARDS, acute respiratory distress syndrome; ARI, acute renal injury; CI, confidence interval; MODS, multiple organ dysfunction syndrome.

Number of studies.

Number of patients.

Heterogeneity P value.

Figure 7

The forest plots of the incidence of complication. A, acute respiratory distress syndrome; (B) acute cardiac injury; (C) acute renal injury; (D) shock; (E) multiple organ dysfunction syndrome; (F) mortality

Meta‐analysis results of the incidence of complications Abbreviations: ACI, acute cardiac injury; ARDS, acute respiratory distress syndrome; ARI, acute renal injury; CI, confidence interval; MODS, multiple organ dysfunction syndrome. Number of studies. Number of patients. Heterogeneity P value. The forest plots of the incidence of complication. A, acute respiratory distress syndrome; (B) acute cardiac injury; (C) acute renal injury; (D) shock; (E) multiple organ dysfunction syndrome; (F) mortality

DISCUSSION

The results of this study showed that fever (87.3%) and cough (58.1%) were the main clinical manifestations in the patients with NCP in China. This was followed by dyspnea (38.3%), myalgia or weakness (35.5%), and chest tightness (31.2%), and some patients also presented other clinical symptoms such as chills, cough, conjunctival discomfort, headache, shortness of breath, and joint pain. A few patients had nausea, vomiting, diarrhea, and other abdominal discomfort symptoms, whereas very few patients showed hemoptysis symptoms. Most patients with NCP required hospitalization, of which 29.3% required intensive care. The main complications are respiratory failure, ARDS (28.8%) and multiple organ failure (8.5%), and heart failure, shock, renal injury, sepsis, striated muscle lysis, and diffuse intravascular coagulation are rare. According to the severity, the patients with NCP can be divided into mild, normal type (80%), medium type, and severe type (13.8%). The clinical manifestations of patients with different severity vary greatly. According to statistics, the fatality rate in China is about 3.8%, lower than that of SARS (9.6%) and MERS (35%). The main causes of death are massive alveolar damage and progressive respiratory failure. Generally, viral pneumonia mainly involves pulmonary interstitium, producing pulmonary interstitial fibrosis. The autopsy report of the first NCP patient in China found that coronavirus disease 2019 (COVID‐19) mainly caused the inflammatory response characterized by deep airway and alveolar damage, accompanied by a large amount of viscous secretions in the airway. The pulmonary transparent membrane became less obvious, and the degree of fibrosis was not as severe as SARS. However, the degree of effect of COVID‐19 on pulmonary fibrosis still needs to be paid close attention, which is also an important factor influencing pulmonary function in the prognosis of patients with NCP. In this meta‐analysis, white blood cells were normal or decreased in most patients, lymphocytes were mostly decreased, and CRP, LDH, ESR level was elevated in some patients. A few patients had elevated creatine kinase procalcitonin bilirubin, whereas some had decreased albumin and elevated ALT, AST. The pathological results of patients with SARS‐COV‐2 suggested that the excessive activation of T lymphocytes, which is characterized by increased Th17 cells and high toxicity of CD8+ T cells, has caused severe immune damage to a certain extent. This may be the main reason for the loss of lymphocytes in patients. Sequence comparison analysis showed that the S spike protein of SARS‐COV‐2 contains a SARS‐CoV‐like receptor binding domain, which indicates that ACE2 may be the main receptor of SARS‐COV‐2. ACE2 was highly expressed in gastric and testicular epithelial cells, and also enriched in colon, heart, kidney, and so on. Over‐expressed ACE2 may be related to the elevated liver enzyme. The similarity of SARS‐COV‐2 and SARS‐CoV gene sequences suggests that the mechanism of action may also be similar. SARS‐COV‐2 enters host cells through dense S protein, , acts on bronchial epithelial cells through ACE2 receptor, and then infects other cells, causing a series of immune responses or inflammatory cytokine storm in severe cases. In addition, the sequence alignment showed that the SARS‐COV‐2 and SARS‐CoV S2 subunits are highly conserved, and the overall identity in the HR1 and HR2 domains is 92.6% and 100%, respectively. This suggested that novel coronary pneumonia drugs research may base on this site. In imaging results, this meta‐analysis showed that 75.7% of the patients had lesions involving both lungs, and 69.9% showed ground‐glass shadows on imaging, mostly interstitial pulmonary lesions. Chest CT showed consolidation shadow nodular or patchy shadow in some patients, whereas there also existed other characteristics in few patients, such as chest‐shaped shadows, thick cord‐like shadows, pleural reactions, thickened blood vessels, pleural effusion, and bronchial inflation, subpleural line, halo sign, antihalo sign, mosaic sign, and so on. The course of the critically ill patient progressed rapidly, and chest CT could cause “white lung” changes within a few days. Because the sensitivity of nucleic acid test is closely related to the detection sample and testing the sample of lower respiratory tract is more sensitive, nucleic acid test shows partial false negative result. Chest CT examination, as an important examination method for NCP, is highly sensitive to SARS‐COV‐2 (even up to 97% in epidemic areas) and is an important supplement to nucleic acid detection. In patients with negative nucleic acid test reports, chest CT results are still of high auxiliary diagnostic value. In addition, imaging manifestations of patients also show dynamic evolution in the course of disease progression. Current research showed that COVID‐19, which source may be Chinese chrysanthemum head bats and pangolin may be a potential intermediate host, can cause a zoonotic disease. Since late February 2020, the number of confirmed cases of NCP abroad has increased rapidly, which may indicate a pandemic. The “three early” principle (early detection, early diagnosis, and early treatment) followed by disease prevention and treatment is particularly important in the prevention and treatment of SARS‐COV‐2. In addition, the clinical manifestations of patients with neocoronary pneumonia are diverse and the atypical symptoms also account for part of the proportion. Therefore, we systematically analyzed the clinical manifestations and auxiliary examination results of patients with COVID‐19, so as to reflect the disease characteristics more comprehensively, increase the discrimination of the disease, and strive for early diagnosis, early isolation, and early treatment. The number of newly diagnosed cases of NCP has been rising worldwide recently, especially in South Korea, Italy, Iran, and Japan. To control the further spread of the epidemic, it is still necessary to strictly follow the management measures for the prevention and treatment of infectious diseases and follow the WHO declaration on public health emergencies of international concern. Certainly, prevention of imported cases is also extremely important. Particularly, in some densely populated markets, stations, large ports, and other places, protective deployment measures should be strengthened to ensure that protective equipment, drugs, medical supplies, and so on are sufficient. National public health capabilities and infrastructure remain at the core of global health security, as they are the first line of defense for infectious disease emergencies. The International Health Organization, all countries, and all humanity need to pay great attention to SARS‐COV‐2. This meta‐analysis, with large enough sample size, relatively high literature quality, and more comprehensive analysis, included a total of 31 literature studies, including 46 959 patients with NCP. The conclusions are very credible to some extent. This article still has the following limitations, for example, (a) the samples are domestic cases, without foreign cases; (b) different data sources may lead to some bias in the results; and (c) there exists some publication bias. Therefore, the conclusions of this article need to be further verified.

