Ventricular substrate identification using close-coupled paced electrogram feature analysis
Bibliographic record
Abstract
AIMS: Substrate based catheter ablation strategies are widely employed for treatment of scar-related ventricular tachycardia (VT). We analysed intracardiac electrograms (EGMs) from close-coupled paced extrastimuli extracted from the EnSite Precision mapping system. We sought to characterize EGM responses of ventricular myocardium to varying coupling intervals from the right ventricular apex (RVA) in both healthy individuals and patients presenting with VT for catheter ablation. METHODS AND RESULTS: Extrastimuli were delivered from the RVA after estimation of the ventricular effective refractory period. Electrograms were recorded from high-density mapping catheters in the left ventricle and exported for analysis to MATLAB. Observational data were collected from 14 patients with ischaemic VT (mean age 72.4 ± 6.3 years, one female) and five controls (mean age 59.4 ± 7.4 years, one female). These derived data were used to inform an interventional strategy on a further 10 patients (mean age 64.7 ± 10.0 years; two female). Significant differences were observed in EGM duration (ED) and latency (LT) at all coupling intervals between VT patients and controls. Significant increases in ED and LT with decreased RVA coupling interval were observed at VT isthmuses. Abnormal responses derived from control subject data were used to classify four types of ventricular EGM response. Targeting sites with abnormal LT and ED significantly reduced VT inducibility (5/14 derivation patients to 0/10 intervention patients; P = 0.03). CONCLUSION: Paced electrogram feature analysis is a novel tool to characterize the ischaemic substrate. Association with VT isthmuses and early ablation results suggest a possible role in substrate ablation for ischaemic VT.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".