Papillary muscle ventricular arrhythmias in patients with arrhythmic mitral valve prolapse: Electrophysiologic substrate and catheter ablation outcomes
Bibliographic record
Abstract
BACKGROUND: Mitral valve prolapse (MVP) is a common valve condition and has been associated with sudden cardiac death. Premature ventricular contractions (PVCs) from the papillary muscles (PMs) may play a role as triggers for ventricular fibrillation (VF) in these patients. OBJECTIVES: To characterize the electrophysiological substrate and outcomes of catheter ablation in patients with MVP and PM PVCs. METHODS: Of 597 patients undergoing ablation of ventricular arrhythmias during the period 2012-2015, we identified 25 patients with MVP and PVCs mapped to the PMs (64% female). PVC-triggered VF was the presentation in 4 patients and a fifth patient died suddenly during follow-up. The left ventricle ejection fraction (LVEF) was 50.5% ± 11.8% and PVC burden was 24.4% ± 13.1%. A cardiac magnetic resonance imaging was performed in nine cases and areas of late gadolinium enhancement were found in four of them. A detailed LV voltage map was performed in 11 patients, three of which exhibited bipolar voltage abnormalities. Complete PVC elimination was achieved in 19 (76%) patients and a significant reduction in PVC burden was observed in two (8%). In patients in which the ablation was successful, the PVC burden decreased from 20.4% ± 10.8% to 6.3% ± 9.5% (P = 0.001). In 5/6 patients with depressed LVEF and successful ablation, the LV function improved postablation. No significant differences were identified between patients with and without VF. CONCLUSIONS: PM PVCs are a source of VF in patients with MVP and can induce PVC-mediated cardiomyopathy that reverses after PVC suppression. Catheter ablation is highly successful with more than 80% PVC elimination or burden reduction.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".