Keywords:
COVID-19 - Cerebrospinal Fluid - Encephalitis - Polymerase Chain Reaction - Headache
Palavras-chave:
COVID-19 - Líquido cefalorraquidiano - Encefalite - Reação em Cadeia da Polimerase
- Cefaleia
INTRODUCTION
The new coronavirus (SARS-CoV-2) appeared in Wuhan, China, and quickly evolved into
a pandemic[1]. There have been reports of neurological manifestations associated with COVID-19.
These manifestations include mild symptoms, such as headache, fatigue, hypogeusia
and hyposmia; and severe manifestations, such as encephalitis, encephalopathy, Guillain-Barré
syndrome (GBS) and stroke[2].
Cerebrospinal fluid (CSF) analysis is essential in making diagnoses of infections
of the central nervous system (CNS), since it can provide information about the inflammatory
response and can identify the etiological agent[3]. However, the precision of CSF analysis among patients with acute COVID-19 and CNS
manifestations has not yet been fully established[4].
In this article, we present a systematic review of CSF findings among patients with
COVID-19 and acute CNS symptoms and discuss the potential findings in different CNS
syndromes. We also discuss the potential contribution of CSF analysis in understanding
the underlying mechanisms in CNS manifestations associated with acute COVID-19.
METHODS
MEDLINE (accessed from PubMed) was systematically searched from January 1, 2020, to
April 30, 2021. The search strategy included the key words: “COVID 19” AND “Cerebrospinal
Fluid”. Articles written in English, Spanish, Portuguese and French were included
in this search.
We included the following study types: case reports, descriptive retrospective studies
and longitudinal studies. Review articles were not included. We only included studies
that reported CSF findings. Studies reporting CSF findings from patients with COVID-19
and peripheral nervous system (PNS) manifestations were not included in the present
analysis. We also excluded reports on multisystem inflammatory syndrome in children,
associated with COVID-19. Cases in which an infectious etiology other than COVID-19
was identified to explain the neurological condition, either through conventional
microbiology or through molecular methods, were also excluded.
We retrieved the results from CSF analysis in the different clinical syndromes that
were reported in the studies: stroke, encephalitis, encephalopathy, inflammatory syndromes,
meningitis, seizures and headache. The clinical syndrome definitions used had some
variation between studies but, in general, encephalopathy was defined as alteration
of one or more brain functions that was attributed to systemic disease without structural
brain lesions[4], while encephalitis was characterized by typically focal neurological signs, with
or without meningeal involvement. Neuroimaging studies and/or detection of inflammatory
cells in the cerebrospinal fluid can identify meningeal involvement when it is present[4]
-
[14]. Other inflammatory syndromes considered included cases of acute disseminated encephalomyelitis
(ADEM)[15], neuromyelitis optica, clinically isolated syndrome (CIS)[7] and acute hemorrhagic leukoencephalopathy[11]. When described in a study, the classification of epileptic seizures was reported.
The following CSF parameters were sought and registered from the studies: opening
CSF pressure; CSF white blood cells (WBC); CSF protein concentration; CSF SARS-CoV-2
RT-PCR; intrathecal immunoproduction (IgG index and/or CSF and serum oligoclonal bands
[OCBs]); CSF specific antibodies (including anti-SARS-CoV-2, anti-myelin oligodendrocyte
glycoprotein [anti-MOG], anti-aquaporin-4 [anti-AQ4], anti-N-methyl-D-aspartate [anti-NMDA],
anti-glutamate decarboxylase [anti-GAD] and other autoimmune and paraneoplastic encephalitis
antibodies; and also anti-cardiolipin); CSF interleukins (Ils); chemokines (CXCLs);
tumor necrosis factor alpha (TNF-α); and neurodegeneration CSF biomarkers (ß-Amyloid,
Tau, enolase, neurofilament light chain [NfL], glial fibrillary acid protein [GFAP]
and α-synuclein).
