Catheter Ablation of Premature Ventricular Complexes Exclusively by A 3D Electroanatomic Pace-Mapping Software Technique: Long-Term Follow-Up
Bibliographic record
Abstract
INTRODUCTION/OBJECTIVE: Ablation of premature ventricular complexes (PVCs) is a challenge in routine electrophysiology. Results depend on factors such as location, tools, and technologies available. The study aimed to analyze the exclusive use of the pace-mapping technique with module of Score Map TM (SM) Software of Ensite Velocity/Precision and evaluate long term success.METHODS/RESULTS: Forty-three procedures were retrospectively analyzed between March 2018 and August 2019.Ablation was conducted with an irrigated tip catheter with a power of 20-40 W and a pump flow rate of 30ml/min.Mapping with a duodecapolar was conducted in 36 (83.72%) cases, and the HDGrid catheter was used in seven (16.28%) cases.The patients included 22 (51.16%)females, and the mean age was 51.65 years (19-78).Thirty-five patients (81.40%) had hypertension; six (13.95%) had chronic coronary disease; four (9.30%) had myocarditis; two (4.65%) had diabetes; and none had implanted defibrillators.Mean ejection fraction was 63.17% (47.35%-77.32%).Average radiofrequency time was 597.72 (176-1356) s, and mean X-Ray time was 7.74 min.During the procedure, median SM was 93.81% (84%-100%) and only seven (18.42%) ablations were considered unsuccessful due to maintenance of extrasystoles or reduction of PVCs.After a followup of 19.58 (12-30) months, 37 (86.05%)patients achieved success.Failure was observed in cases with an SM score ≤ 92%, ablation cases with conscious sedation, female sex, both side ventricle ablation and associated with cardiac veins, and more than 900 seconds of RF application.CONCLUSION: Score Map TM is useful as an exclusive technique for ablation of premature ventricular complexes with very good acute success and low complications, and an SM score higher than 92% had high long-term success.Failure was related to conscious sedation, female gender, both side ventricle with cardiac veins ablation, and longer radiofrequency time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".