Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
Department of Neurology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
Correspondence
Sahar Dalvand, Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Correspondence
Sahar Dalvand, Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
Department of Neurology, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
Correspondence
Sahar Dalvand, Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Correspondence
Sahar Dalvand, Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Abstract
Background
At the end of December 2019, a novel respiratory infection, initially reported in China, known as COVID-19 initially reported in China, and later known as COVID-19, led to a global pandemic. Despite many studies reporting respiratory infections as the primary manifestations of this illness, an increasing number of investigations have focused on the central nervous system (CNS) manifestations in COVID-19. In this study, we aimed to evaluate the CNS presentations in COVID-19 patients in an attempt to identify the common CNS features and provide a better overview to tackle this new pandemic.
Methods
In this systematic review and meta-analysis, we searched PubMed, Web of Science, Ovid, EMBASE, Scopus, and Google Scholar. Included studies were publications that reported the CNS features between 1 January 2020 and 20 April 2020. The data of selected studies were screened and extracted independently by four reviewers. Extracted data analyzed by using STATA statistical software. The study protocol registered with PROSPERO (CRD42020184456).
Results
Of 2,353 retrieved studies, we selected 64 studies with 11,687 patients after screening. Most of the studies were conducted in China (58 studies). The most common CNS symptom of COVID-19 was headache (8.69%, 95%CI: 6.76%–10.82%), dizziness (5.94%, 95%CI: 3.66%–8.22%), and impaired consciousness (1.90%, 95%CI: 1.0%–2.79%).
Conclusions
The growing number of studies has reported COVID-19, CNS presentations as remarkable manifestations that happen. Hence, understanding the CNS characteristics of COVID-19 can help us for better diagnosis and ultimately prevention of worse outcomes.
1 INTRODUCTION
At the end of December 2019, a novel respiratory syndrome, known as COVID-19, was reported in Wuhan city, Hubei province, China. The first sign of this infection (2019-nCoV, COVID-19) was pneumonia (Adhikari et al., 2020; WHO, 2020; Shi, Qin, et al., 2020; Velavan & Meyer, 2020; Wang, Hu, et al., 2020; Wang, Wang, et al., 2020; Wu, Chen, et al., 2020). This new pandemic rapidly spread worldwide, and an increasing number of infected cases and deaths have been reported globally (Jiang et al., 2020; Sohrabi et al., 2020). Hence, the COVID-19 outbreak was officially considered as a Public Health Emergency of International Concern (PHEIC) by the World Health Organization (WHO) Emergency Committee (Mackenzie & Smith, 2020; WHO, 2020). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a zoonotic pathogen and can transmit from infected animals (such as bats and snakes) to humans eventually leading to epidemics and pandemics through human-to-human transmission (Hassan et al., 2020; Mackenzie & Smith, 2020). Most cases of COVID-19 have shown respiratory symptoms ranging from cough to dyspnea and respiratory failure as well as the typical signs and symptoms of infection such as fever and fatigue (Cascella et al., 2020; Chen, Zhou, et al., 2020; Wang, Hu, et al., 2020; Young et al., 2020).
However, a growing number of COVID-19 patients are presenting with different combinations of the central nervous system (CNS) manifestations (Asadi-Pooya & Simani, 2020; Mao et al., 2020; Montalvan et al., 2020). Several case reports have indicated the presence of various CNS complications, including encephalitis, stroke, meningitis, and encephalopathy in COVID-19 patients (Co et al., 2020; Filatov et al., 2020; Moriguchi et al., 2020; Zhou, Zhang, et al., 2020). Furthermore, a large observational study carried out by Mao et al. shows the prevalence of the CNS presentations such as dizziness, headache, impaired consciousness, acute cerebrovascular disease, ataxia, and seizure (Mao et al., 2020). Therefore, awareness of the different aspects of the short- and long-term effects of this virus on the central nervous system could decently guide scientists. In this systematic review and meta-analysis, we assessed the CNS manifestations in COVID-19 cases.
