Neuropsychological outcome of indoor rehabilitation in post-COVID-19 condition—results of the PoCoRe study
Bibliographic record
Abstract
Background Post COVID-19 condition (PCC) is increasingly recognized as a debilitating condition characterized by persistent symptoms following SARS-CoV-2 infection. Neuropsychological deficits, including cognitive impairments and fatigue, are prevalent in individuals with PCC. The PoCoRe study aimed to evaluate the burden of neuropsychological deficits in PCC patients undergoing multidisciplinary indoor rehabilitation and to describe possible changes in this symptomatology. Methods The PoCoRe study, a prospective, non-randomized, controlled longitudinal study, recruited PCC patients from six German indoor rehabilitation centers. Eligible participants underwent comprehensive neuropsychological assessments at admission and discharge. Various measures were employed, including the fatigue scale for motor functioning and cognition (FSMC), the Test Battery for Attention (TAP) and the Montreal Cognitive Assessment (MoCA). Results Out of the 1,086 recruited participants, a total of N = 701 participants were included in the main data analysis. The prevalence of fatigue on admission was high (84.6%) and decreased significantly by discharge (77.4%), with a mild effect size. Reaction times on the alertness subtest were abnormal in 70% of patients on admission and 50% on discharge. Sustained attention was abnormal in 55% of patients on admission, decreasing to 43% on discharge. These differences were significant with mild effect sizes. Furthermore, of the 27% of participants with pathological MoCA scores at admission, 63% improved to normative levels during rehabilitation, indicating a significant treatment effect (p ≤ 0.001). However, the MoCA demonstrated limited sensitivity in detecting attention deficits. Conclusion The PoCoRe study highlights the high prevalence of neuropsychological deficits and fatigue in PCC patients, with notable improvements observed following multidisciplinary rehabilitation. Challenges remain in accurately identifying and addressing these deficits, underscoring the importance of comprehensive neuropsychological assessment and tailored rehabilitation interventions. Further research is warranted to optimize screening tools and enhance neuropsychological care for PCC patients in both rehabilitation and outpatient settings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".