Abstract

Graphical Abstract

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Graphical Abstract

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 as the cause of a respiratory illness designated coronavirus disease 2019 (COVID-19) (Huang et al., 2020). While patients with COVID-19 frequently suffer from respiratory symptoms, neurologic and neuropsychiatric complications have been increasingly reported (Ellul et al., 2020; Varatharaj et al., 2020). Moreover, histopathologic examination of brains from deceased COVID-19 patients indicate the potential of SARS-CoV-2 to infiltrate the central nervous system (CNS) (Solomon et al., 2020).

Reported neuropsychiatric manifestations include milder symptoms like dizziness and anosmia (Hornuss et al., 2020) but also in rare cases severe manifestations such as acute demyelinating encephalopathy (Reichard et al., 2020), meningitis (Moriguchi et al., 2020) and strokes (Helms et al., 2020; Oxley et al., 2020). Recently, the symptoms of 153 patients with COVID-19 from the UK who reported neurologic and psychiatric complications during the acute phase of the disease were reported and intra-cerebral haemorrhages and altered mental status were the most common complications (Varatharaj et al., 2020). Similarly, in a study from Wuhan with 214 patients, 78 patients reported unspecific neurological symptoms and 13 patients had a new cerebrovascular diagnosis during acute infection (Mao et al., 2020).

These studies have focussed on severe neurologic and neuropsychiatric complications during the acute infection but did not include sustained neuropsychological deficits after full recovery from COVID-19. Moreover, severe neurologic complications have been mostly investigated in patients with multiple risk factors who developed severe COVID-19 with complications but not in young adults after recovery. For the outbreaks of the closely related SARS-CoV-2 and middle-east-respiratory-syndrome-coronavirus (MERS-CoV), acute delirium and encephalitis have been reported during acute disease but also sustained neuropsychologic syndromes (Rogers et al., 2020). Thus, deeper analysis and epidemiologic (Ritchie et al., 2020) studies as well as development of screening tools for mild cognitive deficits in young adults are an important unmet clinical need to detect sub-clinical neuropsychologic symptoms and help to differentiate unspecific post-illness-manifestations.

Here, we established a facile screening approach for cognitive deficits in 18 young patients without diagnosed cognitive pre-conditions after recovery from COVID-19 and discovered widespread sub-clinical deficits.

Materials and methods

Results

The aim of this study was to establish a screening that sensitively and specifically detects subtle neurocognitive deficits. Therefore, we screened our post-COVID-19 outpatient clinic for mostly young patients with mild to moderate disease courses according to the WHO criteria (WHO reference number: 451 WHO/2019-nCoV/clinical/2020.5) without known cognitive pre-conditions who recovered without complications. We included 10 females and 8 males at ages ranging from 17 to 71years (mean, 42.2years; SD, 14.3years). Our cohort consisted of 11 inpatients (61%), 6 outpatients (33%) and 1 patient did not seek medical care (6%). During the acute infection, four patients received supplementary oxygen, two patients were treated with remdesivir and one patient with tocilizumab due to cytokine storm. None of the patients received intensive care and no vascular or structural neurological event was recorded. All patients recovered without severe complications 20–105days (median, 85days from COVID-19 recovery to assessment time) prior to the timepoint of our screening (a summary of patients’ characteristics is provided in Table 1). In addition, we tested 10 healthy individuals with similar age (n=10; mean age, 38.4years; SD, 14.4years; a summary of healthy controls’ characteristics is provided in Table 1) as control group.

Table 1

Summary of characteristics and manifestations of post-COVID-19 patients and healthy control subjects

Characteristics	Post-COVID-19 patients	Healthy controls
Mean age (range)	42.11 (17–71)	38.4 (22–59)
Age distribution (%)
<20	1 (5.6)	0 (0)
20–40	8 (42.2)	6 (60)
40–60	8 (47.4)	4 (40)
>60	1 (5.2)	0 (0)
Sex (%)
Female	10 (57.9)	4 (40)
Male	8 (42.1)	6 (60)
Pre-conditions (%)
Asthma bronchiale	3 (16.7)	Not assessed
Hypothyreosis	3 (16.7)	Not assessed
Hypertonus	2 (11.1)	Not assessed
Coagulation disorder	2 (11.1)	Not assessed
Diabetes mellitus type 2	1 (5.6)	Not assessed
Multiple sclerosis	1 (5.6)	Not assessed
Autoimmune hepatitis	1 (5.6)	Not assessed
Follicular lymphoma	1 (5.6)	Not assessed
Clinical stay (%)
Outpatient clinic	6 (68.5)	Not assessed
Inpatient clinic	11 (31.5)	Not assessed
Treatment (%)
Oxygen supplementation	6 (33.3)	Not assessed
Remdesivir	3 (16.7)	Not assessed
Antibiotics	2 (11.1)	Not assessed
Tocilizumab	1 (5.6)
Neuropsychiatric symptoms (%)
Attention deficits	9 (50.0)	0 (0)
Concentration deficits	8 (44.4)	0 (0)
Short-term memory deficits	8 (44.4)	0 (0)
Troubles in finding words	5 (27.8)	0 (0)
Fatigue	3 (16.7)	0 (0)
Severe mood swings	2 (11.1)	0 (0)
Lack of energy	1 (5.6)	0 (0)
Phonophobia	1 (5.6)	0 (0)
Incoherent thoughts	1 (5.6)	0 (0)
Test screening results (range)
TICS-M	38.83 (31–46)	45.8 (43–50)
Fatigue Assessment Scale	24.17 (13–40)	18.1 (18–19)
Patient Health Questionnaire-9 Depression Scale	2.83 (0–9)	0.7 (0–2)

