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Indian Journal of Medical Microbiology xxx (xxxx) xxx
Contents lists available at ScienceDirect
Indian Journal of Medical Microbiology
journal homepage: www.journals.elsevier.com/indian-journal-of-medical-microbiology
Clinical, epidemiological, laboratory, and radiological characteristics of
novel Coronavirus (2019-nCoV) in retrospective studies: A systemic review
and meta-analysis
Ebrahim Kouhsari a, b, Khalil Azizian c, Mohammad Sholeh d, Mohammad Shayestehpour e, f,
Marzieh Hashemian a, Somayeh Karamollahi a, Sajad Yaghoubi g, **, Nourkhoda Sadeghiifard a, *
a
Clinical Microbiology Research Center, Ilam University of Medical Sciences, Ilam, Iran
Laboratory Sciences Research Center, Golestan University of Medical Sciences, Gorgan, Iran
c
Department of Lab Science, Sirjan School of Medical Sciences, Sirjan, Iran
d
Department of Microbiology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran
e
Department of Microbiology and Immunology, Faculty of Medicine, Kashan University of Medical Sciences, Kashan, Iran
f
Autoimmune Diseases Research Center, Kashan University of Medical Sciences, Kashan, Iran
g
Department of Clinical Microbiology, Iranshahr University of Medical Sciences, Iranshahr, Iran
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
2019-nCoV
Clinical
Epidemiological
Laboratory, and radiological characteristics
Meta-analysis
Background: In December 2019, a novel pneumonia related to the 2019 coronavirus unexpectedly developed in
Wuhan, China. We aimed to review data of the novel Coronavirus (2019-nCoV) by analyzing all the published
retrospective studies on the clinical, epidemiological, laboratory, and radiological characteristics of patients with
2019-nCoV.
Methods: We searched in four bibliographic databases PubMed, Scopus, Embase, and Web of Science) for studies
March 10, 2020 focused on the clinical, epidemiological, laboratory, and radiological characteristics of patients
with 2019-nCoV for meta-analysis. The Newcastle-Ottawa Scale was used to quality assessment, and publication
bias was analyzed by Egger's test. In the meta-analysis, a random-effects model with Stata/SE software, v.14.1
(StataCorp, College Station, TX) was used to obtain a pooled incidence rate.
Results: Fifty studies were included in this systematic review and meta-analysis with 8815 patients and the mean
age was 46 years and 4647 (52.7%) were male. The pooled incidences rate of clinical symptoms were: fever (83%,
95% CI: 0.77, 0.89), cough (59%, 95% CI: 0.48, 0.69), myalgia or fatigue (31%, 95% CI: 0.23, 0.39), sputum
production (29%, 95% CI: 0.21, 0.39), and dyspnea (19%, 95% CI: 0.12, 0.26). The pooled incidence rate of acute
respiratory distress syndrome (ARDS) was (22%, 95% CI: 0.00, 0.60).
Conclusion: The results of this systemic review and meta-analysis present a quantitative pooled incidence rate of
different characters of 2019-nCoV and has great potential to develop diagnosis and patient's stratification in 2019nCoV. However, this conclusions of this study still requisite to be warranted by more careful design, larger sample
size multivariate studies to corroborate the results of this meta-analysis.
1. Introduction
In December 8, 2019 a new coronavirus, which was called 2019 novel
coronavirus (2019-nCoV), arise the pneumonia epidemic of the severe
respiratory disease from Wuhan (Huanan seafood market) across China
which now causes the main public health threats worldwide [1,2]. On
January 30, 2020, WHO stated that the epidemic of the Severe Acute
Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) become as a public
health emergency of international concern (PHEIC) [3]. Currently, the
number of patients with 2019-nCoV is dramatically increasing to other
countries around the world [4,5]. According to worldwide statistics, the
death rate is ~4.6%. Main symptoms of 2019-nCoV include pneumonia,
fever, myalgia or fatigue [4,5]. However, some characterizations and
conclusions in the published relevant research were varied, limited and
* Corresponding author. Banganjab, Pazhouhesh Blvd, Ilam University of Medical Sciences, Ilam, Iran.
** Corresponding author. Noor St, Shahdai Anonymous Park, Iranshahr School of Medical Sciences, Iranshahr, Iran.
E-mail addresses: sajadyaghuby@gmail.com (S. Yaghoubi), Sadeghiifard@gmail.com (N. Sadeghiifard).
https://doi.org/10.1016/j.ijmmb.2020.10.004
Available online xxxx
0255-0857/© 2020 Indian Association of Medical Microbiologists. Published by Elsevier B.V. All rights reserved.
