Keywords:
COVID-19 - Neuropsychology - Cognitive Dysfunction - Executive Function - Memory
Palabras clave:
COVID-19 - Neuropsicología - Disfunción Cognitiva - Función Ejecutiva - Memoria
INTRODUCTION
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 110
million people worldwide, resulting in more than 2 million deaths globally. The predominant
consequences of the virus are respiratory; however, neurological manifestations of
COVID-19[1] have been reported with a frequency of 36.4 to 84%[2]. Neurological manifestations include altered consciousness, acute neuropathies,
cognitive impairment, and skeletal muscle injury. It is important to note that neurological
symptoms were also found in patients who did not present with the typical signs of
COVID-19 as the only manifestation[3].
Neurological manifestations associated with SARS-CoV-2 infection usually occur during
the second week of illness and are mainly observed in critically ill patients[4]. While psychiatric and neurological alterations have been consistently reported[5],[6],[7], few studies currently report cognitive deficits among COVID-19 survivors[8],[9],[10],[11],[12]. These studies report cognitive deficits in mild and moderate cases of the infection[13], with significant impairment of executive functions, memory, and attention[14]. In addition, cognitive deficits have been reported in studies performed in the
acute phase of the infection[15] and in recovered patients.
With more than 40 million confirmed cases and 1.5 million deaths, Latin America has
been one of the regions most affected by the pandemic[16]. However, evidence of post-COVID cognitive impairment in the region is scarce. Neurological
alterations in post-COVID-19 patients were reported in a cohort study of 63 hospitalized
post-COVID patients[17]. The most frequent neurological complications were ischemic stroke in 30 patients
(47.6%) and encephalopathy in 17 patients (27%), followed by seizures, hemorrhagic
stroke, and headache. These studies highlight the need to evaluate cognitive symptoms
after the disease to assess patients' cognitive status and design rehabilitation strategies.
Regarding the study of post-COVID cognitive impairment in the Latin American region,
Del Brutto[13] compared cognitive change (decline) in a cohort of middle-aged and older adults
from a community in Atahualpa. The study compared changes between pre-pandemic measures
and post-pandemic assessment and between seropositive and seronegative individuals.
Results show a 21% cognitive decline in the sample of COVID-19 survivors versus only
2% of the seronegative group. This study, as well as others[18],[19],[20], assessed cognitive dysfunction using cognitive screening tools such as the Montreal
Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and Telephone Interview
for Cognitive Status (TICS).
The aim of this study was to describe the cognitive profile of a cohort of COVID-19
survivors that attended a neurological clinic in Buenos Aires, Argentina. In addition,
the impact of COVID-19 on cognitive functions in adults without cognitive complaints
before infection, cognitive dysfunction according to disease severity, and cognitive
risk factors were evaluated.
METHODS
Study design and participants
We report data from 45 post-COVID-19 patients recruited from an outpatient neurological
clinic by attending neurologists. Patients were evaluated for an average of 142 days
after illness. Inclusion criteria were: a positive SARS-CoV2 RT-PCR result from nasopharyngeal
swabs, age > 18 years, and no pre-infection cognitive complaint. Exclusion criteria
were: significant upper limb impairment, visual acuity or visual field deficits, drug
use, or psychiatric disorders. The local ethics committee approved the protocol and
all subjects signed an informed consent form before assessments.
Neuropsychological assessment was performed using an extensive cognitive battery.
Additionally, data were collected on the characteristics of the acute COVID-19 episode,
premorbid medical conditions, and functionality for activities of daily living (ADL)
pre-and-post COVID-19. Disease severity was classified as asymptomatic, mild, moderate,
and severe according to WHO[21]. The study was designed in three steps to answer three specific questions: 1) Are
there cognitive deficits in post-COVID-19 subjects with a cognitive complaint? 2)
Is it possible to describe a cognitive profile for these patients? 3) Are there identifiable
risk factors for the occurrence cognitive complaints? First, subjects were compared
with forty-five healthy control (H.C.) subjects with no history of SARS-CoV-2 infection
matched for sex, age, and educational level. In a second instance of the study, we
created cognitive composites to better understand cognition in the domains. The development
of a comprehensive cognitive battery for post-COVID patients took several months.
For this reason, some patients did not receive the complete assessment regardless
of their cognitive performance. To avoid sample bias, only subjects with complete
data (N=29) and their matched controls were included. Finally, in the third instance,
a risk model was constructed by logistic regression for the clinical and demographic
variables evaluated in the study.