CONCLUSION

COVID‐19 is a new clinical infectious disease, which mainly causes bilateral pneumonia and lung function deteriorates rapidly. Nearly a third of patients need to be admitted to the ICU, and patients are likely to present respiratory failure or even death.

CONFLICT OF INTERESTS

The authors declare that there are no conflict of interests.
  31 in total

1.  Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.

Authors:  Dawei Wang; Bo Hu; Chang Hu; Fangfang Zhu; Xing Liu; Jing Zhang; Binbin Wang; Hui Xiang; Zhenshun Cheng; Yong Xiong; Yan Zhao; Yirong Li; Xinghuan Wang; Zhiyong Peng
Journal:  JAMA       Date:  2020-03-17       Impact factor: 56.272

2.  Molecular Diagnosis of a Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia.

Authors:  Daniel K W Chu; Yang Pan; Samuel M S Cheng; Kenrie P Y Hui; Pavithra Krishnan; Yingzhi Liu; Daisy Y M Ng; Carrie K C Wan; Peng Yang; Quanyi Wang; Malik Peiris; Leo L M Poon
Journal:  Clin Chem       Date:  2020-04-01       Impact factor: 8.327

3.  A pneumonia outbreak associated with a new coronavirus of probable bat origin.

Authors:  Peng Zhou; Xing-Lou Yang; Xian-Guang Wang; Ben Hu; Lei Zhang; Wei Zhang; Hao-Rui Si; Yan Zhu; Bei Li; Chao-Lin Huang; Hui-Dong Chen; Jing Chen; Yun Luo; Hua Guo; Ren-Di Jiang; Mei-Qin Liu; Ying Chen; Xu-Rui Shen; Xi Wang; Xiao-Shuang Zheng; Kai Zhao; Quan-Jiao Chen; Fei Deng; Lin-Lin Liu; Bing Yan; Fa-Xian Zhan; Yan-Yi Wang; Geng-Fu Xiao; Zheng-Li Shi
Journal:  Nature       Date:  2020-02-03       Impact factor: 69.504

4.  Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission.

