Correlation analysis of peripheral platelet markers and disease phenotypes in Alzheimer's disease
Bibliographic record
Abstract
INTRODUCTION: Platelets serve as the primary peripheral reservoir of amyloid beta (Aβ). However, there is limited research on platelet markers in routine blood examinations, particularly with regard to the large platelet ratio (P-LCR) in Alzheimer's disease (AD). METHODS: This study included 512 AD patients and 205 healthy controls (HCs). Platelet markers and apolipoprotein E (APOE) 4 status were assessed in all participants. RESULTS: The study revealed that P-LCR was significantly elevated in AD patients compared to HCs. In AD patients carrying APOE4, P-LCR significantly negatively correlated with Montreal Cognitive Assessment scores. There was an observed increasing trend in the rate of change in P-LCR with disease progression. Binary logistic regression analysis indicated that P-LCR may constitute a risk factor for AD, after adjusting for age, sex, APOE4, and body mass index. DISCUSSION: P-LCR is associated with disease severity in AD patients carrying APOE4. P-LCR may be a promising marker to reflect platelet activity in AD patients. HIGHLIGHTS: P-LCR significantly negatively correlated with MoCA scores in AD patients with APOE4. The rate of change in P-LCR showed an increasing trend with disease progression. P-LCR may be a risk factor for AD.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".