We statistically compared the CSF data from encephalitis, encephalopathy and inflammatory
syndrome cases. The statistical comparisons were carried out using the chi-square
test or Fisher’s exact test, depending on the number of observations in the contingency
table. The significance level was set at P < 0.05.
RESULTS
A total of 222 articles were identified. Among these, we selected 75 articles in accordance
with the search criteria. The study types were case report (37 studies), retrospective
(38 studies) and longitudinal (one study).
A total of 663 patients were included in these 75 studies. The clinical diagnoses
of CNS syndromes among the patients reported in the studies were the following: hemorrhagic
stroke (9 cases; 1.35%), ischemic stroke (16 cases; 2.41%), encephalitis (81 cases;
12.25%), encephalopathy (264 cases; 39.82%), headache (52 cases; 7.84%), other inflammatory
syndromes (56 cases; 8.45%), meningitis (4 cases; 0.6%) and seizures (22 cases; 3.32%).
The seizure types were described as motor (tonic-clonic) generalized onset seizures
(2), focal non motor onset with impaired awareness (2) and unknown (13). The clinical
syndrome was not defined by the authors of the studies in 159 cases.
The findings of CSF parameters were as follows:
-
Opening CSF pressure: this parameter was reported in 59 cases, which were 14 cases
of headache, 13 cases of inflammatory syndromes, 30 cases of encephalitis and two
cases of encephalopathy. Among these, 22% presented increased opening CSF pressure[5]
-
[9]. The results according to the different CNS clinical syndromes are shown in [Table 1].
Table 1
Number of cases tested and number and percentage of cases with abnormal results from
routine CSF analysis in different CNS syndromes.
|
Clinical syndrome
|
CSF pressure
|
CSF WBC
|
CSF protein
|
CSF RT-PCR
|
|
Ischemic stroke
|
0
|
0/4 (0%)
|
0/4 (0%)
|
0/3 (0%)
|
|
Encephalitis
|
2/30 (6.66%)
|
39/74 (52.70%)
|
25/54 (46.29%)
|
6/35 (17.14%)
|
|
Encephalopathy
|
1/2 (50%)
|
24/196 (12.24%)
|
42/153 (29.41%)
|
5/149 (3.35%)
|
|
Headache
|
6/14 (42.86%)
|
0/16 (0%)
|
1/16 (6.25%)
|
0/17 (0%)
|
|
Inflammatory syndromes
|
4/13 (32.5%)
|
18/48 (37.50%)
|
29/48 (41.66%)
|
1/31 (3.22%)
|
|
Meningitis
|
0
|
2/2 (100%)
|
1/1 (100%)
|
1/2 (50%)
|
|
Seizures
|
0
|
3/9 (33.34%)
|
4/5 (80%)
|
0/6 (0%)
|
CSF: cerebrospinal fluid; CSF pressure: elevated CSF open pressure; CSF WBC: increased
CSF white blood cells; CSF protein: increased CSF protein concentration; CSF RT-PCR:
detection of severe acute respiratory coronavirus 2 in CSF by means of reverse transcriptase
polymerase chain reaction.
-
CSF WBC: CSF WBC was reported in 349 cases. Increased CSF WBC was found in 86 cases
(24.64%). Most cases with pleocytosis had less than 100 cells/mm3. In two cases of encephalitis there were more than 100 cells/mm3, in one case the CSF WBC was 115 cells/mm3 and in one case there was marked pleocytosis with 1920 cells/mm3. Overall, there was a predominance of lymphomononuclear cells[5]
-
[76]. The CSF WBC findings according to the CNS clinical syndromes are shown in [Table 1].
-
CSF protein concentration: This information was reported in 281 cases. Increased CSF
protein concentration was found in 93 patients (33.09%). A mild increase in CSF protein
concentration (< 100 mg/dl) was found in 269 patients, moderate increase (100-200
mg/dl) in nine cases and high increase (> 200 mg/dl) in three cases. The highest concentration
was found in a patient with a CNS inflammatory syndrome with CSF protein concentration
of 803 mg/dl[7],[8],[11]
-
[17],[19],[21],[25]
-
[27],[31],[32],[34]
-
[37],[49]
-
[76].
