Lack of detailed severity stratification
The lack of detailed severity stratification beyond hospitalization status limits the ability to fully understand the impact of COVID-19 severity on brain changes.
Relying on self-reported or routinely collected medical records for COVID-19 diagnosis introduces potential misclassification and information bias.
Varied diagnostic accuracy of antibody tests
The reliance on antibody lateral flow tests for some cases and controls raises concerns about diagnostic accuracy and potential misclassification.
The limited ethnic diversity of the sample restricts the generalizability of the findings to other populations.
Potential misclassification bias
The potential misclassification of cases and controls based on testing limitations could bias the results towards the null hypothesis.
Observational study design
The observational nature of the study limits causal inferences, although the longitudinal design strengthens the analysis.
Lack of variant information
The absence of data on specific SARS-CoV-2 variants makes it impossible to assess the impact of different strains on brain changes.
The relatively short follow-up period makes it difficult to determine the long-term effects of SARS-CoV-2 infection on the brain.
Missing baseline cognitive data
The lack of pre-infection cognitive data for all participants makes it challenging to interpret changes in cognitive function.
Potential unmeasured confounding
The potential for unmeasured confounding cannot be entirely ruled out in observational studies.