Comparison of anterior mitral line and mitral isthmus line for ablation of mitral annular flutter
Bibliographic record
Abstract
BACKGROUND: Mitral annular flutter (MAF) is the most common left atrial macro-reentrant arrhythmia following catheter ablation of atrial fibrillation (AF). The best ablation approach for this arrhythmia remains unclear. METHODS: This single-center, retrospective study sought to compare the acute and long-term outcomes of patients with MAF treated with an anterior mitral line (AML) versus a mitral isthmus line (MIL). Acute ablation success, complication rates, and long-term arrhythmia recurrence were compared between the two groups. RESULTS: Between 2015 and 2021, a total of 81 patients underwent ablation of MAF (58 with an AML and 23 with a MIL). Acute procedural success defined as bidirectional block was achieved in 88% of the AML and 91% of the MIL patients respectively (p = 1.0). One year freedom from atrial arrhythmias was 49.5% versus 77.5% and at 4 years was 24% versus 59.6% for AML versus MIL, respectively (hazard ratio [HR]: 0.38, confidence interval [CI]: 0.17-0.82, p = .009). Fewer patients in the MIL group had recurrent atrial flutter when compared to the AML group (HR: 0.32, CI: 0.12-0.83, p = .009). The incidence of recurrent AF, on the other side, was not different between both groups (21.7% vs. 18.9%; p = .76). There were no serious adverse events in either group. CONCLUSION: In this retrospective study of patients with MAF, a MIL compared to AML was associated with a long-term reduction in recurrent atrial arrhythmias driven by a reduction in macroreentrant atrial flutters.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".