Scope on triglyceride levels in elderly patients with dementia versus controls: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: Triglyceride levels vary among elderly patients with dementia. In this study, triglyceride levels were examined to demonstrate whether they increase or decrease in elderly dementia patients and other elderly individuals, whether there is a difference between elderly individuals with different forms of dementia and controls, and whether that difference is considered significant. Methods and materials: This analysis was performed via searching in Scopus, Web of Science, and Pubmed. A PRISMA checklist was followed to conduct the systematic review. The quality assessment was assessed by the Newcastle-Ottawa for case-control studies. Meta-analysis was performed by SPSS, Version 28. Results: Twenty-five studies consisting of 18943 cases and 212144 controls were included in the final analysis. Eighteen studies showed that the triglyceride levels in both patients and controls did not exceed the normal range (1.7 mmol/L or 150 mg/dl). A meta-analysis was also performed for the seven studies that revealed that triglyceride levels exceeded the normal range and no significant difference was found between the cases and controls (p-value =0.18, 95% CI). Conclusion: Triglyceride levels may not be a serious factor that should be considered in dementia, which differs from other areas of medicine, such as cardiovascular diseases.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.022 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".