Association between metabolic syndrome and cognitive decline: a systematic review of prospective population-based studies
Bibliographic record
Abstract
OBJECTIVE: The association between metabolic syndrome (MS) and the risk of cognitive impairment or dementia remains unclear. In this article, we systematically review studies on the risk of cognitive disorders in patients with MS to determine the strength of the association between MS and cognitive decline. METHODS: Electronic databases through December 2009 were searched to identify prospective population-based studies that examined the association between MS and risk of cognitive disorders. Two reviewers used a standardised form to collect data and assess eligibility. The quality of study was assessed by the Newcastle-Ottawa Scale. RESULTS: We found nine eligible studies that involve 19 876 participants. All studies but two indicate that MS is associated with cognitive decline (from one-fold to more than two-fold increase in risk). It seems that MS may be associated with cognitive impairment (positive results in three of five) and vascular dementia (positive results in two of three), whereas three studies involving patients with Alzheimer's disease (AD) did not find the association between MS and AD. When examining the association of the individual risk factors of the MS and cognition in seven eligible studies, glucose (three studies) and hypertension (three studies) showed positive results associated with cognitive decline. CONCLUSION: The MS may be associated with cognitive impairment and vascular dementia but not for AD, which need to be further investigated with high-quality studies.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".