Please cite this article as: Kouhsari E et al., Clinical, epidemiological, laboratory, and radiological characteristics of novel Coronavirus (2019-nCoV) in
retrospective studies: A systemic review and meta-analysis, Indian Journal of Medical Microbiology, https://doi.org/10.1016/j.ijmmb.2020.10.004
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
and the duplicates were removed using EndNote X7 (Thomson Reuters,
New York, NY, USA).
controversial. At present, there is no successful vaccine or antiviral drugs
has been clinically approved for 2019-nCoV. Therefore, to acquire more
exact conclusions on the clinical, epidemiological, laboratory, and radiological characteristics and also to propose significant help for current
clinical studies of patients with 2019-nCoV, we performed a systemic
review and meta-analysis of all these evidence-based medical epidemiological, clinical, laboratory, and radiological characters.
2.2. Selection criteria and data extraction
One of the team researchers randomly evaluated the search results
and reported that no relevant study was ignored. Three authors
(Ebrahim Kouhsari, Mohammad Sholeh and Sajad Yaghoubi) independently done all these steps and reviewed the potentially relevant
studies to clarify whether they met the predetermined eligibility
criteria. Any discrepancies and inconsistencies with article selection
were resolved through discussion, and a fourth author (Nourkhoda
Sadeghifard) was available to resolve the disagreement. In the first
phase, studies obtained from the literature search were precisely
screened by titles and abstracts to exclude irrelevant studies. The full
text of relevant studies was reviewed in depth conferring to definite
criteria. References lists of all related studies were also reviewed for
any other related publication.
Studies were excluded if they met the following conditions: reviews, theses, books, conference papers, repeat articles, letters, editorials, expert opinions, animal, in vitro studies, and overlapping,
unusable data sets (Fig. 1). Information extracted from retrospective
2. Methods
2.1. Search strategy and study selection
Four bibliographic databases, including international databases
(PubMed, Scopus, Embase, and Web of Science) for relevant articles were
searched (Until 10th/March/2020) by using the following keywords:
(”2019 Novel coronavirus” OR “2019-nCoV” OR “Severe Acute Respiratory Syndrome Coronavirus 2” OR “SARS-CoV-2” OR “COVID-19” OR
“Wuhan Coronavirus” OR “Wuhan pneumonia”) in the Title/Abstract/
Keywords fields. No limitation regarding ethnicity, language, country,
gender, patient age was used while searching databases, but inclusion of
the study in our full analysis required at least the abstract to be available
in English. The records found through database searching were merged
Fig. 1. Flow diagram showing the data selection process.
2
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
points: Moderate quality, 3 points: low quality). Higher score indicates higher study quality. A third reviewer (Ebrahim Kouhsari)
adjudicated in any case of disagreement. Need for arbitration and
reason was reported in the data collection tool.
studies on the clinical, epidemiological, laboratory, and radiological
characteristics of novel Coronavirus (2019-nCoV) infected patients
(supplementary data 1).
2.3. Outcomes
2.5. Publication bias
The main outcome of interest was the clinical, epidemiological, laboratory, and radiological characteristics of 2019-nCoV infected patients.
Publication bias was analyzed using Egger's linear regression test,
which measures funnel plot asymmetry.
2.4. Quality assessment
2.6. Statistical analysis
Quality evaluation of the included studies was performed using by
two authors (Marzieh Hashemian, Somayeh Karamollahi) independently, using an adapted version of the tool proposed by the
Newcastle-Ottawa assessment scale [6]. A score ranging from 0 to 9
points was attributed to each study (7 points: high quality, 4–6
All statistical analyses were performed using a random-effects model
with Stata/SE software, v.14.1 (StataCorp, College Station, TX). A chisquared test and I2 statistic were used to assess the inter-study heterogeneity. Hence, values above 75% are considered heterogeneity [7];
Table 1
Characteristics and Quality assessment of included studies.
