444 Epidemiology of subclinical atrial fibrillation in patients with cardiac implantable electronic devices: a systematic review and meta-regression
Bibliographic record
Abstract
Abstract Aims In recent years, attention to subclinical atrial fibrillation (SCAF), defined as the presence of atrial high-rate episodes (AHREs), in patients with cardiac implantable electronic devices (CIEDs), has gained much interest as a determinant of clinical AF and stroke risk. To perform a systematic review and meta-regression of the available scientific evidence regarding the epidemiology of SCAF in patients receiving CIEDs. Methods and results PubMed and EMBASE were searched for all studies documenting the incidence of AHREs in patients (n = 100 or more) with CIEDs without any previous history of AF from inception to 20 August 2021, screened by two independent blind reviewers. This study was registered in PROSPERO: CRD42019106994. Among the 2614 results initially retrieved, 54 studies were included, with a total of 72 784 patients. Meta-analysis of included studies showed a pooled prevalence of SCAF of 28.1%, with an incidence rate (IR) of 16 new SCAF cases per 100 patient-years (I2 = 100%). Multivariate meta-regression analysis showed that age and follow-up time were the only significant determinants of IR, explaining a large part of the heterogeneity (R2 = 61.5%, P < 0.001), with higher IR at earlier follow-up and in older patients, decreasing over follow-up time and increasing according to mean age. Older age, higher CHA2DS2-VASc score, history of AF, hypertension, CHF, and stroke/TIA were all associated with SCAF occurrence. Conclusions In this systematic review and meta-regression analysis, IR of SCAF increased with age and decreased over longer follow-up times. SCAF was associated with older age, higher thromboembolic risk, and several cardiovascular comorbidities.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 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 | 0.001 |
| 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".