2 METHOD
2.1 Search strategy and selection criteria
We performed this systematic review and meta-analysis based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2009), and our study protocol is submitted to PROSPERO (ID: CRD42020184456). We systematically searched six databases including Google Scholar, Scopus, PubMed, Web of science, Ovid, and EMBASE for all published articles from 1 January 2020 until 20 April 2020 using the following Medical Subject Heading terms (MESH terms):
(“Wuhan coronavirus” OR “Wuhan seafood market pneumonia virus” OR “COVID19 virus” OR “COVID-19 virus” OR “coronavirus disease 2019 virus” OR “SARS-CoV-2” OR “SARS2” OR “2019-nCoV” OR “2019 novel coronavirus” OR “2019-nCoV infection” OR “2019 novel coronavirus disease” OR “2019-nCoV disease” OR “coronavirus disease-19” OR “coronavirus disease 2019” OR “2019 novel coronavirus infection” OR “COVID19” OR “COVID-19” OR “severe acute respiratory syndrome coronavirus 2” OR “coronavirus*”) AND (“Manifestation, Neurologic” OR “Neurological Manifestations” OR “Neurologic Manifestation” OR “Neurological Manifestation” OR “Neurologic Symptom” OR “CNS” OR “brain” OR “neuro*” OR “headache” OR “dizziness” OR “ataxia” OR “epilepsy” OR “seizure” OR “migraine*” OR “CSF” OR “Cerebrospinal Fluids” OR “Fluid, Cerebrospinal” OR “Fluids, Cerebrospinal” OR “Cerebro Spinal Fluid” OR “Cerebro Spinal Fluids” OR “Fluid, Cerebro Spinal” OR “Fluids, Cerebro Spinal” OR “Spinal Fluid, Cerebro” OR “Spinal Fluids, Cerebro” OR “stroke” OR “vertigo” OR “consciousness” OR “Impaired consciousness” OR “coma” OR “cerebrovascular disease” OR “acute cerebrovascular disease” OR “encephalitis”) alone or in combination with OR and AND operators.
After removing the duplicated records, articles were screened based on their titles and abstracts by two authors (S.S and M.H) independently. The full texts of eligible publications were examined for inclusion and exclusion criteria (A.AJ, S.M, S.S, and M.H). Observational studies reported at least one of the related CNS symptoms in COVID-19 patients without any language, race, country, and gender limitations included for quantitative synthesis. The preprint studies, interventional studies, systematic reviews, case reports, conferences, commentaries, letters, editorial, author responses, correspondence articles, in vitro, animal studies, children population, articles without full text, or unreliable data were excluded. In addition, the reference list of the eligible studies was searched to prevent missing publication and include all related literature. The data were independently extracted (A.AJ. S.M, S.S, S.S, and M.H), and discrepancies were resolved with discussion and consensus by three independent researchers (SH.N, S.D, and F.A).
2.2 Data analysis and quality assessment
The desired data were recorded using an excel spreadsheet form that included the title, first author, year and month of publication, type of study, country, total sample size, the sample size of male and female, study design, demographic characteristics, exposure history, clinical manifestation, CNS symptoms, and any reported comorbidity.
We assessed the quality of included studies (A.AJ. S.M, S.S, S.S, and M.H), based on the NIH quality assessment tool for observational cohort and case series studies (NIH). This instrument assessed the quality of included studies based on the research question, study population, the participation rate of eligible persons, inclusion and exclusion criteria, sample size justification, analyses, reasonable timeframe, exposure, outcome measures, outcome assessors, and loss to follow-up.
2.3 Meta-analysis
Data from included studies were extracted for the number of events and total patients to perform a meta-analysis (S.D). Cochrane's Q test and the I2 index were used to assess heterogeneity among selected studies. Heterogeneity was categorized as low (below 25%), moderate (25%–75%), and high (above 75%) (Higgins & Thompson, 2002). Also, data adjusted by Freeman–Tukey double arcsine transformation and their 95% CIs were calculated by the Clopper–Pearson method (Clopper & Pearson, 1934). We calculate mean and standard deviations from median and quartiles by using Wan method (Wan et al., 2014). For continuous data, we estimate pooled results of means and their respective 95% CI by the inverse variance method. All analyses were performed using STATA statistical software, version 13 (StataCorp).