ID
First Author, Year
Country
Study Design
Selection (4 points)
Comparability (2 points)
Outcome (3 points)
Total (9 points)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Guan W, 2020
Huang Y, 2020
Tang N, 2020
Cai s, 2020
Chen L, 2020
Feng K, 2020
Liu W, 2020
Chen C, 2020
Zhang L, 2020
Tian S, 2020
Bernheim S, 2020
Wu J, 2020
Peng YD 2020
Wang D 2020
Xu H–Y, 2020
Xia W, 2020
Yang W, 2020
Xiong Y,2020
Hu Z,2020
Zhang JJ,2020
Wang D,2020
Walker,2020
Liu K,2020
Yang X,2020
Wang X,2020
Chung M,2020
Li Q,2020
Ki M,2020
Chen N,2020
Fan BE,2020
Chang D,2020
Yao Y,2020
Cheng J,2020
Song F,2020
Zhou S,2020
Yueying P,2020
Liu C,2020
Shi H,2020
Zhao W,2020
Pan F,2020
Huang C,2020
Li YY,2020
Yang HY,2020
Zhu ZW,2020
Ai T,2020
Ling Y,2020
Lan L,2020
Sun,2020
Li J,2020
Xu,2020
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
China
Australia
China
China
China
China
China
Korea
China
China
China
China
China
China
China
China
China
China
China
China
Chine
China
China
China
China
China
China
USA
China
China
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
retrospective
Retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
retrospectively
3
3
1
3
3
3
3
2
2
3
3
2
3
3
3
3
2
3
3
2
3
1
3
2
3
3
3
2
2
3
3
2
2
3
3
4
3
3
3
3
3
3
2
3
3
3
3
2
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
2
2
2
2
2
2
3
2
2
2
2
2
2
2
2
2
2
2
2
3
2
2
2
2
2
2
2
1
2
2
2
2
3
3
3
3
2
1
1
3
3
2
2
2
2
2
2
2
1
2
2
2
2
1
1
1
8
7
5
7
7
7
7
6
6
7
7
6
7
8
7
7
6
7
7
6
7
3
7
6
7
7
8
7
7
8
7
5
5
8
8
7
7
7
7
7
7
7
3
7
7
7
7
5
6
6
2
2
2
2
2
2
2
3
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Table 2 (continued )
Characteristic
Value
(-CL,
þCL)
(0.84,
1.00)
(0.00,
1.00)
(0.01,
0.06)
(0.99,
1.00)
(0.10,
0.26)
(0.01,
0.08)
(0.82,
1.00)
(0.04,
0.94)
(0.67,
1.00)
(0.15,
0.96)
(0.88,
1.00)
(0.10,
0.18)
(0.04,
0.13)
(0.87,
1.00)
(0.02,
0.09)
(0.04,
0.45)
(0.26,
0.69)
(0.54,
0.87)
(0.85,
1.00)
(0.02,
0.09)
(0.04,
0.45)
(0.83,
1.00)
(0.00,
0.33)
(0.00,
0.97)
(0.88,
1.00)
(0.47,
0.59)
(0.18,
0.31)
(0.87,
1.00)
(0.12,
0.45)
(0.02,
0.08)
(0.71,
1.00)
I2
P
Positive
Table 2
Meta-analysis results.
Number
of
patients
Characteristic
Value
(-CL,
þCL)
I2
P
Positive
Number
of
patients
(0.51,
0.56)
(0.44,
0.49)
(0.15,
0.42)
68.34
0.00
4647
8815
68.34
0.00
4168
8815
95.94
0.00
328
1289
99.38
0.00
121
277
Epidemiology
Male
0.54
*
*
7
181
Female
0.46
*
*
190
190
0.27
*
*
17
99
*
*
5
128
93.22
0.00
440
475
99.24
0.00
254
479
Contact with another
person with
respiratory
symptoms
History of travel
from china
(Wuhan, and …)
Exposure to source of
transmission
Smoking history
95.57
0.00
313
368
Admission to ICU
0.16
99.00
0.00
276
461
Diabetes
0.11
94.23
0.00
382
399
Hypertension
0.19
*
*
34
248
Malignancy
0.05
*
*
11
128
Cardiovascular
0.12
96.48
0.00
559
599
Other comorbidity
0.16
*
*
16
99
COPD
0.03
94.02
0.00
72
298
96.21
0.00
211
599
Clinical symptoms
Fever
0.83
97.46
0.00
865
1159
Cough
0.59
92.38
0.00
514
541
Myalgia or fatigue
0.31
*
*
7
149
Sputum production
0.29
94.02
0.00
38
297
Headache
0.10
95.40
0.00
532
571
Hemoptysis
0.02
95.30
0.00
35
282
Diarrhea
0.08
99.44
0.00
177
420
Dyspnea
0.19
95.81
0.00
502
546
0.22
*
*
151
299
Acute respiratory
distress syndrome
(ARDS)
Vomiting
*
*
47
190
Sore throat
0.12
93.01
0.00
524
563
Rhinorrhea
0.09
93.13
0.00
83
436
Chest pain
0.11
0.00
0.79
14
279
96.86
0.00
528
608
Laboratory
WBC(Normal)
0.81
WBC (Decrease)
0.21
(0.18,
0.41)
84.10
0.00
135
449
WBC(Increase)
0.14
0.95
