In a recent study published in the journal Scientific Reports, researchers assess neuropsychological deficits among individuals with persistent symptoms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.
Study: Neuropsychological deficits in patients with persistent COVID-19 symptoms: a systematic review and meta-analysis. Image Credit: Creative Cat Studio / Shutterstock.com
Background
The coronavirus disease 2019 (COVID-19) has been established as a multi-organ illness with varied presentations, including neurological manifestations such as dizziness, headaches, hyposmia, hypogeusia, intracerebral bleeding, stroke, and encephalopathy.
Previous studies have reported neuropsychiatric alterations, such as mood disorders, anxiety, confusion, delirium, and agitation in COVID-19 patients. Neuropsychological deficits observed among SARS-CoV-2-infected individuals include executive and visuospatial functions, abstraction ability, working memory, and orientation based on the Montreal Cognitive Assessment (MoCA) scores.
Cognitive impairments have also been reported in COVID-19, regardless of disease severity, and could be due to the direct effects of SARS-CoV-2 on the central nervous system (CNS) or indirect CNS involvement and the associated multi-organ damage, generalized inflammation, hypoxia, or immunological dysregulation.
Importantly, these symptoms may persist beyond the acute phase of infection in a condition otherwise known as ‘long COVID.’
About the study
In the present meta-analysis, researchers examine the association between long COVID and neuropsychological symptoms following recovery from acute infection.
Data were searched in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Web of Science, Scopus, PubMed, Google Scholar, and PsycINFO databases between January 2020 and September 2021. References to the included articles and narrative or systematic reviews were also analyzed. Data were screened by two independent researchers, and disagreements were solved by discussion or consulting another researcher.
Random-effects modeling was performed to analyze the cognitive performance of post-COVID-19 patients and healthy individuals. The I2 statistic was used to assess heterogeneity in the included studies. Sensitivity analyses were also performed to determine whether excluding individual studies could impact the results.
Studies with confirmed COVID-19 patients diagnosed three weeks or more before study initiation were included in the analysis. Those with COVID-19-related conditions in the post-acute phase of infection undergoing standardized cognitive functional assessments were included in the analysis.
Additionally, studies with cohort, case-control, cross-sectional, case reports, case series, and quantitative-type study designs, as well as letters and preprints describing original research comprising data on individuals with suspected or laboratory-confirmed COVID-19, were also evaluated.
Studies assessing cognitive defects without validated assessments and those investigating the indirect effects of SARS-CoV-2 infections on mental well-being among uninfected individuals mediated by social distancing measures, including quarantine and isolation and without SARS-CoV-2-positive polymerase chain reaction (PCR) results were excluded from the analysis. All studies included in the meta-analysis had healthy control groups and reported global cognitive scores.
Conference presentation abstracts and studies comprising individuals with a history of pathologies that could impact cognitive function, including neurodegenerative illnesses, acquired brain damage, and neuropsychiatric disorders, were also excluded.
The quality of the included records was assessed using the Newcastle-Ottawa Scale (NOS). Bias risks were evaluated using the Risk of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool.
Long COVID increases risk of cognitive dysfunction
The initial search yielded 1,602 records, with citation searching providing an additional 20 records. A total of 338 duplicates were removed, whereas 978 records, including book chapters, guidelines, and protocols, were removed, after which 80 underwent full-text screening.
An additional 32 records that did not meet the eligibility criteria were removed, which included 14 records with inadequate data and nine opinion articles. Of the remaining 25 studies, six were considered for the meta-analysis.
The studies included in the meta-analysis comprised 175 COVID-19 convalescents and 275 healthy participants. Within the control group, 55% were women with a mean age of 53, whereas the experimental group comprised 51% of women with a similar mean age.
A medium-to-high effect size and a significantly moderate level of heterogeneity among studies, as demonstrated by I2 of 63%, were observed. COVID-19 convalescents showed significant cognitive deficits in comparison to controls. The sensitivity analysis showed similar findings, thus indicating the robustness of the primary analysis findings.
Conclusions
The study findings demonstrate that cognitive dysfunction was more prevalent among individuals with persistent symptoms of SARS-CoV-2 infection as compared to healthy individuals. These observations contribute to existing scientific literature; however, the lack of standardized protocols for cognitive evaluations at baseline might limit the accurate comparison of the results of the included studies.
Importantly, psychological, contextual, and socioeconomic factors and the impact of cognitive reserve affected by COVID-19 were not considered. Collectively, these factors may limit the ability of scientists to distinguish between the effects of infection on cognitive function and the overall influence of the pandemic.
Further research must carefully assess long-term cognitive decline among individuals with persistent symptoms of COVID-19 and rehabilitation intervention efficacy.
Journal reference:
- Sobrino-Relaño, S., Balboa-Bandeira, Y., Peña, J. et al. (2023). Neuropsychological deficits in patients with persistent COVID-19 symptoms: a systematic review and meta-analysis. Scientific Reports 13(10309). doi:10.1038/s41598-023-37420-6