New‑onset non‑motor symptoms in patients with Parkinson's disease and post‑COVID‑19 syndrome: A prospective cross‑sectional study
Bibliographic record
Abstract
The clinical range of post-coronavirus disease 2019 (COVID-19) symptoms in patients with Parkinson's disease (PD) has not yet been thoroughly characterized, with the exception of a few small case studies. The aim of the present study was to investigate the motor and non-motor progression of patients with PD (PWP) and post-COVID-19 syndrome (PCS) at baseline and at 6 months after infection with COVID-19. A cross-sectional prospective study of 38 PWP+/PCS+ and 20 PWP+/PCS- matched for age, sex and disease duration was conducted. All patients were assessed at baseline and at 6 months using a structured clinicodemographic questionnaire, the Unified Parkinson's Disease Rating Scale Part III (the UPDRS III), the Montreal Cognitive Assessment, the Hoehn and Yahr scale, the Geriatric Depression Scale and the levodopa equivalent daily dose (LEDD). There was a statistically significant difference in the LEDD (P=0.039) and UPDRS III (P=0.001) at baseline and at 6 months after infection with COVID-19 between the PWP with PCS groups. The most common non-motor PCS symptoms were anosmia/hyposmia, sore throat, dysgeusia and skin rashes. There was no statistically significant difference in demographics or specific scores between the two groups, indicating that no prognostic factor for PCS in PWP could be identified. The novelty of the present study is that it suggests the new onset of non-motor PCS symptoms of PWP with a mild to moderate stage.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".