Executive function deficit in patients with long COVID syndrome: A systematic review
Bibliographic record
Abstract
Background: Post-COVID-19 condition (Long COVID) refers to a condition in which patients endure persistent symptoms for more than 12 weeks, typically occurring at least 3 months after the onset of Coronavirus disease 2019 (COVID-19) infection. It occurs when a constellation of symptoms persists following the initial illness, and this may obstruct a daily routine and impose difficulty in life. Therefore, this study aimed to systematically review published articles assessing the neurocognitive profile of long COVID patients, with a specific emphasis on executive function (EF), and to determine the correlation between EF deficits and brain alterations through the utilisation of neuroimaging modalities. Methods: A thorough search was conducted using the PubMed/MEDLINE and Web of Science online databases following the PICOS and PRISMA 2020 guidelines. All included studies were deemed to be of high quality according to the Newcastle-Ottawa Scale (NOS). Results: A total of 31 out of 3268 articles were included in the present study. The main outcome is the proportion of individuals with cognitive deficits, particularly in the EF domain, as detected by neuropsychological assessments. The present study also revealed that EF deficits in long COVID patients are correlated with disruptions in the frontal and cerebellar regions, affecting processes such as nonverbal reasoning, executive aspects of language, and recall. This consistent disturbance also emphasised the correlation between EF deficits and brain alterations in patients with long COVID. Conclusion: The present study highlights the importance of evaluating EF deficits in long COVID patients. This insight has the potential to improve future treatments and interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".