P2‐135: Progression of MRI markers and decline of cognitive performance over 10 years the 3C‐MRI‐Dijon study
Bibliographic record
Abstract
There are strong arguments in favour of brain MRI changes (such as atrophy and white matter lesions (WML)) that could significantly influence the risk of developing severe cognitive deterioration in the elderly. However, most of the evidence comes from studies that are cross-sectional or based on a single MRI assessment. In a large population-based study of non-demented elderly, followed-up over 10 years, with 2 MRI examinations, we investigated the longitudinal relationship between MRI marker progression and change in cognitive function over time. A sample of 1314 subjects aged 65 and over from the 3C-Dijon Study had two cerebral MRI 4 years apart. An automated method of detection and quantification of WML was developed. Voxel-Based Morphometry and region of interest methods were used to estimate brain volumes and hippocampal volume. Cognitive performances were assessed using a neuropsychological tests’ battery. To evaluate the relation between brain MRI markers evolution and change in cognitive function, we used a random-effect mixed model adjusting for age, gender, education level and total intracranial volume (TIV). Mean baseline WML volume was 5.3 cm (SD = 4.56) and rose +1.07 cm in 4 years. Mean hippocampal volume was 6.7 mm and decreased -0.25 mmin 4 years. Hypertensive subjects, older persons and those with history of cardiovascular disease had, on average, higher WML progression. Women, older persons, non hypertensive subjects and smokers had significantly higher hippocampal atrophy. Women, diabetic subjects and smokers had also higher total brain atrophy evolution over time. After controlling for potential confounders, each additional unit of WML progression, hippocampal and brain atrophy over time was associated, independently of each other, with higher cognitive decline in memory, verbal fluency and executive function. In a large population-based cohort of elderly, we found that WML increase, hippocampal volume decrease and higher atrophy rate over time were all associated with faster cognitive decline after adjusting for potential confounders. These results provide new potential targets for dementia prevention and could have implications for future preventive trials that could consider assessing serial MRI measurements and focusing on brain MRI markers as a potential surrogate marker.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".