Effect of Frailty and Age on Platelet Aggregation and Response to Aspirin in Older Patients with Atrial Fibrillation: A Pilot Study
Bibliographic record
Abstract
INTRODUCTION: Frailty is associated with changes in inflammation, coagulation, and possibly platelet function. Aspirin is still prescribed for stroke prevention in older patients with atrial fibrillation, although not recommended by current guidelines. In frail older people, it is unclear whether platelet aggregability and response to aspirin are altered. This study aims to investigate the effects of frailty and chronological age on platelet aggregability and on responses to aspirin in older patients with atrial fibrillation. METHODS: Inpatients with atrial fibrillation aged ≥65 years were recruited from a tertiary referral hospital in Sydney, Australia. Frailty was determined using the Reported Edmonton Frail Scale. Platelet aggregation studies were performed using whole blood impedance aggregometry. RESULTS: Data from 115 participants were analyzed (mean age 85 ± 6 years, 41% female, 52% frail). Spearman correlation coefficients found no significant associations of platelet aggregation with chronological age or with frailty score. Comparison between frail and non-frail groups showed that there was no impact of frailty status on aggregation assays amongst participants who were not taking any antiplatelet drugs. Amongst participants taking aspirin, the frail had higher adjusted arachidonic acid agonist (ASPI) test measures (AU per platelet) than the non-frail (0.11 ± 0.11 vs. 0.05 ± 0.04; p = 0.04), suggesting that in frail participants, platelet aggregation is less responsive to aspirin than in non-frail. CONCLUSIONS: We found no effect of chronological age or frailty status on platelet aggregation amongst older patients with atrial fibrillation in this pilot study. However, frailty could be associated with reduced aspirin responsiveness among older patients with atrial fibrillation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".