-
SARS-CoV-2 CSF RT-PCR: A search for SARS-CoV-2 genetic material in CSF samples by
means of RT-PCR was reported in 243 cases. Thirteen patients (5.34%) were found to
be positive[5],[8],[10]
-
[12],[14]
-
[25],[27]
-
[29],[32]
-
[46],[49]
-
[77]. Among the cases classified as having encephalitis, the positivity rate was 17.14%.
The percentages of positive RT-PCR results according to the clinical syndrome are
shown in [Table 1].
-
Intrathecal immunoproduction and specific CSF antibodies: OCBs were found in 20% of
the 138 patients on whom this test was performed. The most frequent pattern was type
4, with identical OCBs in CSF and serum, thus indicating systemic inflammation. The
IgG index was negative in all 12 cases tested. Among the specific antibodies tested
in CSF, anti-MOG was positive in one of two cases (50%), anti-NMDA was positive in
three of 17 cases (11%) and anti-cardiolipin was positive in two of 11 cases (18%)[16],[18],[21],[22],[24],[26],[31],[52],[56],[59],[63]. The complete list of antibodies tested and their results are shown in [Table 2].
Table 2
Number of cases tested and number of cases with abnormal results from the following
CSF tests: intrathecal antibody synthesis tests, specific antibody identification,
inflammation mediators such as interleukin and chemokine concentrations and neurodegeneration
biomarkers in patients with acute COVID-19.
|
CSF test
|
Encephalopathy
|
Encephalitis
|
Inflammatory syndrome
|
IS
|
HS
|
Seizure
|
Headache
|
Not defined
|
Total
|
%
|
|
IgG and antibodies
|
OCB (total)
|
43
|
2
|
9
|
2
|
0
|
6
|
13
|
63
|
138
|
0
|
|
OCB negative
|
17
|
0
|
7
|
2
|
0
|
3
|
13
|
57
|
99
|
72
|
|
OCB type 2
|
2
|
0
|
0
|
0
|
0
|
0
|
0
|
6
|
8
|
8
|
|
OCB type 4
|
23
|
0
|
2
|
0
|
0
|
3
|
0
|
0
|
28
|
20
|
|
IgG index (total)
|
0
|
0
|
12
|
0
|
0
|
0
|
0
|
0
|
12
|
0
|
|
IgG index (positive)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
ANTI-AQ-4 (total)
|
0
|
0
|
12
|
0
|
0
|
0
|
0
|
0
|
12
|
0
|
|
ANTI-AQ-4 positive
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
Anti-MOG (total)
|
0
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
2
|
0
|
|
Anti-MOG (positive)
|
0
|
0
|
1
|
0
|
0
|
0
|
0
|
0
|
1
|
50
|
|
IgG anti-SARS-CoV-2 (total)
|
14
|
2
|
0
|
3
|
2
|
0
|
0
|
0
|
10
|
0
|
|
IgG anti-SARS-CoV-2 (positive)
|
6
|
0
|
0
|
1
|
1
|
0
|
0
|
0
|
0
|
38
|
|
Anti-NMDA (total)
|
2
|
1
|
13
|
0
|
0
|
0
|
0
|
12
|
27
|
0
|
|
Anti-NMDA (positive)
|
1
|
1
|
1
|
1
|
0
|
0
|
0
|
1
|
3
|
11
|
|
Anti-GAD (total)
|
1
|
0
|
12
|
0
|
0
|
0
|
0
|
11
|
24
|
0
|
|
Ant-GAD (positive)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
Other AI* (total)
|
1
|
0
|
0
|
0
|
0
|
0
|
0
|
11
|
12
|
0
|
|
Other AI* (positive)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
Anti-cardiolipin (total)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
11
|
11
|
0
|
|
Anti-cardiolipin (positive)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
2
|
2
|
18
|
|
Inflammatory markers
|
IL-6 (total)
|
3
|
39
|
2
