Early Patient Experience with an Electro‐Anatomic Navigation System Dedicated to Device Lead Implantation: Feasibility and Safety
Bibliographic record
Abstract
INTRODUCTION: Fluoroscopy-guided pacing lead placement has well-recognized limitations and risks. We studied the safety and feasibility of using a novel electromagnetic navigation system specifically designed to guide pacemaker and implantable cardioverter defibrillator lead placement. METHODS: Twenty-four patients (mean age of 54±34 years) underwent the study protocol; 16 before electrophysiology study and eight before device implantation. The navigational deflectable sheath assembly was introduced via the subclavian vein and advanced to seven prespecified targets within the right heart chambers. The time taken to reach each target site was measured. RESULTS: All seven prespecified targets were successfully reached by 21 of 24 patients (88%). The total time required to complete the study protocol ranged from 3.21 to 15.25 minutes (average 8.9 minutes), with an associated mean fluoroscopy time of 50±36 seconds. In three of the 24 patients, this navigation system was successfully used to guide right ventricular pacing lead placement. The average total procedure time for these devices was 97.8 minutes (excluding the study protocol), with an average associated fluoroscopy time of 6.93 minutes. These procedures were well tolerated and no periprocedural complications were noted. CONCLUSIONS: This study suggests that this novel electro-anatomic navigation system is a viable and safe alternative to traditional fluoroscopy-guided lead implantation. Further studies are required to determine the absolute reduction in radiation exposure and increased efficiency relative to current standard fluoroscopic techniques.
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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 | 0.000 | 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) | 0.002 | 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".