Authors:  Xintian Xu; Ping Chen; Jingfang Wang; Jiannan Feng; Hui Zhou; Xuan Li; Wu Zhong; Pei Hao
Journal:  Sci China Life Sci       Date:  2020-01-21       Impact factor: 6.038

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

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

6.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

7.  Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.

Authors:  Joseph T Wu; Kathy Leung; Gabriel M Leung
Journal:  Lancet       Date:  2020-01-31       Impact factor: 79.321

8.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

9.  Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China.

Authors:  Péter Boldog; Tamás Tekeli; Zsolt Vizi; Attila Dénes; Ferenc A Bartha; Gergely Röst
Journal:  J Clin Med       Date:  2020-02-19       Impact factor: 4.241

10.  Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury.

Authors:  Yingxia Liu; Yang Yang; Cong Zhang; Fengming Huang; Fuxiang Wang; Jing Yuan; Zhaoqin Wang; Jinxiu Li; Jianming Li; Cheng Feng; Zheng Zhang; Lifei Wang; Ling Peng; Li Chen; Yuhao Qin; Dandan Zhao; Shuguang Tan; Lu Yin; Jun Xu; Congzhao Zhou; Chengyu Jiang; Lei Liu
Journal:  Sci China Life Sci       Date:  2020-02-09       Impact factor: 6.038

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  113 in total

1.  Patient with pneumonia caused by COVID-19: Surgical findings and radiological correlation of lung lesions.

Authors:  Carlos Déniz-Armengol; Ricard Ramos-Izquierdo; Anna Ureña-Lluveras
Journal:  Arch Bronconeumol       Date:  2020-04-24       Impact factor: 4.872

2.  COVID-19 in Patients with Cancer.

Authors:  Ali Nowroozi; Sepideh Razi; Kamal Kant Sahu; Fabio Grizzi; Jann Arends; Mahsa Keshavarz-Fathi; Nima Rezaei
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

Review 3.  Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection.

Authors:  Seyed Hamid Safiabadi Tali; Jason J LeBlanc; Zubi Sadiq; Oyejide Damilola Oyewunmi; Carolina Camargo; Bahareh Nikpour; Narges Armanfard; Selena M Sagan; Sana Jahanshahi-Anbuhi
Journal:  Clin Microbiol Rev       Date:  2021-05-12       Impact factor: 26.132

Review 4.  COVID-19: the importance of physical therapy in the recovery of workers' health.

Authors:  Luís Eduardo Santos Paz; Bruno José da Silva Bezerra; Taciane Machado de Melo Pereira; Welma Emidio da Silva
Journal:  Rev Bras Med Trab       Date:  2021-04-30

5.  Late incidence of SARS-CoV-2 infection in a highly-endemic remote rural village. A prospective population-based cohort study.

Authors:  Oscar H Del Brutto; Aldo F Costa; Robertino M Mera; Bettsy Y Recalde; Javier A Bustos; Héctor H García
Journal:  Pathog Glob Health       Date:  2020-09-29       Impact factor: 2.894

6.  Pediatric lung imaging features of COVID-19: A systematic review and meta-analysis.

Authors:  Gustavo Nino; Jonathan Zember; Ramon Sanchez-Jacob; Maria J Gutierrez; Karun Sharma; Marius George Linguraru
Journal:  Pediatr Pulmonol       Date:  2020-11-02

7.  Study on the prognosis predictive model of COVID-19 patients based on CT radiomics.

Authors:  Dandan Wang; Chencui Huang; Siyu Bao; Tingting Fan; Zhongqi Sun; Yiqiao Wang; Huijie Jiang; Song Wang
Journal:  Sci Rep       Date:  2021-06-02       Impact factor: 4.379

Review 8.  A Review of Prolonged Post-COVID-19 Symptoms and Their Implications on Dental Management.

Authors:  Trishnika Chakraborty; Rizwana Fathima Jamal; Gopi Battineni; Kavalipurapu Venkata Teja; Carlos Miguel Marto; Gianrico Spagnuolo
Journal:  Int J Environ Res Public Health       Date:  2021-05-12       Impact factor: 3.390

9.  Management of Spine Trauma in COVID-19 Pandemic: A Preliminary Report.

Authors:  Mohammadreza Chehrassan; Adel Ebrahimpour; Hasan Ghandhari; Morteza Sanei Taheri; Bahador Athari; Mehrdad Sadighi; Meisam Jafari KafiAbadi; Amin Karami; Alireza Zali
Journal:  Arch Bone Jt Surg       Date:  2020-04

Review 10.  Covid-19 imaging: A narrative review.

Authors:  Hanae Ramdani; Nazik Allali; Latifa Chat; Siham El Haddad
Journal:  Ann Med Surg (Lond)       Date:  2021-06-18
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