Age determines the profile of cognitive impairment after COVID‐19. Results of an international, multi‐cohort, pooled analysis and meta‐analysis
Bibliographic record
Abstract
Abstract Background Evidence‐based data are still lacking to define de characteristics of cognitive impairment after COVI‐19. Previous findings suggest that Covid‐19 sequelae may resemble early Alzheimer’s disease (AD). In this abstract, our team present data from Argentina, Canada, Russia, Greece, and the UK including 1919 patients and 1031 controls. Method Participants were 18 to 97 years old. Neuropsychological evaluation included Montreal Cognitive Assessment – MoCA, Toronto Cognitive Assessment‐ TORCA, and/or batteries specially built for the evaluation of cognitive dimensions. Some cohorts included the anosmia. Participants were evaluated at a maximum of 6 months after discharge. A factorial analysis was performed on each country identifying 3 factors that could be compared between countries: one accounting for memory and language, the second is an attentional factor, and the last is a working memory factor. Between countries that have young population, there was a fourth factor accounting for executive functioning (planning and inhibition). We carried out meta‐analysis of common factors and co‐variates. Result Average duration of formal learning is 11.06 ± 5.11 years, and the mean age is 52.61 ± 15.87 years. Meta‐analysis revealed an impairment in language (verbal fluency) for all patients vs controls. Factorial scores revealed that all the participants were impaired in attentional tasks but those over 60 years old were impaired also in working memory and the youngest participants in executive functioning. Significant differences between cases and controls in attentional, memory, and language tasks identified 4 different groups: normal cognition (71%); one dimension impaired (20.5%); two dimensions impaired (6.5%); and three dimensions impaired (2%). In older adults, these proportions rise to 28% for the impairment in one dimension; 11.5% for two dimensions, and 3.5% for three dimensions and is significantly associated with the infection diagnoses (p = 0.013) and with presence and severity of anosmia (p = 0,000). Conclusion Older adults are at greater risk of suffering persistent cognitive impairment after recovery from SARS‐CoV‐2 infection and cognitive impairment is correlated with the presence and severity of anosmia.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.033 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".