Epidemiology of subclinical atrial fibrillation in patients with cardiac implantable electronic devices: A systematic review and meta-regression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: 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. We aim to perform a systematic review and metaregression of the available scientific evidence regarding the epidemiology of SCAF in patients receiving CIEDs. Methods: PubMed and EMBASE were searched for all studies documenting the prevalence of AHREs in patients (n=100 or more, <50% with history of AF) with CIEDs from inception to 20th August 2021, screened by two independent blind reviewers. This study was registered in PROSPERO: CRD42019106994. Results: 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% (95%CI: 24.3-32.1%), with high heterogeneity between studies (I 2 =98%). A multivariable meta-regression was able to explain significant proportion of heterogeneity (R 2 =61.9%, p<0.001), with age and follow-up time non-linearly, directly and independently associated with occurrence of SCAF. Older age, higher CHA 2 DS 2 -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, SCAF was frequent among CIED recipients and was non-linearly associated with age and follow-up time. Older age, higher thromboembolic risk, and several cardiovascular comorbidities were associated with presence of SCAF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 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 it