3 RESULTS
As illustrated in (Figure 1), a total of 2,353 studies were retrieved after a systematic search in the aforementioned databases. After removing duplicates, 1,760 studies remained. Then, we narrowed the studies to 203 articles by screening with titles and abstracts. In full-text screening, 45 studies with no reliable or useful data, 24 review articles, 41 preprints, 6 case reports, 1 case controls, 4 reports, 4 papers with specific children population, one study with specific pregnant population, and 13 publications such as Commentary, editorial or Correspondence letters were excluded. Finally, 64 studies (Barrasa et al., 2020; Chen, Chen, et al., 2020; Chen, Qi, et al., 2020; Chen, Wu, et al., 2020; Chen, Yan, et al., 2020; Chen, Yang, et al., 2020; Chen, Zhou, et al., 2020; Cheng et al., 2020; Ding et al., 2020; Du, Liu, et al., 2020; Du, Tu, et al., 2020; Feng et al., 2020; Guan et al., 2020; Guo et al., 2020; Gupta et al., 2020; Han et al., 2020; Hsih et al., 2020; Huang et al., 2020; Jia et al., 2020; Jin et al., 2020; Kim et al., 2020; Kong et al., 2020; Lei, Huang, et al., 2020; Lei, Jiang, et al., 2020b; Li, Wang, et al., 2020; Liang et al., 2020; Ling et al., 2020; Liu, Yang, et al., 2020; Liu, Yang, et al., 2020; Liu, Yang, et al., 2020; Lo et al., 2020; Mao et al., 2020; Mi et al., 2020; Mo et al., 2020; Moein et al., 2020; Peng, Liu, et al., 2020; Peng, Meng, et al., 2020; Qian et al., 2020; Qin et al., 2020; Shao et al., 2020; Shi, Han, et al., 2020; Shi, Qin, et al., 2020; Song et al., 2020; Sun et al., 2020; Tan et al., 2020; Tian et al., 2020; Wan, Xiang, et al., 2020; Wan, Yi, et al., 2020; Wang, Hu, et al., 2020; Wang, He, et al., 2020; Wang, Fang, et al., 2020; Wu, Chen, et al., 2020; Wu, Wu, et al., 2020; Xu et al., 2020; Yang, Cao, et al., 2020; Yang, Yu, et al., 2020; Yu et al., 2020; Zhang, Cai, et al., 2020; Zhang, Wang, et al., 2020; Zhao et al., 2020; Zheng, Tang, et al., 2020; Zheng, Xu, et al., 2020; Zhong et al., 2020; Zhu et al., 2020) including 11,282 COVID-19 patients, met our inclusion criteria, and were entered in meta-analysis. The main characteristics of our included studies are presented in Table 1.
The total sample size of eligible studies was 11,687, including 5,568 females and 6,114 males. The mean age for noncritical patients was 48.557 (95% CI: 44.816%–52.299%) and for critical patients was 58.965 (95% CI: 55.792%–62.139%). As shown in Table 2, the proportion of patients with travel history to Wuhan, Wuhan-related exposure, and Living in Wuhan was 51.15%, 78.52%, and 47.46%, respectively. In addition, the proportion of patients with travel history to other infected areas and contact with patients was 52.21% and 34.65%, respectively. Mortality was assessed in 25 studies with a pooled incidence rate of 10.47%. The incidence rate of positive females and males was 46.42% (95% CI: 43.01%–49.83%) and 49.50% (95% CI: 45.70%–53.31%), respectively. 36.17% (95% CI: 27.91%–44.84%) of infected patients were in the severe, critical, or intensive care unit condition. In addition, the incidence rate of mortality and survival was 10.47% (95% CI: 5.08%–17.33%) and 81.43% (95% CI: 65.75%–93.29%), respectively.
TABLE 2.
