CANADIAN DEMENTIA PRIORITY SETTING PARTNERSHIP
Bibliographic record
Abstract
subsequent cognitive decline (Taniguchi et al., 2014).This longitudinal study aims to examine whether glycosylated hemoglobin (HbA1 c ) level is also predictive for cognitive decline.Methods: Among 1234 community-dwelling older adults aged 65 years or older who participated in health check-ups in Kusatsu town in Japan, 878 adults (mean age [SD], 71.8 [6.2] years; women 55.9%) were followed for a period up to seven years.We defined cognitive decline as a decrease of greater than 0.5 points per year on the MMSE.The Cox hazard model was applied for determining independent association of HbA1 c level with cognitive decline among adults aged 65-74 and 75 years or older, respectively, controlling for sex, age, alcohol drinking and smoking, history of chronic diseases, Geriatric Depression Scale-Short Form score, and APOE genotype.Results: During an average follow-up of 4.3 years, 168 adults (19.1%) developed cognitive decline.After controlling for important confounders, the hazard ratios for cognitive decline in the highest, third, and second quartiles of HbA1 c were 1.92 (95% confidence interval: 1.01-3.65),0.85 (0.40-1.80), and 1.06 (0.56-1.99), respectively, as compared with lowest quartile among adults aged 65-74.The association of HbA1 c level with cognitive decline was not significant among adults aged 75 years or older.Conclusions: A high HbA1 c level was an independent risk marker for subsequent cognitive decline of young-old, but not of old-old.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.238 | 0.053 |
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".