(0.72,
1.00)
97.02
0.00
321
370
Neutrophil (Normal)
0.95
(0.36,
0.95)
98.04
0.00
300
478
(0.73,
0.85)
*
Neutrophil
(Decrease)
Neutrophil
(Increase)
Albumin (Normal)
0.16
0.69
Albumin (Decrease)
0.54
Albumin (Increase)
0.03
Serum Creatinine
(Normal)
Serum Creatinine
(Decrease)
Serum Creatinine
(Increase)
D-Dimer (Normal)
1.00
0.17
0.03
0.94
D-Dimer (Increase)
0.48
Procalcitonin
(Normal)
Procalcitonin
(Increase)
Blood Urea nitrogen
(Normal)
Blood Urea nitrogen
(Decrease)
Blood Urea nitrogen
(Increase)
Thromboplastin time
(Normal)
Thromboplastin time
(Decrease)
Thromboplastin time
(Increase)
C-reactive protein
(Normal)
C-reactive protein
(Increase)
Total Bilirubin
(Normal)
Total Bilirubin
(Decrease)
Total Bilirubin
(Increase)
Prothrombin time
(Normal)
Prothrombin time
(Decrease)
Prothrombin time
(Increase)
Creatinine (Normal)
0.88
0.60
0.98
0.14
0.08
0.98
0.05
0.20
0.48
0.72
0.95
0.05
0.20
0.95
0.10
0.44
0.98
Creatinine
(Decrease)
Creatinine (Increase)
0.53
Platelet count
(Normal)
Platelet count
(Decrease)
Platelet count
(Increase)
Aspartate
Aminotransferase
(Normal)
Aspartate
Aminotransferase
(Increase)
Lactate
Dehydrogenase
(Normal)
Lactate
Dehydrogenase
(Increase)
0.96
0.24
0.27
0.05
0.90
0.29
0.80
*
126
177
0.58
(0.41,
0.73)
99.02
0.00
1917
4208
0.30
(0.16,
0.45)
(0.00,
0.53)
(0.08,
0.27)
(0.08,
0.14)
(0.12,
0.27)
(0.02,
0.08)
(0.06,
0.20)
(0.11,
0.22)
(0.01,
0.06)
98.51
0.00
719
3583
99.18
0.00
1001
1559
94.70
0.00
175
1843
68.64
0.00
250
2505
94.35
0.00
484
2403
82.12
0.00
72
2250
95.16
0.00
207
2301
75.84
0.00
598
2897
75.84
0.00
48
1900
(0.77,
0.89)
(0.48,
0.69)
(0.23,
0.39)
(0.21,
0.39)
(0.06,
0.14)
(0.00,
0.05)
(0.06,
0.11)
(0.12,
0.26)
(0.00,
0.60)
95.15
0.00
3273
4370
97.33
0.00
2100
4308
94.28
0.00
1051
3029
84.96
0.00
478
1497
70.94
0.00
306
3557
70.94
0.00
21
1370
80.05
0.00
203
3690
93.99
0.00
495
2651
96.19
0.00
49
173
(0.02,
0.05)
(0.07,
0.18)
(0.03,
0.17)
(0.04,
0.21)
65.12
0.00
105
2961
91.85
0.00
287
2996
87.72
0.00
64
1455
95.44
0.00
108
1834
(0.69,
0.91)
(0.16,
0.27)
(0.08,
0.21)
(0.87,
1.00)
(0.12,
0.21)
(0.05,
0.34)
95.56
0.00
958
1260
70.65
0.00
180
785
84.85
0.00
109
760
93.15
0.00
721
797
*
*
39
229
92.34
0.00
67
380
86.35
0.00
243
259
0.17
0.03
0.17
0.95
(continued on next page)
4
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Table 2 (continued )
Characteristic
Erythrocyte
Sedimentation
rate (Increase)
Alanine
Aminotransferase
(Normal)
Alanine
Aminotransferase
(Decrease)
Alanine
Aminotransferase
(Increase)
Creatine kinase
(Normal)
Creatine kinase
(Decrease)
Creatine kinase
(Increase)
Lymphocyte
(Normal)
Lymphocyte
(Decrease)
Lymphocyte
(Increase)
Hemoglobin
(Normal)
Hemoglobin
(Decrease)
Radiology
Multiple mottling
and ground-glass
opacity
Bilateral patchy
shadowing
Crazy paving
Table 2 (continued )
Value
0.90
(-CL,
þCL)
I2
P
92.20
(0.00,
0.05)
*
0.18
(0.12,
0.25)
54.18
0.00
65
358
0.94
(0.81,
1.00)
(0.12,
0.22)
(0.03,
0.24)
(0.46,
0.75)
(0.40,
0.75)
(0.06,
0.24)
(0.98,
1.00)
(0.95,
1.00)
93.92
0.00
427
467
*
*
42
248
85.74
0.00
32
320
93.25
0.00
385
701
97.86
0.00
826
1431
0.00
0.00
9
63
*
*
69
69
*
*
162
179
0.17
0.12
0.61
0.58
0.14
1.00
0.98
*
459
2
149
95.37
0.00
1399
2951
0.50
(0.44,
0.57)
(0.06,
0.29)
(0.00,
0.30)
(0.45,
0.75)
(0.45,
0.75)
(0.34,
0.39)
(0.24,
0.51)
(0.00,
0.02)
(0.00,
0.05)
(0.59,
0.79)
(0.00,
0.05)
(0.11,
0.15)
(0.04,
0.13)
(0.02,
0.09)
40.60
0.17
592
1257
85.09
0.00
47
324
93.19
0.00
15
305
91.16
0.00