Positive PCR, severity, mortality, and exposure history of COVID-19-infected patients having CNS symptoms
Variables
No of studies
Total sample size
No positive case
Incidence rate (95% CI)
Heterogeneity
I2 (%)
Q
p-Value
Positive female
60
11,425
5,363
0.4642 (0.4301–0.4983)
92.2
752.6
<.0001
Positive male
60
11,425
5,919
0.4950 (0.4570–0.5331)
93.8
957.8
<.0001
Severe or critical or ICU
40
9,821
2,611
0.3617 (0.2791–0.4484)
98.6
2,827.4
<.0001
Nonsevere or Noncritical or Non-ICU
37
8,095
5,694
0.7061 (0.6229–0.7832)
98.3
2,154.0
<.0001
Mortality
25
7,087
556
0.1047 (0.0508–0.1733)
98.4
1,497.6
<.0001
Survival
18
3,174
2,585
0.8143 (0.6575–0.9329)
98.9
1,600.9
<.0001
Exposure history
Travel history to Wuhan
27
6,476
3,434
0.5115 (0.3295–0.6920)
99.5
5,434.9
<.0001
Wuhan-related exposure
2
567
433
0.7852 (0.7501–0.8183)
–
–
–
Living in Wuhan
2
1,151
535
0.4746 (0.4455–0.5037)
–
–
–
Travel history to other infected areas
3
255
133
0.5221 (0.4609–0.5832)
0.0
1.1
.5664
Contact with patients
19
4,422
1504
0.3465 (0.2976–0.3953)
90.1
181.2
<.0001
Family clustering
6
1,182
254
0.2044 (0.1376–0.2712)
84.9
33.1
<.0001
Unknown exposure history
6
472
63
0.1244 (0.0446–0.2042)
91.3
57.7
<.0001
Based on the results shown in Table 3 and Figure 2, the most common manifestations were fever 79.39% (95% CI: 73.94%–84.37%), cough 54.77% (95%CI: 49.10%–60.38%), fatigue 32.39% (95% CI: 26.78%–38.0%), dyspnea 28.47% (95% CI: 21.49%–35.99%), chest tightness 23.83% (95% CI: 17.84%–29.82%), and shortness of breath 20.42% (95% CI: 13.28%–28.85%). The highest incidence rate among CNS symptoms of COVID-19 patients was for headache (8.69% with 95% CI: 6.76%–10.82%), followed by dizziness (5.94%, 95%CI: 3.66%–8.22%), and impaired consciousness (1.90% with 95% CI: 1.0%–2.79%).
TABLE 3.
Clinical Manifestations in COVID-19-infected patients presenting CNS symptoms
Variables
No of studies
Total sample size
No of positive case
Incidence rate (95% CI)
Heterogeneity
I2 (%)
Q
p-Value
General symptoms
Fever
63
11,537
8,723
0.7939 (0.7394–0.8437)
97.7
2,689.5
<.0001
Fatigue
43
8,638
2,454
0.3239 (0.2678–0.3800)
97.8
1936.5
<.0001
Myalgia (muscle pain or muscle injury)
41
7,479
246
0.1395 (0.1169–0.1621)
88.2
338.4
<.0001
Nasal congestion
3
2,684
151
0.0554 (0.0428–0.0680)
51.2
4.1
.1290
Rhinorrhea
15
3,881
163
0.0447 (0.0258–0.0676)
83.9
87.2
<.0001
Dry cough or cough
62
11,507
6,047
0.5477 (0.4910–0.6038)
97.0
2054.7
<.0001
Arthralgia
3
204
8
0.0243 (0.000–0.0785)
63.6
5.5
.0642
Chill
11
3,878
512
0.1802 (0.0834–0.3021)
98.4
637.1
<.0001
GI symptoms
6
1,795
83
0.0501 (0.0148–0.0854)
87.7
40.8
<.0001
Nausea
11
1,934
115
0.0595 (0.0387–0.0803)
69.0
32.3
.0004
Vomiting
11
2,703
97
0.0322 (0.0255–0.0397)
23.6
13.1
.2183
Nausea and/or vomiting
13
3,160
181
0.0518 (0.0337–0.0700)
79.7
59.2
<.0001
Anorexia or inappetence
17
2,638
588
0.2052 (0.1393–0.2711)
96.8
508.7
<.0001
Diarrhea
45
8,270
909
0.1030 (0.0832–0.1227)
91.0
489.8
<.0001
Abdominal pain
14
3,132
112
0.0345 (0.0205–0.0485)
74.7
51.5
<.0001
Chest tightness
9
1,857
468
0.2383 (0.1784–0.2982)
88.3
68.6
<.0001
Shortness of breath
26
6,538
1,177
0.2042 (0.1328–0.2858)
98.1
1,329.0
<.0001
Dyspnea
32
4,793
1,255
0.2847 (0.2149–0.3599)
96.4
859.7
<.0001
Chest pain
13
2,490
68
0.0249 (0.0075–0.0490)
81.4
64.4
<.0001
Hemoptysis
13
3,518
71
0.0169 (0.0074–0.0289)
65.2
34.5
.0006
Heart palpitations
2
191
13
0.0671 (0.0316–0.1026)
–
–
–
Pharyngodynia or Throat pain or Pharyngalgia or throat sore
The incidence rate of CNS manifestations in COVID-19 patients (this figure is Created with BioRender.com)
Table 4 shows comorbidities that were reported in 60 studies. The highest incidence rate in comorbidities was hypertension with 23.54% (95% CI: 19.14%–27.94%), diabetes mellitus (11.68% with 95% CI, 9.80%–13.57%), cardiovascular disease (11.66% with 95% CI: 8.97%–14.35%), and cerebrovascular diseases (3.47% with 95% CI: 2.29%–4.85%).