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We chose the TICS-M as primary tool (Cook et al., 2009) as it has been extensively validated for screening of mild cognitive deficiencies by telephone. This we considered important when conducting larger studies that include affected individuals who might not seek professional health care and stay in home quarantine. Strikingly, post-COVID-19 patients scored significantly lower results in the TICS-M (mean, 38.83; range, 31–46) compared to healthy controls (mean, 45.8; range, 43–50) (Fig. 1A), especially regarding short-term memory, attention and concentration/language tasks (Fig. 1B). Notably, results from screening for depression (Personal Health Questionnaire 9) and for fatigue (Fatigue Assessment Scale) did not show significant correlation with TICS-M scores (Fig. 1C and D). In terms of patients’ self-reported symptoms, out of 18 included individuals 9 (50%) reported attention deficits, 8 (44.4%) concentration deficits, 8 (44.4%) short-term memory deficits, 5 (27.8%) troubles in finding words, 3 (16.7%) fatigue, 2 (11.1%) severe mood swings and 1 (5.6%) sustained lack of energy, phonophobia and incoherent thoughts (Fig. 1E).

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Figure 1

Cognitive deficiencies in post-COVID-19 patients. (A) Comparison of TICS-M total scores (P=0.0002) between healthy individuals (n=10) and post-COVID-19 patients (n=18). Two-tailed Wilcoxon-test was used and mean with 95% confidence interval is shown. (B) Comparison of the different cognitive domains orientation (P=0.9643), attention (P=0.029), language and concentration (P=0.009) and memory (P=0.004) that were tested with the TICS-M. Two-tailed Wilcoxon-test was used and mean with 95% confidence interval is shown. (C, D) Linear regression analysis of TICS-M scores and Fatigue Assessment Scale (C; t = −1.3653, FDR-adjusted P=0.3820, Estimate = –0.165) and Patient Health Questionnaire-9 Depression Scale (D; t=0.8957, FDR-adjusted P=0.3836, Estimate = 0.324) scores of post-COVID-patients. (E) Reported neuropsychiatric symptoms that sustained after recovery.

Next, we aimed to find the predictors of our observed cognitive deficits. First, we analysed patients’ characteristics and found that neither sex (Fig. 2A) nor age (Fig. 2B) could explain the observed differences. Additionally, we investigated whether severity of the acute COVID-19 disease could be an explanation. Therefore, we next analysed whether hospitalization had an impact on post-COVID-19 manifestations. However, we found that TICS-M scores in post-COVID-19 patients did not correlate with the time interval from our interview to recovery (Fig. 2C), length of sickness (Fig. 2D) and length of inpatient stay (Fig. 2E). To further evaluate the impact of disease severity, we correlated the neurocognitive deficits with acute and sustained somatic symptoms (Fig. 2F) and treatments during the acute infection. Our analysis revealed that the number of somatic symptoms did not correlate with the number of sustained self-reported neurocognitive deficits (Fig. 2G) and the results in our screening (Fig. 2H). Moreover, treatments such as oxygen supplementation (Fig. 3A) and drugs such as remdesivir, tocilizumab or antibiotics (Fig. 3B) in acute infection could not predict the observed cognitive impairments. Thus, our data imply that post-COVID-19 neuropsychologic deficits are independent from hospitalization and disease severity.

