Lower Blood Lipid Level Is Associated with the Occurrence of Parkinson’s Disease: A Meta‐Analysis and Systematic Review
Bibliographic record
Abstract
Background . The changes of blood lipid levels in patients with Parkinson’s disease (PD) and its clinical relevance remain unclear. We aimed to evaluate the potential association of blood lipid and the occurrence of PD, to provide evidence to the clinical treatment and nursing care of PD. Methods . We searched PubMed, Medline, Web of Science, Cochrane Library, Wanfang Database, Weipu Database, and China National Knowledge Infrastructure for studies related to the blood lipid levels and PD until November 30, 2021. Two researchers independently screened the literature and extricated the data including the levels of total cholesterol (TC), triglycerides (TG), high‐density lipoprotein cholesterol (HDL‐C), and low‐density lipoprotein cholesterol (LDL‐C). Newcastle‐Ottawa Scale (NOS) was used to evaluate the quality of included studies. RevMan5.3 and Stata 12.0 software were used for statistical processing and analysis. Results . A total of 15 cohort studies with 9740 participants involving 2032 PD patients and 7708 controls were included. Meta‐analysis indicated that TC (SMD = −0.29, 95% CI −0.55∼−0.03, P = 0.04), TG (SMD = −16.83, 95% CI −20.71∼−12.95, P < 0.001), HDL‐C (SMD = −0.14, 95% CI −0.26∼−0.02, P < 0.001) and LDL‐C (SMD = −0.26, 95% CI −0.50∼−0.01, P = 0.04) level in the PD patients was significantly lower than that of health controls. Sensitivity analysis indicated that the results were stable. No significant publication bias was found between the synthesized outcomes. Conclusions . Lower blood TC, TG, HDL‐C, and LDL‐C level are associated with the occurrence of PD. Limited by sample size and study population, further high‐quality, large‐sample clinical trials in different areas are needed to further determine the relationship between blood lipids and PD in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".