TABLE 4.
Comorbidities in COVID-19-infected patients with CNS symptoms
Variables
No of studies
Total sample size
NO positive case
Incidence rate (95% CI)
Heterogeneity
I2 (%)
Q
p-Value
Any comorbidities
27
6,729
1,932
0.3247 (0.2729–0.3766)
95.8
617.9
<.0001
Cerebrovascular diseases
19
4,502
152
0.0347 (0.0229–0.0485)
76.3
76.1
<.0001
Cardiovascular diseases
35
8,394
743
0.1166 (0.0897–0.1435)
97.8
1577.8
<.0001
Cardiovascular disease and Cerebrovascular diseases
Recently, the world has encountered an emergent outbreak posed by the novel coronavirus 2019, officially known as COVID-19. This infection has become a global threat, endangering millions of lives worldwide. Hence, many experts, researchers, scientists, and clinicians are attempting to investigate various aspects of this new infection to find useful solutions for coping with COVID-19. One of the various aspects of COVID-19 is its impact on the CNS, as reported in a growing number of studies (Baig, 2020). In addition to the common symptoms in COVID-19, several CNS symptoms such as headache and impaired consciousness have been observed in infected patients (Mao et al., 2020).
While most investigated the respiratory symptoms of COVID-19, Mao et al. specifically examined the prevalence of neurological manifestations ranging from CNS to peripheral nervous system (PNS) and neuromuscular symptoms in an observational study on COVID-19 patients. They demonstrated CNS presentations ranging from dizziness and headache to impaired consciousness, acute cerebrovascular disease, ataxia, and seizure (Mao et al., 2020). Based on the possible neuroinvasive potential of COVID-19, in this systematic review and meta-analysis, we analyzed those evidence indicating the involvement of CNS. We assessed 11,687 COVID-19 adult patients from six countries. We reported that COVID-19 patients commonly showed CNS symptoms, including headache, dizziness, and impaired consciousness. Headache (8.69%) was the most common CNS symptoms, followed by dizziness (5.94%) and impaired consciousness (1.9%). Exact reasons for headache, commonly seen in patients, remained unexplained. However, it can be due to COVID-19-related stress and anxiety (Garg, 2020). It is reported that the headache may also be related to the elevated level of inflammatory mediators and reduced cerebral blood flow in response to hypoxia (Jasti et al., 2020), but further studies are needed.
There are two main routes of CNS entry of COVID-19 (hematogenous and peripheral nerves route) leading to CNS infection. In the hematogenous route, the virus infecting respiratory tracts can reach the CNS through the bloodstream via overcoming a strict obstacle known as the blood–brain barrier (BBB) (Desforges et al., 2014, 2020; Román et al., 2020; Sepehrinezhad et al., 2020; Swanson and McGavern, 2015). They also may enter the CNS through circumventricular organs, those CNS organs lacking the BBB (Chigr et al., 2020). The second route, a peripheral nerve, can provide the virus with a retrograde route in to access the CNS via an axonal transport machinery (Baig et al., 2020; Desforges et al., 2014, 2020; Román et al., 2020; Sepehrinezhad et al., 2020; Swanson and McGavern, 2015). In accordance with this finding, some previous studies on other types of coronaviruses indicate that coronaviruses can reach the brain via cranial nerves (e.g., olfactory, trigeminal nerve terminals in the nasal cavity) (Desforges et al., 2020; Li et al., 2016; Natoli et al., 2020; Netland et al., 2008).
Furthermore, SARS-CoV-2 can have indirect effects on the CNS (Zhou, Kang, et al., 2020). Cytokine storm as an immune system response during COVID-19 infection could lead to the breakdown of the blood–brain barrier (BBB) (Liguori et al., 2020; Poyiadji et al., 2020). Infection of airway tissues by COVID-19 in severe cases leads to impaired gas exchange, subsequently causing CNS hypoxia resulting in neural dysfunction (Abboud et al., 2020). More precisely, both cytokine storm and hypoxia which are frequently present in the severe condition of infection can contribute to making the BBB more permeable to the virus (Kaur & Ling, 2008; Zhou, Kang, et al., 2020).