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Figure 2

Cognitive deficits are independent from hospitalization and sickness duration. (A) Comparison of TICS-M total scores (P=0.9644) between female (n=10) and male (n=8) post-COVID-19 patients. Two-tailed Wilcoxon-test was used. (B–E) Linear regression analysis of TICS-M scores and age in years (B; t=1.0241, FDR-adjusted P=0.6420, Estimate = 0.057), time to recovery from acute COVID-19 in days (C; t = −0.0576, FDR-adjusted P=0.9548, Estimate = −0.003), duration of sickness in days (D; t = −0.0576, FDR-adjusted P=0.9548, Estimate = 0.023) and duration of inpatient treatment in days (E; t=0.8254, FDR-adjusted P=0.7021, Estimate = 0.112) of post-COVID-patients. (F) Self-reported somatic symptoms that appeared at least once after recovery from COVID-19 and were reported from at least two patients. (G,H) Linear regression analysis of number of somatic and neurocognitive symptoms (G; t=1.282, FDR-adjusted P=0.2181, Estimate = 0.177) and number of somatic symptoms and TICS-M scores (H; t=0.161, FDR-adjusted P=0.874, Estimate = 0.068).

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Figure 3

Cognitive deficits are independent from acute disease severity and viremia. (A) Comparison of TICS-M total scores (P=0.9251) between post-COVID-19 patients who received supplementary oxygen during acute disease (n=6) and patients who recovered without supplementary oxygen (n=12). Two-tailed Wilcoxon-test was used. (B) Comparison of TICS-M total scores (P=0.1589) between post-COVID-19 patients who received no treatment (n=12), antibiotics (n=2), remdesivir (n=2) or tocilizumab (n=1) during acute COVID-19. Two-tailed Wilcoxon-test was used. (C–H) Linear regression analysis of TICS-M scores and maximal anti-SARS-CoV2-IgG titre (C; t=1.4352, FDR-adjusted P=0.4626, Estimate = 0.014), cycle threshold values in SARS-CoV-2 PCR (D; t=0.8422, FDR-adjusted P=0.9358, Estimate = 0.064), CRP (E; t = −0.0811, FDR-adjusted P=0.4363, Estimate = 0.021), ferritin (F; t=0.1266, FDR-adjusted P=0.4363, Estimate = 0.002), IL-6 (G; t = −0.1309, FDR-adjusted P=0.4363, Estimate = 0.009), d-dimers (H; t=0.8330, FDR-adjusted P=0.4363, Estimate = 0.121) during acute COVID-19 infection.

Subsequently, we analysed the impact of acute inflammation and maximal viremia in acute COVID-19 on neurocognitive deficits. Therefore, we accounted the cycle threshold from SARS-CoV-2 PCR, antibodies against SARS-CoV-2 and inflammatory serum markers. Our analysis revealed that maximal SARS-CoV-2 IgG-titres (Fig. 3C), SARS-CoV-2-PCR cycle threshold values (Fig. 3D), CRP (Fig. 3E), ferritin (Fig. 3F), IL-6 (Fig. 3G) and d-dimer (Fig. 3H) serum concentration during acute COVID-19 were not significant predictors of our observed neurocognitive deficits.

For further diagnostic measures, we investigated the two most severely affected patients by cranial MRI and lumbar puncture that excluded structural pathologies and acute inflammation. Detailed neuropsychologic evaluation confirmed deficits of attention, executive functions and memory (detailed case vignettes are reported in the supplementary material).

Discussion

SARS-CoV-2 affects multiple organ systems by infiltrating endothelial cells of blood vessels throughout the whole body (Varga et al., 2020). Thus, a multitude of symptoms and clinical disease courses have been described (Gupta et al., 2020). Here, we focussed on the evaluation of neurocognitive post-COVID-19 manifestations in mostly young adults who recovered from acute uncomplicated COVID-19. This study demonstrates substantial neurocognitive deficits that sustain after recovery and advocate screening routines for cognitive deficits during medical care of post-COVID-19 patients.

Cerebrovascular events and altered mental status have been described to be common neuropsychiatric manifestations in acute COVID-19 in a nationwide surveillance study in the UK (Varatharaj et al., 2020). In total, 59% of patients with altered mental status could be assigned to a neuropsychiatric disorder, underlining the diversity of COVID-19-associated manifestations. We screened patients after recovery from COVID-19 and found substantial neurocognitive deficits that sustained after acute infection. Moreover, we detected subtle cognitive deficits that did not restrain most patients in daily life and were only unmasked by our specific screening, including deficits in short-term memory, attention and concentration. Retrospective meta-analysis of SARS and MERS outbreaks has revealed acute and long-term neuropsychological deficits. Similar to our findings, most-common post-illness manifestations included impaired concentration and attention in 19.9% and impaired memory in 18.9% of patients after recovery (Rogers et al., 2020). Therefore, our study represents first indications that warrant broad screenings in post-COVID-19 patients to clarify the diversity of neuropsychological deficits and prevent potential further harm.

