Recurrent stroke in patients with history of stroke/transient ischemic attack and device-detected atrial fibrillation: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction: Prolonged cardiac monitoring after stroke increases the detection of device-detected atrial fibrillation (DDAF), leading to a clinical dilemma regarding anticoagulation for secondary stroke prevention. While anticoagulation reduces thromboembolic risk in clinical AF, its benefit-risk profile in DDAF remains uncertain. Methods: In this systematic review and meta-analysis, randomized-controlled clinical trials (RCTs) evaluating anticoagulation among patients with DDAF post stroke or transient ischemic attack (TIA) were pooled. The primary efficacy outcome was any stroke recurrence, while stroke or systemic embolism, ischemic stroke recurrence, myocardial infarction, and cardiovascular mortality were assessed as secondary efficacy outcomes. The primary safety outcome was major bleeding, while hemorrhagic stroke and all-cause mortality were assessed as secondary safety outcomes. Results: Two RCTs with 599 patients (294 anticoagulation, 305 no-anticoagulation) were included. Anticoagulation significantly reduced any stroke recurrence (RR: 0.47; 95% CI: 0.23–0.94; p = 0.034; number-needed-to-treat = 34). Anticoagulation lowered the risk of the composite outcome of stroke recurrence and systemic embolism (RR: 0.45; 95% CI: 0.22–0.90; p = 0.023). However, anticoagulation was associated with an increased risk of major bleeding (RR: 2.30; 95% CI: 1.06–4.98; p = 0.035; number-needed-to-harm = 37). There were no differences in ischemic stroke recurrence (RR: 0.53; 95% CI: 0.26–1.09; p = 0.084), myocardial infarction (RR: 0.58; 95% CI: 0.17–1.96; p = 0.379), cardiovascular mortality (RR: 0.68; 95% CI: 0.35–1.34; p = 0.265), hemorrhagic stroke (RR: 0.25; 95% CI: 0.03–2.24; p = 0.217) or all-cause mortality (RR: 0.97; 95% CI: 0.66–1.41; p = 0.857). Discussion: Anticoagulation in DDAF patients with prior stroke/TIA reduces any stroke recurrence but increases major bleeding risk without raising hemorrhagic stroke incidence. This trade-off underscores the need for individualized risk stratification. Conclusions: Anticoagulation lowers any stroke recurrence in DDAF patients post-stroke/TIA but raises major bleeding risk.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".