Outcomes
Participants underwent a comprehensive neuropsychological evaluation that included
anxiety, depression, and functionality scales. In addition, assessment of clinical
illness characteristics and risk factors were self-reported using structured questionnaires
and scales.
Cognitive assessment
Cognitive screening was performed using the Argentine version of the MoCA[22]. The extensive neuropsychological assessment included attention, memory, language,
executive functions, and visuospatial skills tests. Attention was assessed with Trail
Making A[23], Digit Span Forwards[24], and Digit-Symbol Coding[25]. Memory was tested using Craft Story 21[26], Rey Auditory Verbal Learning Test[27], and Delayed Recall from the Benson Figure Test[28]. Executive function assessment included Trail Making B[23], Wisconsin Card Sorting Test[29], Stroop Test[30], and phonological fluency[31]. Benson Figure and Clock Drawing Test[32] assessed visuospatial skills. Finally, the language was assessed using the Multilingual
Naming Test[33] and semantic fluency[34].
Neuropsychiatric and functional assessment
The Hospital Anxiety and Depression Scale[35] was administered for neuropsychiatric screening purposes. In addition, WHODAS 2.0
Functional Scale[21] was used to assess pre- and post-COVID-19 changes in ADL. Subjects were instructed
to answer the questions regarding their pre-infectious status.
Disease severity and risk factors for cognitive impairment assessment
Participants completed the CAIDE (Cardiovascular Risk Factors, Aging, and Incidence
of Dementia) Dementia Risk Score, a test for estimating risk of dementia in the general
population[36]. This test combines self-reported measures of age, education, sex, hypertension,
body mass index, hypercholesterinemia, and physical activity into a dementia risk
score. In addition, we assessed risk factors for COVID disease severity such as diabetes,
smoking, cardiac disease, and chronic obstructive pulmonary disease (COPD) using an
ad hoc yes/no binary questionnaire.
Statistical analysis
All variables were tested graphically and analytically for normality assumptions.
For variables with normal distribution, summary statistics are presented as mean and
standard deviation (S.D.), and for variables without normal distribution, median (M)
and interquartile range (IQR) are used. Group differences were evaluated using independent
t-tests, one-way ANOVA, and the Mann-Whitney U or Kruskal-Wallis test was used according
to data distribution. To prevent an increase in the family-wise error rate (FWER)
associated with multiple independent hypothesis testing, we used the Benjamini Hochberg
procedure when more than four independent variables were analyzed in one group. We
also approached the FWER problem with the creation of composites (see next section).
A risk model for cognitive impairment diagnosis was built. In this cohort, cognitive
impairment diagnosis was defined as a Z score of -1.5 or less in at least one cognitive
composite. A logistic regression model was used to assess this risk. Results are presented
as odds ratios (OR) for every risk factor and accuracy model through Akaike information
criteria (AIC). For all tests, a significance level was set at p<0.05.
Results from neuropsychological tests were calculated using composite scores. The
composite quantifies cognitive function across multiple tests with greater statistical
power than individual measures. It consolidates type 1 error into a single outcome.
Domain-specific composites were constructed using the tests from the neuropsychological
battery that better predicted cognitive impairment for each cognitive domain.
The domain-specific composite outcome was calculated as follows:
-
Scores for each contributing test were converted to Z scores according to normative
data. When necessary, Z scores were corrected so that positive scores reflected better
performance and negative scores reflected worse performance;
-
Memory Composite: RAVLT learning score and RAVLT Delayed Score, Benson Figure Test
Delayed score;
-
Attention Composite: TMT A, Digit span Forwards;
-
Executive Composite: TMT B, Digit span Backward, Phonological fluency;
-
Language Composite: MINT score, Semantic fluency.
RESULTS
Demographic results
The characteristics of the complete cohort of 45 post-COVID-19 patients (M = 50) and
45 H.C. matched by age, sex, and education are shown in [Table 1]. There were no differences between patients and H.C. in the estimated risk for dementia
as measured by the CAIDE Score (p=0.3).