327
517
91.16
0.00
61
249
*
*
411
1114
94.74
0.00
650
1594
4
141
0.10
Peripheral
distribution
Unilateral
Pneumonia
Local patchy
shadowing
Consolidation
0.61
0.61
0.36
0.37
Cavitation
0.00
Lymphadenopathy
0.02
Bilateral pneumonia
0.70
Pneumothorax
0.01
Interstitial
abnormalities
Linear
0.13
Pleural effusion
0.05
Supportive treatment
Antiviral therapy
0.90
Antibiotic therapy
0.68
Use of corticosteroid
0.32
Immunotherapy
0.39
Oxygen support
0.56
Non-invasive
ventilation or
0.11
0.08
(0.74,
0.99)
(0.49,
0.84)
(0.19,
0.47)
(0.13,
0.69)
(0.32,
0.78)
(0.05,
0.19)
Continuous renal
replacement
therapy
Clinical outcomes
Recovered
Staying in hospital
Death
Value
(-CL,
þCL)
I2
P
Positive
Number
of
patients
0.08
(0.01,
0.19)
(0.00,
0.05)
96.06
0.00
88
1643
71.69
0.00
15
576
97.00
0.00
218
339
79.86
0.00
23
361
788
1791
151
2952
2355
3054
0.02
0.55
0.06
0.53
0.67
0.05
(0.24,
0.84)
(0.01,
0.13)
98.63
97.93
89.08
0.00
0.00
0.00
Thus, DerSimonian and Laird random effects models were used [8]. All
statistical interpretations were reported on a 95% confidence interval
(CI) basis.
3. Results
(0.50,
0.70)
Discrete nodules
high-flow nasal
canula
Invasive mechanical
ventilation
Invasive mechanical
ventilation and
ECMO
Nasal cannula
500
0.60
0.16
Characteristic
Number
of
patients
(0.77,
0.98)
0.01
0.00
Positive
3.1. Search results
We evaluated 5 electronic databases and categorized 2095 articles
published until 10 March 2020 (Fig. 1). Of these, after initial screening of
the title and abstract, 1795 articles were excluded due to their irrelevance and duplication and the full text of remaining 300 articles were
reviewed (Fig. 1). Among the 250 articles, were excluded again for
specific reasons: case reports, conference papers, repeat articles, letters,
editorials, expert opinions, animal, in vitro studies, and unusable data
sets. Finally, 50 studies were included in this systematic review and metaanalysis. Supplementary data 1 depicts the main characteristics of 50
included studies.
3.2. Characteristics of studies
A total of 50 articles were included in this meta-analysis [2,4,5,9–20],
[21–30, 31–55] including data from 8815 patients. Study size ranged
from 4 to 1719 subjects. The methodological quality of the included
studies was high for observational studies (Table 1). The highest quality
of the literature was 8 stars and the lowest 3 stars.
59.24
0.02
18
523
90.99
0.00
1330
1644
*
*
1
99
*
*
143
1099
*
*
12
142
69.66
0.00
39
615
3.4. Epidemiological characteristics
98.61
0.00
1374
2205
97.80
0.00
1094
1806
96.97
0.00
498
2028
98.92
0.00
428
1674
98.95
0.00
1003
2141
93.91
0.00
163
1858
A total of 50 studies including 8815 patients were included in this
study, the mean age was 46 years and 4647 (0.54%) were male. Among
studies been reported that data on the epidemiological characteristics,
evidence of heterogeneity was present in the history contact with another
person with respiratory symptoms (I2 ¼ 95.94, P ¼ 0.00), history of
travel from China (Wuhan) (I2 ¼ 99.02, P ¼ 0.00), exposure to source of
transmission (COVID-19 infected patients, wildlife) within 14 days
(I2 ¼ 98.51, P ¼ 0.00), admission to ICU (I2 ¼ 94.70, P ¼ 0.00), smoking
history (current or past) (I2 ¼ 99.18, P ¼ 0.00) (Table 2). Among eligible
literatures, 26 studies reported that hypertension, diabetes, and cardiovascular illness were more prevalent in patients. Detailed results of Metaanalysis are shown in Table 2.
