Prevalence of unreported atrial fibrillation in electrocardiograms with ventricular-paced rhythm: a multicenter experience
Bibliographic record
Abstract
Abstract Introduction Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a major preventable cause of stroke. The diagnosis of AF on electrocardiogram is through the recognition of absent p waves and an irregularly irregular ventricular rhythm. However, in ventricular-paced patients, the rhythm on electrocardiogram (ECG) is often regular and may obscure AF diagnosis. Thus, unrecognized AF on ECG poses a potential risk among untreated ventricular-paced patients. There is scant published data reporting the prevalence of underrecognized and untreated ECG-detected AF among ventricular-paced patients. Objectives In the first part of this study, we aim (1) to determine the prevalence of AF and unreported AF on ECGs with ventricular-paced rhythm obtained across all 6 hospitals in our city, Canada. Using data obtained from (1), we then aim (2) to report the rates of untreated and unreported ECG-detected AF among ventricular-paced patients with an indication for anticoagulation, (3) to describe the length of delay in AF recognition and treatment among patients who should be considered for anticoagulation at the time of ECG-detected AF and (4) to identify possible strategies that can improve reporting of AF on ECGs with ventricular-paced rhythm using our institutional ECG software. Methods This is a retrospective multicenter review of ventricular-paced ECGs interpreted and reported by physicians using our institutional ECG software. ECGs were reviewed and confirmed by two independent cardiologists who were blinded from the reported interpretation of the ECGs. Results Of the sample of 1500 ECGs with ventricular-paced rhythm from 2017–2019, 2 independent cardiologists agreed that AF was present in 622 ECGs (41.5%). Of these, 251 (40.4%) were not reported to have AF by the interpreting physician. Conclusions Our study shows that there is a high prevalence of unreported AF on ECG in patients with ventricular-paced rhythm in our local hospitals. Further studies are warranted on describing whether this impacts treatment and outcomes among ventricular-paced patients. This study also highlights the importance of identifying possible strategies to improve reporting of AF on ECGs with ventricular-paced rhythm. Funding Acknowledgement Type of funding sources: None.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".