Table 1
Demographic results.
|
Characteristic
|
Healthy controls (N = 45)
|
Post-COVID (N = 45)
|
p-value2
|
|
Age (y)
|
57 (46, 64)
|
50 (43, 63)
|
0.4
|
|
Sex: female
|
20 (44%)
|
22 (49%)
|
0.7
|
|
Education (y)
|
17.00 (15.00, 18.00)
|
17.00 (15.00, 18.00)
|
>0.9
|
|
Duration of infection (days)
|
-
|
15.5 (2.2)
|
|
|
Evaluation post-infection (days)
|
-
|
142 (75.9)
|
|
|
Hospitalization
|
-
|
14 (31%)
|
|
|
CAIDE dementia score
|
6.00 (3.00, 7.00)
|
5.00 (2.00, 7.00)
|
0.3
|
Data are reported as median (interquartile range), n (%), or median (standard deviation);
[2]Wilcoxon rank sum test or Pearson's Chi-squared test; CAIDE: Cardiovascular Risk
Factors, Aging, and Incidence of Dementia Dementia Risk Score.
General cognitive performance and neuropsychiatric symptomatology
When comparing H.C. and patients on individual test measures ([Table 2]), no significant differences were found in the complete sample for the screening
measures (MoCA p=0.15; MMSE p=0.4). However, significant differences were found between
groups in all of the memory and attention scales. Language measures were significantly
lower for semantic and phonological fluency in the patient group, but not for naming.
Significant differences in executive performance were found between groups, with a
better performance of H.C. in alternating attention, categorization, and perseverations.
No differences were found in the visuospatial domain in copying complex figures; however,
significantly lower performance was observed in the patient group for the CDT. It
is important to note that this test does not exclusively assesses visuospatial abilities
but also includes semantic and executive components. The neuropsychiatric variables
of depression and anxiety did not differ between groups.
Table 2
General cognitive results.
|
|
Healthy controls (N = 451)
|
Post-COVID (N = 451)
|
p-value2
|
|
Screening
|
MoCA total
|
27.22 (1.99)
|
26.49 (2.90)
|
0.4
|
|
MMSE/MoCA crosswalk
|
27.22 (1.99)
|
26.04 (3.33)
|
0.15
|
|
CDT
|
9.78 (0.59)
|
9.13 (1.35)
|
0.007
|
|
Memory
|
RAVLT Total
|
50 (9)
|
43 (13)
|
0.018
|
|
RAVLT delayed recall
|
10.2 (2.9)
|
8.2 (3.5)
|
0.007
|
|
Benson figure delayed recall
|
12.27 (2.65)
|
10.50 (3.25)
|
0.009
|
|
Language
|
MINT/BNT crosswalk
|
30.31 (1.55)
|
29.47 (2.12)
|
0.058
|
|
Semantic fluency
|
22.6 (4.5)
|
18.9 (5.2)
|
<0.001
|
|
Phonological fluency (p)
|
17.9 (4.3)
|
14.1 (4.6)
|
<0.001
|
|
Attention
|
Digit span (direct)
|
6. 89 (0.93)
|
5.89 (1.30)
|
<0.001
|
|
Digit span (indirect)
|
5.09 (0.95)
|
4.04 (1.19)
|
<0.001
|
|
Trail making test A
|
29 (7)
|
47 (25)
|
<0.001
|
|
WAIS-IV Coding
|
13.5 (2.9)
|
11.8 (3.7)
|
0.010
|
|
Executive system
|
Trail making test B
|
62 (22)
|
107 (76)
|
<0.001
|
|
WCST cat
|
6.00 (0.00)
|
5.59 (1.04)
|
0.014
|
|
WCST pers
|
0.89 (1.29)
|
2.94 (4.63)
|
0.010
|
|
Visuospatial
|
Benson figure copy
|
16.24 (0.98)
|
16.26 (3.10)
|
0.2
|
|
Neuropsychiatric
|
HADS anxiety
|
8.8 (3.4)
|
8.5 (3.4)
|
0.8
|
|
HADS depression
|
6.1 (3.7)
|
5.9 (3.5)
|
0.7
|
[1]Data are reported as mean (standard deviation); [2] Wilcoxon rank-sum test; MoCA: Montreal Cognitive Assessment; CDT: Clock Drawing
Test; RAVLT: Rey Auditory Verbal Learning Test; MINT/BNT crosswalk: Multilingual Naming
Test / Boston Naming Test crosswalk; WAIS IV: Wechsler Adult Intelligence Scale IV;
WCST: Wisconsin Card Sorting Test; HADS: Hospital Anxiety and Depression Scale.
Cognitive results by domain, severity, and impact on functionality
The complete cognitive battery including memory, attention, language and executive
composite scores, neuropsychiatric, functional, and risk factor assessment was administered
to a subsample of 29 patients and 29 controls.
