Cognitive Function and Anticoagulation Control in Patients With Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: Patients with atrial fibrillation usually are elderly and may have cognitive dysfunction. These patients may receive less effective oral anticoagulation, resulting in more vascular events and bleeding. METHODS AND RESULTS: In an analysis of cognitive function associated with the time in therapeutic range (TTR) in the Atrial Fibrillation Clopidogrel Trial With Irbesartan for Prevention of Vascular Events, 2510 patients (mean age, 71+/-9.5 years) from 27 countries completed the Mini-Mental State Examination (MMSE). Of these patients, 171 (6.8%) had an MMSE score <24, suggesting dementia, and 194 (7.7%) had intermediate scores of 24 to 25. Low MMSE scores were correlated with a low TTR. Even mild cognitive impairment was associated with a TTR below the median (<65%). Patients with an MMSE score <26 had more vascular events (6.7% versus 3.6% per 100 patient-years; P=0.002) and more bleeding (9.6% versus 7% per 100 patient-years; P=0.04). After controlling for TTR, the MMSE no longer conferred increased risk, suggesting that if improved anticoagulation was provided, vascular events and bleeding would be reduced. Other independent factors associated with a TTR <65% were region of the world, recent initiation of vitamin K antagonist, type of anticoagulant, and concurrent use of amiodarone or insulin. After adjustment for these factors, lower MMSE scores still predicted a reduced TTR. CONCLUSIONS: Cognitive dysfunction is common in elderly patients with atrial fibrillation and is related to less effective anticoagulation and more vascular events. The MMSE identifies patients with atrial fibrillation in whom extra efforts are needed to maintain effective anticoagulation and improve outcomes. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique identifier: NCT00243178.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".