Evolving Electroanatomic Substrate and Intra‐Atrial Reentrant Tachycardia Late After Fontan Surgery
Bibliographic record
Abstract
INTRODUCTION: The prevalence of intra-atrial reentrant tachycardia (IART) increases with age in Fontan patients. This study aimed to characterize the atrial electroanatomic substrate for IART late after Fontan surgery. METHODS AND RESULTS: Detailed electroanatomic mapping of the right atrium (RA) was performed in 11 consecutive patients (33 ± 9 years) with older style Fontan circulation (atriopulmonary and atrioventricular connection) who underwent their first radiofrequency catheter ablation (RFCA) for IART. A comparative group of 30 non-Fontan congenital heart disease (CHD) patients were also studied. Fontan patients had larger RA (P = 0.004), larger low-voltage area ≤ 0.5 mV (P = 0.01), and more fractionated potentials (P < 0.001) than non-Fontan CHD patients. RA enlargement correlated significantly with both low-voltage zones (Spearman ρ= 0.68, P < 0.001) and fractionated potentials (Spearman ρ= 0.48, P = 0.001). Among Fontan patients, both age and time since Fontan surgery were significantly correlated to the amount of low-voltage areas (Spearman ρ= 0.87, P < 0.001; Spearman ρ= 0.63, P = 0.04, respectively). Successful RFCA was accomplished in 30 (73%) patients and was less likely in Fontan patients (54% vs 83%, P = 0.04). Larger RA was significantly associated with a lower success rate (P = 0.04). During a follow-up duration of 2.3 ± 1.6 years, IART recurred in 47% of patients. Larger RA size and larger low-voltage areas predicted IART recurrence after RFCA. CONCLUSION: Fontan patients demonstrate progressive adverse atrial electrical remodeling with increasing age and time since surgery. Newer strategies beyond surgical incisions, such as pharmacotherapies that retard the progression of atrial fibrosis, may be required to reduce the long-term risk of atrial arrhythmias.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".