Results from composite scores show deficits in memory (p=0.016, d= 0.73), attention
(p<0.001, d=1.2), executive functions (p<0.001, d=1.4), and language (p=0.002, d=0.87).
Cohen’s D was calculated for each composite to measure effect size. Effects for executive
functions, attention, and language were large and effects for memory were intermediate
([Table 3]).
Table 3
Results of cognitive composites.
|
|
Healthy control (N = 291)
|
Post-COVID (N = 291)
|
p-value2
|
Effect size3
|
|
Memory (composite)
|
0.20 (-0.19, 0.60)
|
-0.19 (-0.76, 0.06)
|
0.016
|
0.734
|
|
Attention (composite)
|
-0.12 (-0.57, 0.28)
|
-1.16 (-1.66, -0.60)
|
<0.001
|
1.272
|
|
Executive (composite)
|
0.10 (-0.02, 0.31)
|
-0.62 (-1.52, -0.21)
|
<0.001
|
1.483
|
|
Language (composite)
|
0.05 (-0.22, 0.42)
|
-0.49 (-0.76, 0.04)
|
0.002
|
0.877
|
[1]Data are reported as median (interquartile range); [2]Wilcoxon rank sum test; [3]Cohen's D.
The patient group was divided according to illness severity using the WHO severity
scale ([Table 4] and [Figure 1]). Results show no significant differences between the different cognitive composites
across the different severity groups.
Table 4
Cognitive domain performance across different COVID-19 severity levels.
|
|
Ambulatory: mild disease (N = 191)
|
Hospitalized: moderate and severe disease (N = 91)
|
p-value2
|
|
Memory (composite)
|
-0.19 (-0.69, -0.01)
|
-0.35 (-0.98, 0.06)
|
0.8
|
|
Attention (composite)
|
-1.16 (-1.60, -0.63)
|
-1.31 (-1.90, -0.72)
|
0.6
|
|
Executive (composite)
|
-0.62 (-1.50, -0.32)
|
-0.74 (-1.87, -0.21)
|
0.8
|
|
Language (composite)
|
-0.54 (-0.71, 0.11)
|
-0.40 (-0.76, -0.26)
|
>0.9
|
[1]Data are reported as median (interquartile range); [2]Kruskal-Wallis rank sum test.
Figure 1 Cognitive domains across illness severity levels in in healthy controls.
The change in functionality was assessed with the WHODAS 2.0, which inquires on different
aspects of functioning before and after SARS-CoV-2 infection. The total score was
significantly different between severity groups (p=0.011), indicating a change in
functionality post-SARS-CoV-2 infection according to disease severity. In addition,
WHODAS subscore results show a differential impact of cognitive functionality, social
participation, and mobility between disease severity levels (p=0.007).
Predictors of cognitive impairment
A logistical regression model was built to identify predictors of cognitive impairment
among post-COVID-19 subjects. The model with the best predictive performance (AIC:
38.3) did not identify common clinical risk factors as predictors of post-COVID-19
cognitive impairment. In addition, only self-reported anxiety measured by the Hospital
Anxiety and Depression Scale (HADS) showed significant results ([Table 5]).
Table 5
Predictors of cognitive impairment.
|
Characteristic
|
OR1
|
95% CI1
|
p-value
|
|
CAIDE dementia score
|
0.21
|
0.00, 1.15
|
0.14
|
|
Age (y)
|
1.19
|
0.89, 1.75
|
0.3
|
|
Sex
|
|
|
|
|
Male
|
49.7
|
0.66, 41986.3
|
0.15
|
|
Female
|
49.8
|
0.67, 6.54
|
0.14
|
|
Education (y)
|
1.00
|
0.26, 6.54
|
>0.9
|
|
Obesity
|
4472.3
|
0.97, 5012838000
|
0.11
|
|
Hypertension
|
0.00
|
NA, 14383040000
|
>0.9
|
|
HADS Depression
|
2.22
|
1.17, 6.54
|
0.056
|
|
HADS Anxiety
|
0.49
|
0.18, 0.84
|
0.043
|
|
Physical activity
|
0.21
|
0.00, 10.1
|
0.4
|
[1]Data are reported as odds ratio (OR) and 95% confidence interval (95%CI); CAIDE:
Cardiovascular Risk Factors, Aging, and Incidence of Dementia - Dementia Risk Score;
HADS: Hospital Anxiety and Depression Scale. NA: Not available.
