Cognitive impairment in COVID‐19 Survivors: Analysis and Extensions on Population Studies in Greece
Bibliographic record
Abstract
Abstract Background The aim of our study was to investigate the prevalence and associations of cognitive impairment in COVID‐19 survivors in the post‐acute setting. Method Our study is conducted in three post‐COVID‐19 outpatient clinics in tertiary hospitals in Greece. Eligible subjects included previously hospitalized COVID‐19 survivors with mild to moderate disease, returning for follow‐up at least two months post‐discharge. Exclusion criteria included intensive care unit admission, intubation, a history of neurodegenerative disease and other significant comorbidities. Study measurements included demographics, clinical evaluation, medical, family history, anthropometrics, 6‐minute walk test (6MWT), 30 seconds sit‐to‐stand (30STS), handgrip strength, spirometry, Pittsburgh Sleep Quality Index (PSQI), the Montreal Cognitive Assessment (MoCA), reactive oxygen metabolites (dROMs) and plasma antioxidant capacity (PAT). Cognitive impairment was considered on MoCA ≤24. Result 142 COVID‐19 survivors were included in the study (110 Male, 32 Female; Mean age of 56.16±10.92). A total of 47.2% presented with cognitive decline (CD) as indicated by a MoCA score ≤24. Cognitive decline prevalence by SARS‐CoV‐2 variant of concern (VOC) was 39.5%, 50% and 62.5% for Alpha, Beta and Delta, correspondingly. A binary logistic regression model controlling for age, gender and VOC indicated that the diffusing capacity for carbon monoxide (DLCO) was independently associated with MoCA ≤24 (p = 0.014, OR = 0.669, 95%CI: 0.484‐0.923). Compared to severe untreated OSAS (n = 28), distinct domains but similar prevalence of cognitive impairment was noted. Conclusion Diffusion capacity abnormalities for carbon monoxide in COVID‐19 survivors as noted in other studies, may be implicated in the development of cognitive 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".