Cognitive function in recovered COVID-19 Lebanese patients with schizophrenia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: It remains unclear whether COVID-19 which is an infectious disease caused by the SARS-CoV-2 virus is associated with the deterioration of cognitive function among patients with schizophrenia. This study aimed to evaluate changes in cognitive function before and after COVID-19 and associated factors among patients with schizophrenia at the Psychiatric Hospital of the Cross (HPC). METHODS: A prospective cohort study was conducted among 95 patients with schizophrenia followed from mid-2019 until June 2021 at the Psychiatric Hospital of the Cross (HPC). This cohort was divided into a group diagnosed with COVID-19 (n = 71) and another not diagnosed with COVID-19 (n = 24). The questionnaire included the Brief Assessment of Cognition in Schizophrenia (BACS), Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale for Schizophrenia (CDSS), and Activities of Daily Living (ADL). RESULTS: The repeated-measures ANOVA showed no significant effect of time and the interaction between time and being diagnosed or not with COVID-19 on cognition. However, being diagnosed or not with COVID-19 had a significant effect on global cognitive function (p = 0.046), verbal memory (p = 0.046), and working memory (p = 0.047). The interaction between being diagnosed with COVID-19 and cognitive impairment at baseline was significantly associated with a higher cognitive deficit (Beta = 0.81; p = 0.005). Clinical symptoms, autonomy, and depression were not associated with the cognition (p > 0.05 for all). CONCLUSION: COVID-19 disease affected global cognition and memory: patients diagnosed with COVID-19 had more deficits in these domains than those without COVID-19. Further studies are necessary to clarify the variation of cognitive function among schizophrenic patients with COVID-19.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it