Neurofilament Light Chain as a Biomarker of Global Cognition in Individuals With Possible Vascular Mild Cognitive Impairment
Bibliographic record
Abstract
Background Neurofilament Light Chain (NfL) is a biomarker of axonal injury elevated in mild cognitive impairment (MCI) and Alzheimer’s disease dementia. Blood NfL also inversely correlates with cognitive performance in those conditions. However, few studies have assessed NfL as a biomarker of global cognition in individuals demonstrating mild cognitive deficits who are at risk for vascular-related cognitive decline. Objective To assess the relationship between blood NfL and global cognition in individuals with possible vascular MCI (vMCI) throughout cardiac rehabilitation (CR). Additionally, NfL levels were compared to age/sex-matched cognitively unimpaired (CU) controls. Method Participants with coronary artery disease (vMCI or CU) were recruited at entry to a 24-week CR program. Global cognition was measured using the Montreal Cognitive Assessment (MoCA) and plasma NfL level (pg/ml) was quantified using a highly sensitive enzyme-linked immunosorbent assay. Results Higher plasma NfL was correlated with worse MoCA scores at baseline ( β = −.352, P = .029) in 43 individuals with vMCI after adjusting for age, sex, and education. An increase in NfL was associated with worse global cognition ( b [SE] = −4.81[2.06], P = .023) over time, however baseline NfL did not predict a decline in global cognition. NfL levels did not differ between the vMCI (n = 39) and CU (n = 39) groups ( F (1, 76) = 1.37, P = .245). Conclusion Plasma NfL correlates with global cognition at baseline in individuals with vMCI, and is associated with decline in global cognition during CR. Our findings increase understanding of NfL and neurobiological mechanisms associated with cognitive decline in vMCI.
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 | 0.002 |
| 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 | 0.001 | 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".