Cognitive inhibition deficit in long COVID-19: An exploratory study
Bibliographic record
Abstract
Background and objectives: An increasing number of research studies point toward the importance and prevalence of long-term neurocognitive symptoms following infection with COVID-19. Our objectives were to capture the prevalence of cognitive impairments from 1 to 16 months post-COVID-19 infection, assess the changes in neuropsychological functions over time, and identify factors that can predict long-term deficits in cognition. Methodology: A cross-sectional research design was adopted to compare four sub-samples recruited over a 16-month timeframe (1-4, 5-8, 9-12, and 13-16 months). Phone interviews were conducted at least 6 weeks after being infected by COVID-19. Sociodemographic and clinical questionnaires were administered followed by standardized neurocognitive and psychological tests and health questionnaires screening cognitive symptoms, anxiety, depression, fatigue, and autonomy. Results: Regarding general health questionnaires, 55.2% of the 134 participants had symptoms of psychiatric illness, while 21.6% of patients had moderate-to-severe anxiety or depression. Cognitive efficiency was diminished in 19.4% of our population. Executive dysfunction was screened in 56% of patients, and an impairment of cognitive flexibility and inhibition was revealed in 38.8%. Depression, hospital or intensive care unit (ICU) admission, and the duration of hospital or ICU stay were associated with an inhibition deficit. The duration elapsed from the initial infection, and the neurocognitive assessment was not associated with a decrease in inhibition deficit. The prevalence of cognitive impairments, other than inhibition deficit, tended to decrease during the study period. Discussion: This study supports the extensive literature on the cognitive and neuropsychiatric sequelae of COVID-19 and highlights long-lasting inhibition deficits, while other cognitive functions seemed to improve over time. The severity of infection could interact as a catalyst in the complex interplay between depression and executive functions. The absence of a relation between inhibition deficits and sociodemographic or medical factors reinforces the need for cognitive screening in all COVID-19 patients. Future research should focus on inhibition deficits longitudinally to assess the progression of this impairment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".