Neurological outcomes 1 year after COVID‐19 diagnosis: A prospective longitudinal cohort study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Neurological sequelae from coronavirus disease 2019 (COVID-19) may persist after recovery from acute infection. Here, the aim was to describe the natural history of neurological manifestations over 1 year after COVID-19. METHODS: A prospective, multicentre, longitudinal cohort study in COVID-19 survivors was performed. At a 3-month and 1-year follow-up, patients were assessed for neurological impairments by a neurological examination and a standardized test battery including the assessment of hyposmia (16-item Sniffin' Sticks test), cognitive deficits (Montreal Cognitive Assessment < 26) and mental health (Hospital Anxiety and Depression Scale and Post-traumatic Stress Disorder Checklist 5). RESULTS: Eighty-one patients were evaluated 1 year after COVID-19, out of which 76 (94%) patients completed a 3-month and 1-year follow-up. Patients were 54 (47-64) years old and 59% were male. New and persistent neurological disorders were found in 15% (3 months) and 12% (10/81; 1 year). Symptoms at 1-year follow-up were reported by 48/81 (59%) patients, including fatigue (38%), concentration difficulties (25%), forgetfulness (25%), sleep disturbances (22%), myalgia (17%), limb weakness (17%), headache (16%), impaired sensation (16%) and hyposmia (15%). Neurological examination revealed findings in 52/81 (64%) patients without improvement over time (3 months, 61%, p = 0.230) including objective hyposmia (Sniffin' Sticks test <13; 51%). Cognitive deficits were apparent in 18%, whereas signs of depression, anxiety and post-traumatic stress disorders were found in 6%, 29% and 10% respectively 1 year after infection. These mental and cognitive disorders had not improved after the 3-month follow-up (all p > 0.05). CONCLUSION: Our data indicate that a significant patient number still suffer from neurological sequelae including neuropsychiatric symptoms 1 year after COVID-19 calling for interdisciplinary management of these patients.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it