Magnetoelectroanatomic Mapping of Arrhythmias in Structural Heart Disease Using a Novel Multielectrode Catheter:
Bibliographic record
Abstract
Electroanatomic mapping with CARTO requires point-by-point acquisition using the mapping catheter's bipolar tip electrode. This study evaluates the utility of a novel 26-electrode catheter (Qwikstar) for electroanatomic mapping of arrhythmias in patients with structural heart disease. The multielectrode catheter acquires activation times and anatomic data simultaneously from its tip and shaft electrodes. Eight patients (6 men, 2 women, age 47 years [37, 65]) with atrial tachycardia (n = 6) and ventricular tachycardia (n = 2) due to congenital heart disease (n = 4) and cardiomyopathy (n = 4) were studied. Using the multielectrode catheter, the electroanatomic map was constructed in two stages: (1) a scout map using the minimum number of tip and shaft electrode data points that covered > 70% of the tachycardia cycle length and/or the majority of the chamber volume, and (2) a complete map using additional tip electrode data points. A total of 36 (28, 510) tip electrode and 38 (34, 42) shaft electrode electroanatomic data points comprised the scout map. The complete map was constructed with a total of 102 (73, 134) tip electrode electroanatomic data points. In three patients, the scout map suggested a cavotricuspid isthmus dependent atrial flutter that was confirmed with the complete map. In another four patients, the scout map identified the earliest site of focal activation, which was also confirmed with the complete map. In comparison, activation mapping using the bipolar catheter (Navistar) in a group of arrhythmia-matched control subjects required 210 (180, 320) electroanatomic data points (P = 0.012 vs multielectrode catheter complete map). In conclusion, for large macroreentrant or focal arrhythmias in patients with structural heart disease, the multielectrode catheter can generate a scout map that accurately guides complete electroanatomic mapping using fewer point-by-point acquisitions than the bipolar catheter.
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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".