DISCUSSION
The SARS-CoV2 infection produces multiple organ failure leading to a wide variety
of symptomatology and respiratory syndromes. Neurological manifestations are frequent[2] and diverse, and may include cognitive impairment[12]. This study focused on the description of cognitive performance in previously healthy
adults with no history of cognitive impairment. Our results advocate for the importance
of including cognitive assessment as a protocolized stage of post-COVID examination.
We studied patients that attended a Neurological Clinic with a post-COVID cognitive
complaint. Our results show that deficits can be identified predominantly in executive
functions and attention, and have a smaller effect on memory and language. Furthermore,
these deficits do not vary according to disease severity as measured by the WHO's
COVID-19 severity scale[37]. Notwithstanding, self-reported cognitive functionality, social participation, and
mobility differ according to disease severity, indicating that the impact of cognitive
impairment is higher when illness severity is increased.
Regarding the affected cognitive domains, our results are consistent with other studies
that found a similar cognitive profile, with impaired attention and executive functions
in patients one to six months after infection, with severity ranging from asymptomatic[18] to moderate and severe[10],[15],[38]. Furthermore, these deficits are reported in the acute phase of the disease[39],[40] to up to 6 months after recovery[13].
Our study reported that cognitive dysfunction did not vary significantly between the
mild and moderate severity groups. However, this result must be interpreted with caution
because our sample size was small and, most importantly, unevenly distributed across
severity levels. Most of the patients were classified as mild (n=19), and very few
patients as moderate COVID-19 (N=9). Conflicting results have been found in other
studies that looked into the correlation between cognition and cognitive performance.
A group of studies found no association between the severity of COVID-19 and cognitive
functioning[12],[20]. In contrast, others found that global cognitive impairment and executive dysfunction
correlated with the severity of respiratory symptoms and poorer pulmonary function[15]. Our study complements previous research but is not conclusive enough to draw conclusions.
Prospective studies specifically designed to study cognitive performance and cognitive
profile across different disease severity groups are needed.
Regarding possible predictors of cognitive impairment, we found no influence of commonly
studied risk factors for dementia (diabetes, smoking, age, and education) nor the
well-known risk factors for severe COVID-19 respiratory illness. Our study, however,
found that anxiety was a predictive factor of cognitive impairment. It is a well-known
that mood disorders, including anxiety, can cause cognitive dysfunction[41]. However, our study did not find significant differences between groups in anxiety
or depression, and levels of anxiety of our cohort fell into the normal range in both
groups. Therefore, the results must be regarded with caution.
A possible understanding of COVID-19 cognitive impairment may be based on records
of other coronaviruses (such as SARS and MERS), in which long-term neuropsychological
deficits were registered[42]. In these outbreaks, cognitive deficits were also centered on attention, executive
functions, and memory. Furthermore, cognitive dysfunction in patients with a viral
infection such as Human Immunodeficiency Virus (HIV) has also been reported in prior
studies, in which deficits in attention, learning, and memory functions were reported[43]. Additionally, the Zika virus has also been reported to leave long-term cognitive
sequelae[44]. The COVID-19 pandemic has brought to our attention the need to better understand
the role of viral infections in cognitive impairment.
Finally, our results suggest that cognitive symptoms may be expected in patients after
COVID-19 recovery and may last months after illness remission. Thus, our results underscore
the need to include a cognitive assessment in post COVID-19 follow-ups to guide possible
cognitive rehabilitation treatment.
Limitations of our study include heterogeneity at the time of evaluation, small sample
size, and unequal frequency of disease severity levels, as well as the non-inclusion
of patients with severe disease. Future studies should include a systematic analysis
with larger patient cohorts and long-term follow-up. Another limitation of our study
is the absence of a cognitive assessment before infection, which would allow a more
accurate estimation of the impact of COVID-19 on cognitive functions. In addition,
the subjects included in the study had requested a medical consultation, which could
result in a population with elevated anxiety symptoms that could affect cognitive
performance. Finally, a considerable number of subjects did not fully complete the
cognitive assessment battery, so composites were generated to avoid sample bias between
groups.
Results indicated that commonly used screening methods in the elderly population (MMSE,
MoCA) are not sensitive enough to detect cognitive impairment in post-COVID patients.
A more exhaustive neuropsychological examination is needed. Our study is among the
first in our region to use a broad and robust neuropsychological battery, which is
sensitive for detecting cognitive dysfunction post-COVID-19. The neuropsychological
tests included in our composites could be recommended as an adequate neuropsychological
battery for the Latin American population.
