Exploring the impact of cognitive dysfunction, fatigue, and shortness of breath on activities of daily life after COVID-19 infection, until 1-year follow-up
Bibliographic record
Abstract
OBJECTIVE: Despite expanding knowledge on COVID-19, the long-term effects on daily-life activities remain unclear. The prevalence and changes in fatigue, cognitive dysfunction, and activity limitations in the first year after COVID-19 infection in hospitalized and non-hospitalized patients were explored. SUBJECTS: A total of 122 patients were recruited from hospital care and 90 from primary care. METHOD: Baseline data comprised the Montreal Cognitive Assessment and Trail Making Test. Participants were followed up at 3 and 12 months using these tests and a semi-structured interview to identify symptoms and how they affected participation in daily-life activities. Both within- and between-group analyses were performed to explore changes over time and compare groups. RESULT: High levels of fatigue and cognitive dysfunction were found in both groups, which persisted for 12 months. A significant impact on daily-life activities was also observed, with marginal change at the 12-month follow-up. The hospital care group performed worse than the primary care group in the cognitive tests, although the primary care group perceived a higher level of fatigue and cognitive dysfunction. Activity limitations were higher in the primary care group than in the hospital care group. CONCLUSION: These findings highlight the need for long-term follow-up and further investigation of the impact of persistent deficits on rehabilitation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".