Comparison of Safety and Effectiveness Between Direct Oral Anticoagulants and Vitamin K Antagonists in Dementia Patients with Atrial Fibrillation: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background/Objectives: The question of whether the benefits of anticoagulation outweigh the risks of bleeding in patients with dementia and atrial fibrillation (AF) remains unresolved. This study aimed to evaluate the effectiveness of oral anticoagulation (OAC) and to compare the safety and effectiveness of direct oral anticoagulants (DOACs) with vitamin K antagonists (VKAs) within this at-risk population. Methods: This meta-analysis was conducted following the PRISMA guidelines and was registered in PROSPERO. Data were extracted from MEDLINE, Web of Science, and Cochrane Library. The Newcastle–Ottawa Scale was used to assess the risk of bias. The outcomes were analyzed using the Comprehensive Meta-Analysis software, with odds ratios (ORs) and 95% confidence intervals (CIs) calculated for dichotomous variables. Results: Eight retrospective studies were included, with sample sizes of up to 40,350 participants. The primary outcome was mortality incidence, while secondary outcomes included ischemic stroke, major bleeding, and intracranial hemorrhage (ICH). DOACs significantly reduced ICH events compared to VKAs (OR 0.38, 95% CI 0.17–0.84; I2 = 87.3%) but showed no significant difference in major bleeding (OR 0.48, 95% CI 0.22–1.03; I2 = 88%). Mortality and ischemic stroke rates were similar between the DOAC and VKA groups. OAC use reduced mortality by 29% compared to no OAC (OR 0.71, 95% CI 0.57–0.88; I2 = 81.3%) but increased major bleeding risk (OR 1.19, 95% CI 1.08–1.3; I2 = 0%). Conclusions: DOACs offer a safer profile regarding ICH in dementia patients with AF compared to VKAs, with no significant differences in mortality or ischemic stroke rates. This study highlights the need for careful anticoagulant selection in this vulnerable population.
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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 | 0.017 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.038 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".