There exists a wealth of evidence that supports the expression and distribution of the ACE2, the receptor for SARS-CoV-2, in the CNS (Jiang et al., 2013; Kawajiri et al., 2009; Li, Li, et al., 2020; Xia & Lazartigues, 2008; Xia et al., 2011; Xu et al., 2011; Zubair et al., 2020). Hence, ACE2 may be a potential target of COVID-19 upon the entrance into the CNS, triggering its effects on CNS tissue (Baig et al., 2020). The presence of the virus in the central nervous system is also supported by some evidence reporting COVID-19 in the CSF of the infected cases (Moriguchi et al., 2020; Zhou, Zhang, et al., 2020).
In our meta-analysis, the mortality rate of COVID-19 cases with at least one CNS symptom was 10.47%, which is much higher than the mortality rate of the general infected population (Borges do Nascimento et al., 2020). Such a mortality rate can indicate the importance of careful monitoring of CNS manifestations in COVID-19 patients. This may be due to the effect of COVID-19 on the brain stem and suppression of the cardiorespiratory control centers causing respiratory failure and death (Li, Bai, et al., 2020).
Moreover, recent studies have shown that COVID-19 can accelerate the formation of the blood clot in the blood vessels, increasing the risk of cerebrovascular diseases in COVID-19 patients (Choi et al., 2020; Hess et al., 2020). Hence, because the brain is nourished by a network of blood vessels, this could be indicative of the importance of cerebral vasculature investigations on the CNS symptoms in the COVID-19 infection.
In a nutshell, attention to the CNS aspects of COVID-19 infection has outstanding benefits for clinician's understanding of a very serious complication of this infection. At this point in time, researchers have mainly focused on finding medicinal treatments for respiratory symptoms of COVID-19. However, it is necessary to investigate the various CNS manifestations of COVID-19 since they are associated with increased severity and mortality (Mao et al., 2020). Not only respiratory system dysfunction, but also impairment of respiratory control centers in the CNS (brain stem) can induce acute respiratory failure (Carvalho et al., 2011; Li, Bai, et al., 2020). Therefore, considering all effective factors, it can provide clinicians to choose the best way in an attempt to manage this pandemic more efficiently.
5 LIMITATIONS
There are several limitations in our systematic review and meta-analysis. Since in this ongoing pandemic, most of the investigations have conducted on typical signs and symptoms of COVID-19. Thus, the number of studies on the atypical complications of COVID-19, such as CNS presentations, is partially low. Moreover, there exist many COVID-19 preprint papers that have not yet undergone peer review. Additionally, five studies included in our meta-analysis reported headache and/or dizziness as one symptom in COVID-19 cases. Because we were not sure that headache and/or dizziness is resulted from headache or is a consequence of the dizziness, it would be challenging to categorize headache and/or dizziness in the subgroup of dizziness or headache. Hence, in our meta-analysis, it was not reported as a CNS manifestation and is implied as a separate symptom (Table 3).
6 CONCLUSION
COVID-19 is a global problem that currently affects millions of people. This highly pathogenic virus can affect various parts of the human body. Although the respiratory tract has been mainly targeted by COVID-19, the central nervous system can be affected significantly. In addition, patients with more severe illness showed more CNS symptoms, which may bring on worsen clinical conditions. This study achieved an important estimation for the incidence of neurological manifestations in patients with COVID-19. The results of our survey may be helpful for clinicians for better diagnosis and management of CNS signs and symptoms in patients with COVID-19.
7 AUTHOR CONTRIBUTORS
SH.N. and S.D. conceptualized and designed the study; A.A.J., S.M., S.S., S.S., and M.H. involved in acquisition of data; S.D. analyzed and interpreted the data; S.H.N., S.D., A.A.J. S.M., S.S., and S.M.P. drafted the manuscript; SH.N., S.D., A.A.J., F.A., H.E., and D.F. critically revised the article.
ACKNOWLEDGMENTS
Dr. Katayoun Alikhani for her supports and comments.
The data that support the findings of this study are openly available.
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