Cognition and Long COVID: A PRISMA Systematic Review of Longitudinal Studies
Bibliographic record
Abstract
INTRODUCTION: Long COVID is defined by National Institute for Health and Care Excellence (NICE) as the set of signs and symptoms that develop during or after a SARS-CoV-2 infection and continue for more than twelve weeks without any alternative diagnosis. One of the most frequent persistent symptoms reported by patients and verified in neuroimaging studies is cognitive dysfunction, due to a generalized hypoconnectivity and a diffuse axonal lesion in white matter. Therefore, the objectives of the present review are to determine how long cognitive functions remain affected during Long COVID and to explore which cognitive functions are most affected beyond three months of follow-up in patients up to 65 years of age without previous neuropsychological or psychiatric complications. METHODS: A systematic review was performed using PRISMA criteria and 11 articles were included through a comprehensive search of five different databases: PubMed, Medline, Scopus, WOS and ProQuest. The risk of bias of the articles was assessed using the Newcastle-Ottawa scale. RESULTS: Cognitive problems in Long COVID persist over time and improve slowly, although studies seem to agree that most areas improved significantly after one year. The cognitive functions that remained impaired the longest were processing speed and attention. CONCLUSIONS: These cognitive alterations cause a reduction in the quality of life of the patients and a reduction in work capacity and manifest the need for a cognitive intervention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".