60 Taking the long way around: case series of biatrial flutter following anteroseptal mitral isthmus line
Bibliographic record
Abstract
Introduction Left atrial perimitral flutter is a common late complication of atrial fibrillation ablation. Repeat ablation with a posterolateral mitral isthmus line to eliminate the flutter circuit has proven technically challenging, leading some to opt for anteroseptal line ablation as an alternative. A significant issue with the latter approach is the emergence of a biatrial flutter using the right atrial septum via epicardial connections to bypass the line of block and allow continued flutter propagation (image 1). In this case series we present our experience of biatrial flutter in patients with previous anteroseptal left atrial ablation. Methods We reviewed all cases of biatrial flutter treated at our institution from January 2017 to July 2024. Results Four cases of biatrial flutter were identified. Clinical and procedural characteristics are listed in table 1. All patients were male and had undergone prior pulmonary vein isolation and anteroseptal line. Ablation at sites of interatrial conduction successfully terminated biatrial flutter in 3 out of 4 cases. The remaining case had an unsuccessful ablation and was cardioverted to sinus rhythm. Conclusion Biatrial flutter is a potential complication following anteroseptal line formation for perimitral flutter, necessitating biatrial mapping for diagnosis. Ablation at interatrial connection sites where earliest activation is identified is a potentially effective treatment strategy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".