RELATIONSHIO BETWEEN METABOLIC SYNDROME AND PARKINSON DISEASE PRODROMAL SYMPTOMS
Bibliographic record
Abstract
There is evidence that mechanisms involved in the systemic metabolic dysfunction that occur in Metabolic Syndrome (MS) and obesity, such as oxidative stress, inflammation caused by inadequate protein deposition, and changes in lipid pathways, have common elements with Parkinson's Disease (PD). The objective of this study was to investigate the frequency of MS in adult patients at basic health units in the city of Vitória de Santo Antão-PE, and relate it to possible symptoms experienced in the prodromal period of PD. This is a cross-sectional study, in which sociodemographic and blood data were collected to analyze the serum levels of fasting glucose, triglycerides, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol. The Epworth Sleepiness Scale, Patient Health Questionnaire-9, and the Montreal Cognitive Assessment were applied. In addition to performing anthropometry and measuring systemic blood pressure. A total of 179 individuals were evaluated, 78.8% female, with a mean age of 49.64 (±6.0) years. For the allocation of groups with and without MS, a sample of 89 volunteers with a mean age of 48.6 years (±5.8) was obtained, among which 71.7% were obese. The frequency of MS among those evaluated was 51.7% and there was a relationship between its components and prodromal symptoms of PD, such as excessive daytime sleepiness and mild cognitive impairment, both in individuals with MS and in those without the syndrome.
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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 | 0.000 | 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) | 0.002 | 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".