Coffee Consumption Correlates With Better Cognitive Performance in Patients With a High Incidence for Stroke
Bibliographic record
Abstract
Background Atrial fibrillation is an independent risk factor for the development of cognitive impairments. Regular coffee consumption has shown cognitive benefits in healthy individuals. Whether regular consumption reduces cognitive decline in vulnerable patients is controversial. We investigated the association in elderly people with atrial fibrillation. Methods and Results Daily coffee consumption was assessed using a structured nutrition questionnaire, and cognitive function was evaluated by a detailed neurocognitive‐test‐battery, including the Montreal Cognitive Assessment, Trail‐Making Test, semantic fluency, and Digit‐Symbol‐Substitution Test. The cognitive construct score combines all neurocognitive tests mentioned and provides an overall cognitive performance indicator. Hs‐CRP (high‐sensitivity C‐reactive protein) and IL‐6 (interleukin‐6) were measured to explore an association with inflammation. Results were estimated using linear mixed‐effects‐models with detailed adjustments for confounders. The <1 cup/day consumers (reference group) reached a cognitive construct score of −0.24 (95% CI, –0.27 to –0.16), and the group with the highest consumption (>5 cups/day) was at −0.10 (95% CI, –0.10 to 0.04; p =0.048). Montreal Cognitive Assessment score in the reference group was 24.58 (95% CI, 24.58–25.32); the group with the highest intake achieved 25.25 (95% CI, 24.98–26.85; p =0.163). Inflammatory markers decreased with higher coffee consumption (hs‐CRP with 5 compared with <1 cup/day by factor 0.78 [95% CI, 0.54–1.13], p = 0.188, IL‐6 significantly by factor 0.73 [95% CI, 0.57–0.95], p =0.017). Conclusions Coffee consumption in patients with atrial fibrillation may be associated with improved cognitive performance and reduced inflammatory markers. Further research is needed to confirm these findings and to consider implementation in dietary counseling for atrial fibrillation management. Registration URL: https://www.clinicaltrials.gov ; Identifier: NCT02105844.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".