Neuropsychological Outcomes in Adult Patients and Survivors of COVID-19
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is believed to affect central nervous system functions through various indirect, and possibly direct, mechanisms. We are only now beginning to understand the possible effects of the virus on human cognition. This review summarizes extant yet limited literature on clinical neuropsychological findings in adult coronavirus disease 2019 (COVID-19) patients and survivors. Neuropsychological outcomes were often in the form of cognitive screen results, although various studies administered comprehensive batteries. With respect to screens, the Montreal Cognitive Assessment appeared relatively sensitive to cognitive dysfunction associated with COVID-19. Patients and survivors presented with weaknesses on screens and comprehensive batteries, although the pattern of these weaknesses was not specific to etiology. Broadly, weaknesses were suggestive of executive dysfunction, although more than one study did not detect significant impairment. Weaknesses should be interpreted cautiously due to potential confounds/contributing factors (weaknesses may partly reflect psychiatric sequelae; weaknesses may be over-interpreted due to inadequate assessment of premorbid functioning). Studies reported different approaches in defining impairment, likely contributing to variable findings. The current review discusses ongoing efforts to harmonize approaches to evaluating neuropsychological functioning globally, as well as emphasizes taking a comprehensive approach towards understanding how the disease affects cognition.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".