3.3. Publication bias detection
The results of the Egger test are displayed in Table 3. There was a
publication bias in the meta-analysis of the bilateral pneumonia group
(P ¼ 0.004).
5
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Table 3
Results of Egger test.
Group
Fever
Cough
Myalgia or
fatigue
Acute respiratory distress
syndrome
Death
COPD
Multiple mottling and groundglass opacity
Bilateral patchy
shadowing
Bilateral
pneumonia
P
0.103
0.054
0.592
0.868
0.197
0.127
0.155
0.238
0.004
There were 13 symptoms of 2019-nCoV in infected patients which
were reported. Among studies been reported that data on the clinical
symptoms, evidence of heterogeneity was present in the symptoms of
fever (I2 ¼ 95.15, P ¼ 0.00), cough (I2 ¼ 97.33, P ¼ 0.00), myalgia or
fatigue (I2 ¼ 94.28, P ¼ 0.00), sputum production (I2 ¼ 84.96, P ¼ 0.00),
headache or hemoptysis (I2 ¼ 70.94, P ¼ 0.00), and diarrhea (I2 ¼ 80.05,
P ¼ 0.00) (Table 2). Among been reported clinical symptoms, the pooled
incidence rate was calculated for four symptoms: acute respiratory
distress syndrome (ARDS) (22%, 95% CI: 0.00, 0.60), dyspnea (19%,
95% CI: 0.12, 0.26), sore throat (12%, 95% CI: 0.07, 0.18), chest pain
(11%, 95% CI: 0.04, 0.21), rhinorrhea (9%, 95% CI: 0.03, 0.17), vomiting
(3%, 95% CI: 0.02, 0.05) (Table 2).
with antiviral and antimicrobial agents (the pooled incidence rates and
heterogeneities were 90%; 68%, I2 ¼ 98.61; 97.80). The pooled incidence
rates were 32% and 39% in use of corticosteroids and immunotherapy.
Totally, 1510 patients used oxygen therapy. Among these studies, there
were 218 patients who used nasal cannula, the pooled incidence was
55% (95% CI: 0.24, 0.84) for five studies. 11% (95% CI: 0.32, 0.78)
patients used non-invasive ventilation or high-flow nasal cannula.
Additionally, 88 and 15 patients were treated with invasive mechanical
ventilation and invasive mechanical ventilation or extra-corporeal
membrane oxygenation (ECMO), the pooled incidence were 8% and
2% (Table 2). Three articles had no detailed data on oxygen therapy [12,
55]. There were 23 patients who used continuous renal replacement
therapy, the pooled incidence was 6% (95% CI: 0.01, 0.13) for five
studies.
3.6. Laboratory characteristics
3.9. Clinical outcomes
Among been reported laboratory characteristics, white blood cells
were decreased in 180 patients (the pooled incidence rate was 21%, I2 ¼
70.65, P ¼ 0.00) and increased in 109 patients (the pooled incidence rate
was 14%, I2 ¼ 84.85, P ¼ 0.00) (Table 3). Lymphocyte were decreased in
826 patients (the pooled incidence rate was 58%, I2 ¼ 97.86, P ¼ 0.00) and
increased in 9 patients (the pooled incidence rate was 14%, I2 ¼ 0.00, P ¼
0.00) (Table 2). The increased neutrophils observed in 67 patients, evidence
of heterogeneity was present in it (I2 ¼ 92.34%, P ¼ 0.00). Albumin were
decreased in 121 patients (the pooled incidence rate was 54%, I2 ¼ 99.38, P
¼ 0.00). The D-Dimer and thromboplastin time were increased in 254
and 72 patients (the pooled incidence rates were 48%; 20%, I2 ¼ 99.24;
94.02, P ¼ 0.00). Procalcitonin, C-reactive protein, alanine aminotransferase, aspartate aminotransferase, Lactate Dehydrogenase and
creatine kinase were increased in 276, 865, 65, 135, 300 and 32 patients
(the pooled incidence rates were 60%, 72%, 18%, 29%, 69% and 12%, P ¼
0.00) (Table 3). Prothrombin time were decreased in 35 patients (the
pooled incidence rate was 10%, I2 ¼ 95.30, P ¼ 0.00) and increased in
177 patients (the pooled incidence rate was 44%, I2 ¼ 99.44, P ¼ 0.00)
(Table 2).
