Relationship between autonomic nervous function and cognitive function in elderly patients with Parkinson's disease
Bibliographic record
Abstract
Objective To analyze relationship between autonomic nervous function and cognitive function in elderly patients with Parkinson's disease (PD). Methods A total of 130 elderly patients with PD admitted to The Affiliated Brain Hospital of Nanjing Medical University from January 2020 to December 2022 were included. Hoehn‑Yahr staging was used to evaluate stage of the disease, Unified Parkinson's Disease Rating Scale Ⅲ (UPDRS Ⅲ) was used to evaluate the severity of motor disorders, Scales for Outcomes in Parkinson's Disease ‑ Autonomic (SCOPA ‑ AUT) was used to evaluate autonomic nervous function, Mini‑Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to evaluate cognitive function, Non‑Μotor Symptoms Scale (NMSS) was used to evaluate the severity of nonmotor symptoms. Results According to whether the patients were accompanied by Alzheimer's disease (AD), they were divided into a group with AD (n = 82) and a group without AD (n = 48). The proportion of Hoehn‑Yahr staging 3 to 5 (χ2 = 5.689, P = 0.017), UPDRSⅢ score (t = 21.490, P = 0.000), SCOPA‑AUT score (t = 21.330, P = 0.000), dysregulation of body temperature (χ2 = 8.512, P = 0.004), urinary dysfunction (χ2 = 17.270, P = 0.000), gastrointestinal dysfunction (χ2 = 24.471, P = 0.000), dysregulation of pupil (χ2 = 5.299, P = 0.021), cardiovascular dysfunction (χ2 = 15.355, P = 0.000) and NMSS score (t = 32.309, P = 0.000) in the group with AD were higher than those in the group without AD, the MMSE (t = 4.730, P = 0.000) and MoCA (t = 6.840, P = 0.000) total scores and subtype scores (P = 0.000, for all) in the group with AD were lower than those in the group without AD. Correlation analysis showed that the SCOPA‑AUT score of PD patients with AD was negatively correlated with MMSE and MoCA total scores and subtype scores (P = 0.000, for all). Conclusions The autonomic dysfunction of elderly PD patients with AD is more serious, and the autonomic nervous function is closely related to cognitive function.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".