GA to HbA1C ratio, but not HbA1C is associated with cognition in Chinese nondiabetic old adults
Bibliographic record
Abstract
OBJECTIVES: To investigate the relationship between glycated albumin (GA) to glycated hemoglobin (HbA1c) ratio and cognitive impairment in old age. Diabetes is associated with cognitive impairment in older people. However, the link between elevated GA/HbA1c levels and the risk of cognitive impairment in nondiabetic individuals is unclear. METHODS: A cross-sectional study of 474 old, nondiabetic adults (192 women, mean age 73.8 years ± 6.9 SD) who had been admitted to our hospital was conducted. Glycemic measures included fasting plasma glucose (FPG), 2-hour post-prandial plasmic glucose (2hPPG), GA and HbA1c. Cognitive function was assessed using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) at the same examination visit in which the glycemic measures were determined. RESULTS: When the individuals were divided into two groups according to the median of GA/HbA1c ratio, old adults with GA/HbA1c ratio ≥ 2.53 showed lower MMSE and MoCA scores compared to those with GA/HbA1c ratio < 2.53. Univariate regression analysis showed that MMSE and MoCA scores were not correlated with HbA1c, but were inversely correlated with GA and GA/HbA1c ratio. Linear regression analysis revealed that there was a significant negative correlation between GA/HbA1c and cognitive function (β = -0.77, P < 0.01 for MoCA and β = -0.69, P < 0.05 for MMSE) even after adjustment for age, body mass index, systolic blood pressure, lipoprotein(a) and sex. CONCLUSION: Our results indicate that even in the absence of manifest type 2 diabetes mellitus, GA/HbA1c ratio levels exert a negative influence on cognition and it may be a better predictor for cognitive impairment in the older population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".