|
12
|
5
|
3
|
0
|
58
|
122
|
0
|
|
Increased Il-6
|
3
|
33
|
2
|
12
|
5
|
3
|
0
|
47
|
105
|
86
|
|
Il-8 (total)
|
1
|
3
|
0
|
12
|
5
|
3
|
0
|
18
|
42
|
0
|
|
Increased IL-8
|
1
|
3
|
0
|
12
|
5
|
3
|
0
|
18
|
42
|
100
|
|
Il-10 (total)
|
1
|
3
|
2
|
0
|
0
|
0
|
0
|
0
|
6
|
0
|
|
Increased Il-10
|
1
|
3
|
2
|
0
|
0
|
0
|
0
|
0
|
6
|
100
|
|
TNF-alpha (total)
|
1
|
2
|
0
|
5
|
12
|
3
|
0
|
25
|
48
|
0
|
|
Increased TNF-alpha
|
1
|
2
|
0
|
5
|
12
|
3
|
0
|
18
|
41
|
85
|
|
MCP-1 (total)
|
0
|
1
|
0
|
0
|
0
|
0
|
0
|
0
|
1
|
0
|
|
Increased MCP-1
|
0
|
1
|
0
|
0
|
0
|
0
|
0
|
0
|
1
|
100
|
|
Il-2 (total)
|
0
|
22
|
2
|
0
|
0
|
0
|
0
|
0
|
24
|
0
|
|
Increased Il-2
|
0
|
22
|
2
|
0
|
0
|
0
|
0
|
0
|
24
|
100
|
|
Il-4 (total)
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
0
|
2
|
0
|
|
Increased Il-4
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
0
|
2
|
100
|
|
Il-12 (total)
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
7
|
9
|
0
|
|
Increased Il-12
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
0
|
2
|
22
|
|
Il-1ß (total)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
18
|
18
|
0
|
|
Increased Il-1ß
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
18
|
18
|
100%
|
|
CXCL-2 (total)
|
0
|
22
|
0
|
0
|
0
|
0
|
0
|
0
|
22
|
0
|
|
Increased CXCL-2
|
0
|
22
|
0
|
0
|
0
|
0
|
0
|
0
|
22
|
100%
|
|
CXCL-8 (total)
|
0
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
2
|
0
|
|
Increased CXCL-8
|
0
|
0
|
2
|
0
|
0
|
0
|
0
|
0
|
2
|
100%
|
|
CXCL-10 (total)
|
1
|
3
|
2
|
0
|
0
|
0
|
0
|
0
|
6
|
0
|
|
Increased CXCL-10
|
1
|
3
|
2
|
0
|
0
|
0
|
0
|
0
|
6
|
100%
|
|
CSF neurodegeneration biomarkers
|
ß-amyloid (total)
|
1
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
1
|
0
|
|
Decreased ß-amyloid
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0%
|
|
Tau (total)
|
1
|
16
|
0
|
0
|
0
|
0
|
0
|
16
|
33
|
0
|
|
Increased Tau
|
0
|
6
|
0
|
0
|
0
|
0
|
0
|
6
|
12
|
36%
|
|
Enolase (total)
|
0
|
1
|
0
|
0
|
0
|
0
|
0
|
0
|
1
|
0
|
|
Increased enolase
|
0
|
1
|
0
|
0
|
0
|
0
|
0
|
0
|
1
|
100%
|
|
NfL (total)
|
0
|
17
|
0
|
0
|
0
|
0
|
0
|
34
|
51
|
0
|
|
Increased NfL
|
0
|
8
|
0
|
0
|
0
|
0
|
0
|
28
|
36
|
71%
|
|
GFAP (total)
|
0
|
17
|
0
|
0
|
0
|
0
|
0
|
16
|
33
|
0
|
|
Increased GFAP
|
0
|
3
|
0
|
0
|
0
|
0
|
0
|
3
|
6
|
18%
|
|
α-synuclein (total)
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
7
|
7
|
0
|
|
Increased α-synuclein
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0%
|
CSF: cerebrospinal fluid; IS: ischemic stroke; HS: hemorrhagic stroke; Total: number
of cases tested; OCB: oligoclonal bands; AQ-4: aquaporin-4; MOG: myelin oligodendrocyte
glycoprotein; NMDA: N-methyl-D-aspartate; GAD: glutamic acid decarboxylase; *Other
AI: other CSF antibodies for autoimmune and paraneoplastic encephalitis; Il: interleukin;
TNF-α: tumor necrosis factor alpha; MCP-1: monocyte chemoattractant protein - 1; CXCL:
chemokine; NfL: light neurofilament; GFAP: glial fibrillary acidic protein.
