Predictive value of vitamin B2, S-adenosylmethionine, and homocysteine for age-related cognitive decline in elderly patients
Bibliographic record
Abstract
Objective To explore the predictive value of vitamin B2 (VB2), S-adenosylmethionine (SAM), and homocysteine (Hcy) for age-related cognitive decline in elderly patients (≥60 years old). Methods A total of 142 hospitalized elderly patients from Department of Geriatrics, the Affiliated Hospital of Xuzhou Medical University, between December 2023 and June 2024 were included. Their cognitive function was assessed through the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). According to the presence of cognitive impairment, the patients were divided into two groups: an age-related cognitive impairment (ARCI) group and a healthy control (HC) group. Correlation analysis was conducted to explore the relationship between MMSE and MoCA scores, and folate metabolites. Furthermore, stratified multiple linear regression analysis was performed to assess the impact and predictive value of folate metabolites on cognitive function. Results Significant differences were observed between the ARCI group and the HC group in terms of age, education level, total bilirubin, direct bilirubin, total bile acids, TAU-181, Aβ1-42 levels, total albumin, MMSE, and MoCA scores (P<0.05). Correlation analysis showed that MMSE and MoCA scores were positively correlated with serum VB2 (r=0.354, 0.314; P<0.001), VB9 (r=0.345, 0.355; P<0.001), and SAM (r=0.424,0.399; P<0.001) levels, and negatively correlated with Hcy (r=-0.363, -0.325; P<0.001) levels. Stratified multiple linear regression analysis revealed that VB2, SAM, and Hcy were predictors of cognitive decline (P<0.01), explaining 45.9% of the variance in MMSE scores (F=9.05, P<0.001, R2=0.459) and 42.7% of the variance in MoCA scores (F=10.375, P<0.001, R2=0.427). Conclusions VB2, SAM, and Hcy have significant predictive value for age-related cognitive decline in the elderly population and can provide reference for early risk assessment.
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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) | 0.001 | 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".