[Clinical characteristics in Parkinson's disease patients with cognitive impairment and effects of cognitive impairment on sleep].
Bibliographic record
Abstract
OBJECTIVE: To analyze the clinical characteristics, correlation factors and clinical heterogeneities in Parkinson's disease (PD) patients with cognitive impairment and identify whether cognitive impairment could influence the aspect of sleep. METHODS: A total of 130 PD outpatients and inpatients of sleep center at our hospital were eligible for participation. According to Montreal cognitive assessment (MOCA), they were divided into cognitive normal group (MOCA ≥ 26) (n = 51) and cognitive impairment group (MOCA < 26) (n = 79). Their clinical characteristics were mainly evaluated by unified Parkinson's disease rating scale (UPDRS) , Hoehn-Yahr (H-Y) stage, Hamilton depression scale (HAMD-24 item) and Epworth sleepiness scale (ESS). And all of them underwent video-polysomnography (PSG). RESULTS: The proportion of cognitive impairment (MOCA < 26) was 60.76%. Compared to those without cognitive impairment, the PD patients with cognitive impairment had significantly higher score of HAMD (10 ± 7 vs 7 ± 4), increased incidence of hallucinations (40.50% vs 19.60%) and REM behavior disorders (RBD) (63.29% vs 39.21%), significantly higher H-Y stage [2.5(2.0-3.0) vs 2.0 (2.0-2.5)] , United Kingdom Parkinson Disease Society (UPDRS) part III (22 ± 10 vs 19 ± 10) and levodopa-equivalent daily dose (LED) (511 ± 302vs 380 ± 272) (all P < 0.05). However, no significant differences existed in the subscores of MOCA between PD patients with different sides of onset and motor subtypes of onset (all P > 0.05). Non-conditional Logistic regression analysis showed that PD duration, score of HAMD and H-Y stage were the major influencing factors of cognition. On PSG, significantly decreased sleep efficiency (57% ± 21% vs 66% ± 17%), higher percentage of non-REM sleep stage 1 (NREMS1) (37% ± 21% vs 27% ± 13%), lower percentage of NREMS2 (40% ± 17% vs 46% ± 13%) and REM sleep (39% ± 28% vs 54% ± 36%) were found for PD patients with cognitive impairment (all P < 0.05). CONCLUSION: The PD patients with cognitive impairment have more severe disease and partial nonmotor symptoms. And the severity of disease and depression is closely associated with cognitive impairment. Cognitive impairment may also affect sleep to cause decreased sleep efficiency and severe sleep structure disorder.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".