Cognitive sequelae of long COVID may not be permanent: A prospective study
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
BACKGROUND AND PURPOSE: Cognitive decline is a recognized manifestation of long COVID, even among patients who experience mild disease. However, there is no evidence regarding the length of cognitive decline in these patients. This study aimed to assess whether COVID-19-related cognitive decline is a permanent deficit or if it improves over time. METHODS: Cognitive performance was evaluated by means of the Montreal Cognitive Assessment (MoCA) in COVID-19 survivors and noninfected individuals. All study participants had four cognitive evaluations, two of them before the pandemic and the other two, 6 and 18 months after the initial SARS-CoV-2 outbreak infection in the village. Linear mixed effects models for longitudinal data were fitted to assess differences in cognitive performance across COVID-19 survivors and noninfected individuals. RESULTS: The study included 78 participants, 50 with history of mild COVID-19 and 28 without. There was a significant-likely age-related-decline in MoCA scores between the two prepandemic tests (β = -1.53, 95% confidence interval [CI] = -2.14 to -0.92, p < 0.001), which did not differ across individuals who later developed COVID-19 when compared to noninfected individuals. Six months after infection, only COVID-19 survivors had a significant decline in MoCA scores (β = -1.37, 95% CI = -2.14 to -0.61, p < 0.001), which reversed after 1 additional year of follow-up (β = 0.66, 95% CI = -0.11 to 1.42, p = 0.092). No differences were noticed among noninfected individuals when both postpandemic MoCA scores were compared. CONCLUSIONS: Study results suggest that long COVID-related cognitive decline may spontaneously improve over time.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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