-
Inflammatory mediators: The complete list of cytokines and chemokines tested and their
results is shown in [Table 2]. The most frequently tested inflammatory mediators were Il-1ß, Il-2, Il-6, Il-8
and TNF-α. Increased CSF concentration of inflammatory mediators was found in at least
85% of the cases in which they were tested. The only exception was in relation to
Il-12, which was increased in only 22% of the cases, although it had only been tested
in 18 cases[8],[12],[13],[36],[47],[48],[60],[67],[70],[7]
[6].
-
Neurodegeneration CSF biomarkers: The most frequently tested CSF neurodegeneration
biomarkers were Tau protein, NfL and GFAP, in 33, 51 and 33 cases, respectively. Increased
levels were found in 36%, 71% and 18%, respectively[9],[61],[66],[70],[77]. One study found a correlation between Tau and NfL levels and the opening CSF pressure[9]. The complete list of biomarkers and their results is shown in [Table 2].
-
Statistical analyses: [Table 3] shows the statistical comparison between CSF data from patients with encephalitis,
encephalopathy and inflammatory syndromes. The percentage of increased WBC in patients
with encephalitis was significantly higher than in cases with encephalopathy or inflammatory
syndrome. Patients with encephalitis and inflammatory syndrome had significantly higher
protein concentration in the CSF than those with encephalopathy. The percentage of
RT-PCR positivity was significantly higher among cases with encephalitis than in patients
with encephalopathy and inflammatory syndromes. There was no difference between the
groups regarding the presence or the type of OCBs, or the frequency of increased Il-6.
Table 3
Statistical comparisons of the following variables: increased WBC/mm3, increased protein concentration, percentage detection of the SARS-CoV-2 genome,
percentage of type 2 and type 4 OCBs and percentage of cases with increased CSF IL-6,
among patients classified as having encephalitis, encephalopathy or inflammatory syndromes,
using the chi-square test or Fisher's exact test.
|
Increased CSF WBC/mm3
|
Increased CSF protein concentration
|
RT-PCR
|
OCB type 2
|
OCB type 4
|
IL-6
|
|
Encephalitis
|
39 of 74 (52.7%)
|
24 of 54 (42.29%)
|
6 of 35 (17.14%)
|
0 of 2 (0%)
|
0 of 2 (0%)
|
33 of 39 (84.61%)
|
|
Encephalopathy
|
24 of 172 (12.24%)
|
42 of 153 (29.41%)
|
5 of 144 (3.35%)
|
2 of 42 (4.65%)
|
23 of 43 (53.48%)
|
3 of 3 (100%)
|
|
Inflammatory syndrome
|
18 of 48 (37.5%)
|
29 of 48 (41.66%)
|
1 of 31 (3.22%)
|
0 of 9 (0%)
|
2 of 9 (22.22%)
|
2 of 2 (100%)
|
|
P
|
< 0.05
|
< 0.05
|
< 0.05
|
NS
|
NS
|
NS
|
WBC: white blood cells; SARS-CoV-2: severe acute respiratory coronavirus 2; CSF: cerebrospinal
fluid; IL-6: interleukin 6; OCB: oligoclonal bands; RT-PCR: detection of the genome
of SARS-CoV-2 in the CSF with reverse transcriptase polymerase chain reaction; Il:
interleukin; NS: not significant.
