Plasma p-tau markers and vascular factors are associated with cognitive decline and clinical progression in the CIMA-Q cohort
Bibliographic record
Abstract
ABSTRACT Introduction We compared associations between phosphorylated tau biomarkers (p-tau217, p-tau181, p-tau231) and vascular risk factors with clinical progression and cognitive decline along the AD continuum. Methods Baseline plasma p-tau concentrations and vascular risk factors were assessed in 280 CIMA-Q participants. Associations between these markers, cognition and clinical progression over 8 years were examined. Results Elevated p-tau217 predicted progression from mild cognitive impairment (MCI) to AD dementia ( p <.01), while hypertension predicted progression from cognitively unimpaired (CU) to MCI ( p <.02). Higher p-tau levels, particularly p-tau217, and hypertension were linked to cognitive decline in MCI individuals. In the CU group, few associations were seen between p-tau levels and cognitive decline, with minimal effect of vascular risk factors. Discussion Plasma p-tau217 was the most sensitive marker of AD-related decline, but hypertension was particularly relevant at earlier stages. The results highlight the need for multimodal profiling to optimize prediction and intervention along the AD continuum.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".