Association of lipid levels with motor and cognitive function and decline in Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: Most studies have focused on comparing blood lipid biomarkers between Parkinson's disease (PD) and normal controls (NC). However, further research is necessary to explore the impact of blood lipid levels on motor and cognitive function, as well as the progression of motor dysfunction and cognitive decline over time. Thus, the aim of this study is to investigate the relationship between blood lipid biomarkers and these indicators in individuals with PD. METHODS: The cohort study enrolled 157 PD patients and 146 NC from the Tianjin Huanhu Hospital from September 2017 to September 2019. Serum lipid fractions were detected in fasting serum samples. PD patients were followed up at 2 ± 0.6 years for clinical assessment. RESULTS: PD patients exhibited lower serum triglyceride (TG) levels as compared to NC (P = 0.008). PD male patients exhibited lower serum lipoprotein cholesterol(LDL-C) and total cholesterol (TC) levels than female patients (LDL-C: P = 0.034; TC: P = 0.019). Serum TG levels correlated significantly with Unified PD Rating Scale III, Hoehn and Yahr stage and Montreal Cognitive Assessment scores in PD patients. Additionally, serum TG levels were associated with follow-up motor function decline and cognitive decline in adjusted regression models in PD patients. CONCLUSIONS: To summarise, the study findings suggest that decreased serum TG levels are significantly associated with greater motor dysfunction, cognitive dysfunction and the greater deterioration of the two indicators.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".