Screening methods for mild cognitive deficits are mostly used in the diagnostics of dementia that were validated in elderly adults (Castanho et al., 2014). Here, we chose TICS-M as it has been validated as a telephone screening method which is important for prospective studies that include patients who did not seek professional medical care during or after COVID-19. However, TICS-M has been validated for the diagnosis of mild amnestic dementia in a patient cohort with an average age of 74.9years (Cook et al., 2009). Since the average age of our patient cohort (42.1years) was considerably lower, we additionally tested a healthy control group with similar age as control. Thus, further optimization of a standardized screening tool is needed. Our findings suggest to especially focus the screening on short-term memory, attention and concentration. In contrast to currently available screening tools, validation should include all age groups since we and others (Dinakaran et al., 2020; Nalleballe et al., 2020) observed neurocognitive deficits in young adults.

Post-viral-syndromes have been described for multiple viral infections, such as Epstein–Barr–Virus or influenza (Hotchin et al., 1989) and are characterized by severe fatigue (Thomas, 1987). Smartphone-App-based patients’ reports assessing fatigue in COVID-19 (Menni et al., 2020) and histopathological findings of viral infiltrates and diffuse immune cell activation in brains from deceased COVID-19 patients (Polak et al., 2020) may indicate similar clinical presentations. However, systematic analysis with large patient cohorts in different cultural settings and different countries is needed for clarification. To exclude potential biases and classical post-viral-syndromes, we additionally screened for fatigue and depression. Our data indicate that neurocognitive deficits after recovery from COVID-19 are independent from fatigue and mood alterations and therefore might be different from the classical post-viral syndrome (Perrin et al., 2020) but a specific post-COVID-19 manifestation. SARS-CoV-2 might infiltrate the CNS through the nose (Riel et al., 2015) and trigger a reactive immune response in the brain that could alter neuronal signalling. In addition, exposure of human brain organoids to SARS-CoV-2 revealed direct infection of neurons with subsequent alterations of intracellular signalling and cell death (Ackermann et al., 2020) that could disturb neuronal connectivity. Notably, TICS-M scores of post-COVID-19 patients did not significantly correlate with the maximal inflammatory response during the acute infection. Studies that investigated chronic fatigue syndrome in rheumatic disorders (Korte and Straub, 2019) and multiple sclerosis (Giovannoni, 2006) found that chronic but not acute dysregulation of the immune metabolism and especially cytokine composition correlated with fatigue and individual suffering. Although serum profiling during acute COVID-19 revealed distinct cytokine profiles that correlated with disease outcome (Lucas et al., 2020), detailed immunological profiling of post-COVID-19 patients is sparse. Our study is limited by the sample size. Therefore, we cannot report representative frequencies of post-COVID-19 manifestations and longitudinal monitoring and analysis of large cohorts of post-COVID-19 patients is warranted to find clear correlates with long-lasting symptoms after recovery.

Furthermore, we used the TICS-M that was originally developed to screen for MCI in elderly adults because we aimed to establish a tool that was validated for telephone interviews. However, our test results should be validated by neuropsychological tests that were established in young adults such as the Cambridge Automated Test Battery (Crooks et al., 2006). Furthermore, confounders for cognitive testing such as years of education and substance abuse were not assessed. However, we documented the patients’ profession and except for one participant who still visited high school all patients received at least 12years of education. Moreover, only two patients received detailed neuropsychological and neurological assessment that confirmed the results of our screening as well as cranial MRI and lumbar puncture to exclude other potential pathologies. However, we provide a clear description of the observed deficits and provide distinct symptoms that will instruct prospective screenings in larger cohorts to sensitively identify post-COVID-19 patients with cognitive deficits.

Together, the results of our study demonstrate that young patients who recovered from uncomplicated COVID-19 can have sustained neuropsychologic deficits that can be unmasked by targeted screening.

Supplementary material

Supplementary material is available at Brain Communications online.

Supplementary Material

Acknowledgements

Glossary

Contributor Information

Marcel S Woo, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

Jakob Malsy, Division of Infectious Diseases, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Jana Pöttgen, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

Susan Seddiq Zai, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

Friederike Ufer, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany. Department of Neurology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Alexandros Hadjilaou, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany. Department of Neurology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Stefan Schmiedel, Division of Infectious Diseases, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Marylyn M Addo, Division of Infectious Diseases, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. German Center for Infection Disease (DZIF), University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Christian Gerloff, Department of Neurology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Christoph Heesen, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany. Department of Neurology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Julian Schulze Zur Wiesch, Division of Infectious Diseases, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. German Center for Infection Disease (DZIF), University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.

Manuel A Friese, Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

References