DISCUSSION
Mild inflammatory changes in conventional CSF analyses were frequently found in patients
with central neurological manifestations associated with COVID-19, and were seen more
frequently in cases of encephalitis. The SARS-CoV-2 genome was found in a small percentage
of cases, more commonly among those with encephalitis than in those with encephalopathy
or other inflammatory syndromes. Most patients, regardless of the clinical syndrome,
presented increased CSF cytokines and chemokines. CSF neurodegeneration markers were
increased in several cases. These data suggest that CSF analysis is useful in the
clinical evaluation of these patients and may contribute to better understanding of
the CNS neurological manifestations associated with COVID-19. However, with the present
data, it is not yet possible to define the precise mechanisms involved in neuronal
injury and in generation of neurological symptoms.
The number of patients with ischemic and hemorrhagic stroke on whom CSF analysis was
done was too small to allow any definitive conclusion about the role of CSF in these
conditions. There were no abnormalities in the conventional CSF analysis in cases
of ischemic stroke. The levels of Il-6, IL-8 and TNF-α were increased in all cases
of ischemic and hemorrhagic stroke that were tested. It is still uncertain whether
the inflammatory process revealed by these CSF measurements has a role in the pathogenesis
of vascular injury associated with these clinical syndromes[21],[24],[43],[49],[57].
Most patients with encephalitis had mild pleocytosis with mild to moderate increases
in CSF protein concentration. Only in 17.14% of the encephalitis cases was the SARS-CoV-2
genome detected in CSF. Previous studies have shown that SARS-CoV-2 can invade the
CNS, via the olfactory nerve or through hematogenous spread, which thus explains why
RT-PCR was positive in some cases[7]. However, the precise role of neuroinvasion and the presence of SARS-CoV-2 within
the CNS in encephalitis cases are still unknown. Interleukins, chemokines and TNF-α
were increased in encephalitis cases[68]. One potential explanation for this is that inflammation has a more frequent role
than direct virus-mediated neuronal injury; however, this hypothesis still needs confirmation.
Another possibility is that the CSF viral load is extremely low, thus reducing the
positivity of CSF RT-PCR9. Future studies comparing cases with and without detection of the viral genome and
correlating CSF data with neuroimaging findings may help to elucidate the pathophysiology
of COVID-19 encephalitis and perhaps may contribute to a more refined definition of
these cases according to these findings.
Changes to the conventional CSF analysis were found in a minority of cases of encephalopathy.
The viral genome was found in the CSF in a small percentage of these patients. It
is possible that systemic inflammation is a determining factor in these cases; however,
this cannot be definitively stated since systemic inflammation was not evaluated in
the present study with regard to encephalitis[5],[8],[10]
-
[12],[14]
-
[25],[27]
-
[29],[32]
-
[76]. Other factors, such as hypoxia, metabolic alterations and drugs with effect on
the CNS, may also have contributed but were not separately analyzed in the studies
included in this review. CSF abnormalities were reported; pleocytosis was found in
12% of the encephalopathy cases and 3.35% had positive CSF RT-PCR for SARS-CoV-2.
It is not possible to rule out the possibility that at least some of these cases were
actually encephalitis rather than encephalopathy cases. The lack of uniformity in
case definition between studies may have contributed to such heterogeneity. Distinguishing
between COVID-19 encephalitis and COVID-19-associated encephalopathy can be difficult
and much other information besides CSF needs to be considered, such as the clinical
picture, electrophysiological findings and the brain magnetic resonance imaging findings[4]. Future studies should establish more homogeneous criteria for distinguishing between
these syndromes and for assessing possible differences in neurological prognosis between
these two conditions.
