Exploring the relationship of cognitive function with and without COVID-19 recovered schizophrenic patients
Bibliographic record
Abstract
Background The Coronavirus disease 2019 (COVID-19) is linked to the deterioration of cognitive function among individuals suffering from schizophrenia. The purpose of this study was to compare the cognitive performance of schizophrenic patients before and after COVID-19. Methods A longitudinal cohort study involving a sample of 219 individuals diagnosed with schizophrenia was enrolled between June 2022 and May 2023. The participants were split into two groups infected with COVID-19 (n = 165) and not infected with COVID-19 (n = 54). The data were gathered via a questionnaire on demographic characteristics, the Brief Assessment of Cognition in Schizophrenia (BACS), the Positive and Negative Syndrome Scale (PANSS), the Calgary Depression Scale for Schizophrenia (CDSS), the Activities of Daily Living (ADL) scale, and the Insomnia Severity Index (ISI). Results The repeated-measures ANOVA showed that Among patients diagnosed with COVID-19, there was a deterioration in global cognitive function (before COVID-19 = −2.45 vs. after COVID-19 = −3.02, p = 0.007), working memory (before COVID-19 = −2.76 vs. after COVID-19 = −3.34, p < 0.00 1), motor speed (before COVID-19 = −1.64 vs. after COVID-19 = −2.12, p < 0.001), attention and speed of information processing (before COVID-19 = −1.93 vs. after COVID-19 = −1.16, p = 0.008). multi-variable analysis showed that several factors as having a secondary grade of education (β = 0.434), experiencing insomnia (β = 0.411)and the interaction between COVID-19 diagnosis and cognition at baseline (β = 0.796) were significantly associated with cognitive deficits. At the same time, no significant associations were found between global cognition and clinical symptoms, autonomy, or depression (p > 0.05). Conclusion The COVID-19 pandemic has significantly impacted various cognitive functions, such as verbal memory, working memory, and global cognition. Insomnia has been identified as the predominant determinant of cognitive impairment, alongside the confirmation of a COVID-19 diagnosis. Additional research is imperative to elucidate the diversification of cognitive functionality observed in individuals diagnosed with schizophrenia who have acquired COVID-19.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".