Trajectories of Neurologic Recovery 12 Months After Hospitalization for COVID-19
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Little is known about trajectories of recovery 12 months after hospitalization for severe COVID-19. METHODS: We conducted a prospective, longitudinal cohort study of patients with and without neurologic complications during index hospitalization for COVID-19 from March 10, 2020, to May 20, 2020. Phone follow-up batteries were performed at 6 and 12 months after COVID-19 onset. The primary 12-month outcome was the modified Rankin Scale (mRS) score comparing patients with or without neurologic complications using multivariable ordinal analysis. Secondary outcomes included activities of daily living (Barthel Index), telephone Montreal Cognitive Assessment (t-MoCA), and Quality of Life in Neurologic Disorders (Neuro-QoL) batteries for anxiety, depression, fatigue, and sleep. Changes in outcome scores from 6 to 12 months were compared using nonparametric paired-samples sign test. RESULTS: = 0.003). Nonsignificant improvements occurred in fatigue, sleep, and depression scores in 48%, 48%, and 38% of patients, respectively. Barthel Index and mRS scores remained unchanged between 6 and 12 months in >50% of patients. DISCUSSION: At 12 months after hospitalization for severe COVID-19, 87% of patients had ongoing abnormalities in functional, cognitive, or Neuro-QoL metrics and abnormal cognition persisted in 50% of patients without a history of dementia/cognitive abnormality. Only fatigue severity differed significantly between patients with or without neurologic complications during index hospitalization. However, significant improvements in cognitive (t-MoCA) and anxiety (Neuro-QoL) scores occurred in 56% and 45% of patients, respectively, between 6 and 12 months. These results may not be generalizable to those with mild or moderate COVID-19.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".