Correlation between the time from rapid eye movement sleep behavior disorder to disease onset and clinical characteristics in Parkinson's disease
Bibliographic record
Abstract
Objective To study the correlation between the time from rapid eye movement sleep behavior disorder (RBD) to disease onset and the clinical characteristics of Parkinson's disease (PD). Methods A total of 123 PD patients were recruited from Tianjin Huanhu Hospital between September 2019 and December 2021. All participants were divided into the group with RBD (41 cases) and the group without RBD (82 cases) according to the probable RBD criteria. Hoehn ⁃Yahr staging was used to evaluate PD grade. Unified Parkinson's Disease Rating Scale Ⅲ (UPDRS Ⅲ) was used to evaluate the motor function of PD. Mini⁃Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Rating Scale (HAMA) and Hamilton Depression Rating Scale (HAMD), Parkinson's Disease Sleep Scale (PDSS), and Non ⁃ Motor Symptom Scale (NMSS) were used to evaluate cognitive function, anxiety, depression, sleep and total non ⁃ motor symptoms. The life quality of patients was evaluated by 39 ⁃ Item Parkinson's Disease Questionnaire (PDQ ⁃ 39). Spearman rank correlation analysis was used to explore the correlation between the time from RBD to disease onset and clinical characteristics in PD. Results UPDRS Ⅲ (t = ⁃ 2.703, P = 0.008) and NMSS (t = ⁃ 2.176, P = 0.032) scores of PD with RBD group were higher than those of the PD without RBD group. The time from the RBD to the onset of PD was posit correlated with NMSS score (rs = 0.547, P = 0.001). Conclusions The motor and non ⁃ motor symptoms in PD patients with RBD are more severe than those of patients without RBD. Early onset of RBD in prodromal period may indicates more severe non⁃motor symptoms in future.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".