Among been reported clinical outcomes, unfortunately, 151 died
cases were reported, the pooled incidence of mortality was 53% with
significant heterogeneity (I2 ¼ 89.08%, P ¼ 0.00). Subsequently the
course of treatment of patients is about several weeks until some articles
published, some patients still staying in the hospital, the statistics on
mortality may be inaccurate. Incidence rate correlation is shown in
Table 4. In addition, 1791 and 788 cases were reported as staying in
hospital and recovered with significant heterogeneity (I2 ¼ 97.93%;
98.63, P ¼ 0.00) (Table 2).
Pooled incidence rate for characters is shown in Fig. 2.
3.5. Clinical characteristics
4. Discussion
2019-nCoV is one type of coronaviruses are enveloped nonsegmented positive-sense RNA viruses belonging to the β-coronavirus
cluster like SARS and Middle East respiratory syndrome (MERS) and
now it had diseased more than half millions of people worldwide [12,
13,55,56]. It is assumed that 2019-nCoV to be a recombinant virus
between bat coronavirus and coronavirus of another unknown origin
[57]. Up to now, unfortunately, there is no detailed and precise
treatments presented for 2019-nCoV. Symptomatic and supportive
treatment is the basis of therapy for patients infected by 2019-nCoV.
Our meta-analysis was based on data from 50 retrospective studies
in 8815 patients of 2019-nCoV. The Most of the cases were from
hospitals in China. Several clinical predictors of mortality were found
including increased age, male sex and underlying illness, including
hypertension, diabetes, renal disease, heart disease and respiratory
disease. In our meta-analysis, the frequency of males more than females (52.7% vs 47.3%). The similar findings with the gender distribution have been reported in MERS and SARS [13,15]. It may be
related to the occupational risk factors for males [4]. There are some
possible reasons in the reduced susceptibility of females to 2019-nCoV
such as Gender-specific effects and X chromosome in infectious disease
susceptibility, and their more strong immune responses [58,59].
Although, a recent study that revealed there was no divergence with
the gender distribution of males and females between ICU patients and
3.7. Radiological characteristics
The radiological characteristics of 2019-nCoV infected patients were
described differently. By reviewing the literature, there are different
common manifestations as follows: multiple mottling and ground-glass
opacity, bilateral pneumonia, consolidation, and bilateral or local patchy shadowing. Among been reported radiological characteristics, evidence of heterogeneity were reported in the multiple mottling and
ground-glass opacity (60%, I2 ¼ 95.37, P ¼ 0.00), bilateral pneumonia
(70%, I2 ¼ 90.99, P ¼ 0.00), consolidation (37%, I2 ¼ 94.74, P ¼ 0.00),
and bilateral patchy shadowing (50%, I2 ¼ 40.60, P ¼ 0.17). Additionally, pneumothorax happened in one patient [13].
3.8. Treatment
Among been reported treatment, 1374, 1094 patients were treated
6
11
8
0.0004
***
Yes
0.0027
**
Yes
0.0311
*
Yes
7
19
0.56
0.0002
***
Yes
0.8801
0.5938 to
0.9686
0.7747
0.8951
0.5158 to
0.9810
0.8012
0.7989
0.1152 to
0.9690
0.6383
8
20
30
35
0.0228
*
Yes
0.02
*
Yes
0.0411
*
Yes
0.0003
***
Yes
0.6065
0.3345
0.5784
0.3037 to 0.7643
0.3752
0.01724 to
0.6479
0.1408
0.5155
0.09454 to
0.7801
0.2657
0.7788
0.9578 to
0.1643
0.7483
0.4456 to 0.8975
non-ICU patients [34]. However, we suggest that more investigations
are required in order to identify potential risk factors, their relation to
different populations, and their mechanisms involved. Older adults
and severe patients with comorbidities are as high-risk group to
2019-nCoV [45]. A study performed on influenza illness demonstrated
the higher risk of mortality for severe patients with chronic obstructive pulmonary disease (COPD) (OR 1.49, 95% CI: 1.10–2.01), cardiovascular disease (OR 2.92, 95% CI: 1.76–4.86), hypertension (OR
1.49, 95% CI: 1.10–2.10) [60]. The comorbidities effect had also been
observed to have similar effects in 2019-nCoV and MERS [61]. Age
and comorbidities are major predictors of numerous adverse outcomes
in SARS [62]. SARS cases were mostly occurred in younger people;
while half of the cases of MERS infection seen in people older than
50 years [63]. Compared with SARS patients, comorbidities, such as
diabetes, hypertension, chronic heart disease and chronic pulmonary
disease, were more common in MERS cases [64]. Based on to the
outcomes of meta-analysis, incidence rates of clinical characteristic
includes fever, cough, myalgia or fatigue, and sputum production were
83, 59, 31, and 29% respectively. The incidence of ARDS was 22%,
and the case mortality rate of patients with 2019-nCoV infection was
5% which is lower than to SARS and MERS [65]. Several reports
propose that pulmonary fibrosis will become one of the severe problems in cases with 2019-nCoV infection [66–68]. How to stop and
