The Role of Cardiovascular Implantable Electronic Devices in the Detection and Treatment of Subclinical Atrial Fibrillation
Bibliographic record
Abstract
Importance: Subclinical atrial fibrillation (AF) is associated with an increased risk for stroke. Observations: Subclinical AF is asymptomatic, short in duration, and usually detected with long-term, continuous monitoring. Most prior studies have explored its consequences using cardiovascular implantable electronic devices (CIEDs). Although current prevalence estimates are derived from study populations with prior CIEDs, 3 trials will assess the time to a first AF diagnosis among patients receiving a CIED for purposes of AF detection. Stroke risk estimates are currently limited to patients with a prior CIED and vary widely, ranging from a hazard ratio of 0.87 (95% CI, 0.58-1.31) to 9.40 (95% CI, 1.80-47.00). Stroke risk pathogenesis may include factors that are proximately causal, upstream risk activators, and risk markers. The treatment of subclinical AF may be a useful stroke prevention strategy; however, no direct evidence of benefit from oral anticoagulation exists in this population. Two ongoing trials will assess the risk and benefit of non-vitamin K oral anticoagulants among patients at high risk for stroke with a previously placed implantable CIED, but without a prior diagnosis of clinical AF. If clinical benefit is proven, then the cost-effectiveness of screening for and the treatment of subclinical AF will require additional study. Conclusions and Relevance: At present, no evidence suggests that implanting a CIED to detect AF or initiating oral anticoagulation therapy among those in whom AF is detected is beneficial. Ongoing and future studies will identify people at high risk for developing subclinical AF and will evaluate the efficacy, safety, and economic value of oral anticoagulation therapy in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".