Patients with other inflammatory syndromes presented with conventional CSF changes
similar to what is normally seen in patients with ADEM due to other etiologies, i.e.
normal CSF or CSF with mild inflammatory changes. The SARS-CoV-2 genome was found
in only one case of CIS and was not found in cases of ADEM. ADEM cases can have transient
OCBs in the CSF and not in the serum. In the present review, no cases with SARS-CoV-2-associated
ADEM had intrathecal immunoproduction, but it is important to mention that only nine
cases of inflammatory syndromes underwent this analysis. It is possible that an autoimmune
disorder triggered by SARS-CoV-2 infection occurred in these cases. One case that
was positive for anti-MOG antibodies and two cases with anti-cardiolipin antibodies
suggest the possibility of an immunological cross-reaction[26]. Unfortunately, these cases were not evaluated for the presence of CSF anti-SARS-CoV-2
antibodies[56], which could have contributed to better understanding of the pathogenesis of this
inflammatory brain injury. With the available data, it is not possible to establish
whether ADEM associated with COVID-19 presents neurological differences in comparison
with ADEM associated with other etiologies. The meaning of anti-NMDA positivity in
a few cases, including some with a clinical pattern compatible with limbic encephalitis,
still needs to be better elucidated. One hypothesis is that SARS-CoV-2 may trigger
not only ADEM but also, on rare occasions, autoimmune limbic encephalitis[62],[63].
The number of cases of patients with seizures and meningitis was too small for an
accurate analysis on CSF findings in these groups[16],[31],[33]. It is more likely that seizures represent a manifestation of encephalopathy or
encephalitis and not a specific clinical syndrome in the context of acute SARS-CoV-2
infection. Almost half of the patients with headache had increased opening pressure
without other CSF abnormalities[6],[9],[48]. The mechanism for this increased pressure is unknown. It is possible that COVID-19-associated
coagulopathy explains this increased opening pressure, for example, through thrombosis
and stenosis in the venous drainage system. An alternative explanation is that a dysfunction
in CSF production and absorption may occur during COVID-19. Both hypotheses still
need to be better evaluated in future studies.
Increased levels of neurodegeneration markers were found in more than 40% of the patients
with encephalitis in whom these markers were tested. One study showed higher levels
of NfL in patients with encephalitis than in patients with encephalopathy[71]. It is possible that NfL determination, along with other CSF, clinical and neuroimaging
data, contributes to refining the assessment of these patients. Also, abnormalities
in neurodegeneration markers not only may be important in acute COVID-19 but also
may potentially contribute to assessing long-term cognitive symptoms in patients with
post-COVID-19 syndrome. In fact, previous studies showed a correlation between some
markers of neurodegeneration and neuroinflammatory response in patients with COVID-19
and the risk of cognitive abnormalities[77]. Future studies providing prospective evaluations on cognition and neurodegenerative
markers among patients who recovered from the acute phase of this disease may contribute
to better understanding of the long-term neurological consequences of this infection.
This study had limitations that deserve to be mentioned. The most important concerns
the definition of cases. The distinction between encephalopathy and encephalitis is
often difficult to ascertain, as both conditions can lead to lowered consciousness.
The presence of epileptic seizures can be part of the context of either encephalopathy
or encephalitis, so it is difficult to assess this manifestation in isolation. Considering
the non-uniformity of criteria for defining cases between the different studies, it
is possible that this influenced the interpretation of CSF data in these different
syndromes. Other limitations included the fact that the studies were retrospective
or case reports. The extensive period of review, taking into account the period of
occurrence of the pandemic, and the analysis of a wide CSF database are strengths
of this study.
In conclusion, the present review shows that CSF analysis has a role in evaluation
of COVID-19-associated CNS disorders. CSF may also contribute to better understanding
of the relationship between SARS-CoV-2 infection and the CNS. Prospective studies
including assessment of CSF inflammatory and neurodegeneration biomarkers may possibly
contribute to better understanding of the determinants of the neurological prognosis
after acute COVID-19.