decrease the incidence of pulmonary fibrosis in cases with 2019-nCoV
infection are crucial complications in the treatment of 2019-nCoV
[66–68]. Additionally, we observed that hemoptysis, vomiting, diarrhea rhinorrhea, headache chest pain and sore throat are less than
occurred in patients with 2019-nCoV. Air-space opacities (unilateral
focal and both unilateral multifocal or bilateral involvement) are the
key radiological characters in SARS cases [69,70]. Although,
ground–glass opacities and consolidation were the most frequent
radiological characters in MERS patients [71,72]. Guan W and colleagues [17] observed that the frequent radiographic features were
ground-glass opacity (50%) and bilateral patchy shadowing (46%) in
1099 cases with 2019-nCoV infection. Huang C and colleagues [4]
reported that the normal radiographic feature of severe patients with
2019-nCoV were bilateral multiple lobular and subsegmental areas of
consolidation. The pooled incidences of the bilateral pneumonia
multiple mottling and ground-glass opacity bilateral patchy shadowing
and consolidation were 70%, 60%, 50%, and 37%. Based on the laboratory characters, the pooled incidence rate of lymphocytes decrease
and increase were 58% and 14%. Otherwise, the pooled incidence rate
of increasing and decreasing Neutrophils was 17% and 16%. These
defects are comparable to those previously detected in cases with
MERS and SARS infection [73]. These outcomes more endorse that
lymphocytes decrease along with increasing neutrophils was a characteristic of SARS, and 2019-nCoV might primarily effect on lymphocytes, especially T lymphocytes [74]. Additionally, the
administration of glucocorticosteroids cause immunosuppression,
decreasing the function and/or numbers of lymphocytes, and
deregulated lymphocyte responses. Therefore, treatment with glucocorticoids difficult the concern about Lymphopenia [75]. On the other
hand, immune insufficiency may be also a risk factor for poor outcome
in patients with 2019-nCoV. Currently, outcomes on the death of
2019-nCoV are varying. The recent four reports include 138, 41, 507
and 41 cases, the mortality was 4.3%, 15%, 7.9% and 14.6% respectively [4,34,52,56]. However, the mortality rates of SARS (10%) and
MERS (35%) are higher than to 2019-nCoV [76]. In our meta-analysis,
the pooled incidence death was 5% respectively. Although, this result
higher than the death reported by the previous reports [52,56]. The
cause for this occurrence may be related with the absence of identifying information on data, and also deficient data on diagnosis approaches and treatment practices about 2019-nCoV. However, there
were also some limitations of our meta-analysis: (1) all reports
included had retrospective designed with high statistic heterogeneity
(large variation in the sample size among studies; (2) often cases in
0.03390
0.2882
0.0391
*
Yes
15
0.5376
0.2383 to
0.7437
0.289
0.0013
**
Yes
33
r
95% confidence
interval
R squared
P value
P (two-tailed)
P value summary
Significant?
(alpha ¼ 0.05)
Number of XY Pairs
0.5368
0.8228 to
Death vs. Fever
(37⋅3 C) or (38 C)
Death vs.
Age mean
Death vs. History of travel
from china (Wuhan and …)
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Pearson r
Table 4
Summary of Pearson Correlation Coefficient Values between deaths with other variable.
Death vs.
Cough
Death vs.
Diarrhea
Death vs. thromboplastin
time (Increase)
Death vs.
lymphocyte
(Normal)
Death vs.
Cavitation
Death vs.
Linear
Death vs.
Antiviral
therapy
E. Kouhsari et al.
7
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Fig. 2. Pooled incidence rate for characters in the study.
8
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Fig. 2. (continued).
9
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Fig. 2. (continued).
still requisite to be warranted by more careful design, larger sample
size multivariate studies to corroborate the results of this
meta-analysis.
this meta-analysis are Chinese; (3) large variation in lengths of
follow-up led to some cases may be still stating in hospital in the
included studies. In conclusion, the outcomes of our systemic review
and meta-analysis provide a quantitative pooled incidence rate of
clinical, epidemiological, laboratory, and radiological features of
2019-nCoV and has great potential to develop diagnosis and patient's
stratification in 2019-nCoV. However, this conclusions of this study
Source(s) of support
None.
10
E. Kouhsari et al.
Indian Journal of Medical Microbiology xxx (xxxx) xxx
Declaration of competing interest
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The authors declare that there are no conflict of interests.
Acknowledgements
We thank the health workers, nurses, clinical staff and all the people
who fight with 2019-nCoV.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://
doi.org/10.1016/j.ijmmb.2020.10.004.
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