Heartbeat: lower risk of dementia with a direct oral anticoagulatant, compared to a vitamin K antagonist, for patients with atrial fibrillation
Bibliographic record
Abstract
Patients with atrial fibrillation (AF) have a higher risk of dementia and mild cognitive impairment, in addition to a fivefold higher risk of stroke, compared with patients in normal sinus rhythm. Potential mechanisms of cognitive impairment or dementia related to AF include recurrent micro emboli versus cerebral hypoperfusion in association with increased oxidative stress, inflammation and disruption of the blood-brain barrier. Using linked electronic health records from the Clinical Practice Research Datalink in the UK, Cadogan and colleagues1 compared the incidence of dementia or mild cognitive impairment in 39 200 patients (median age 76 years, 45% women) with AF treated with either a vitamin-K antagonist (VKA) or a direct oral anticoagulant (DOAC). Incident dementia was diagnosed in 3.2% with a 16% lower risk of dementia in patients treated with a DOAC versus VKA (adjusted HR 0.84, 95% CI: 0.73 to 0.98) . Mild cognitive impairment was diagnosed in 4.0% with a 26% lower risk in those treated with a DOAC versus VKA (adjusted HR 0.74, 95% CI: 0.65 to 0.84) (figure 1). For patients taking a VKA, greater time with anticoagulation in therapeutic range was associated with a lower risk of dementia. Figure 1 Association between oral anticoagulant use and incident dementia and mild cognitive impairment, defined using clinical codes. ∧Adjusted for age, calendar year, time-on-treatment and sex. *Adjusted for age, calendar year, time-on-treatment, sex, body mass index, smoking status, hazardous alcohol consumption, socioeconomic status (practice level Index of Multiple Deprivation), primary care consultation frequency, diabetes, hypertension, myocardial infarction, statins, heart failure, stroke, vascular disease, renal disease, liver disease, antiplatelet drugs, ACE/ARB inhibitors, beta-blockers, antiarrhythmics, digoxin, diuretics, antipsychotics, antidepressants and proton …
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".