Optimal lead preparation for the extraction of a lumenless defibrillation lead
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The OmniaSecure lead (Medtronic) is the first small-diameter, lumenless, catheter-delivered defibrillation lead. Its design, including the absence of a central lumen, precludes the use of traditional lead-locking stylets during transvenous lead extraction, requiring reevaluation of optimal lead preparation (lead prep) techniques. Successful extraction relies on maximizing lead tensile strength while maintaining compatibility with available extraction sheaths. OBJECTIVE: This study aimed to evaluate and compare the mechanical performance, sheath compatibility, and practicality of 5 lead prep strategies for the OmniaSecure lead in a bench testing model. METHODS: 5 lead prep methods were tested, varying in connector retention, suture placement, and use of a 1-tie compression coil. Outer diameters were measured with calipers and compared against commercial extraction sheath specifications. Tensile strength was assessed using a mechanical test system simulating 3 common adhesion points: the myocardium, tricuspid valve, and venous vasculature. Each technique was evaluated at least 3 times for sheath compatibility, maximum tensile load, and failure location. RESULTS: Outer diameters of the OmniaSecure lead preps ranged from 8.4F to 13.7F, with the removed DF-4 connector secured with a 1-tie demonstrating the smallest profile and highest average tensile strength (12.3 pounds of force). It was compatible with all tested sheaths. Most cable failures occurred proximally, allowing for potential repreparation. CONCLUSION: Among the tested methods, the removed DF-4 connector secured with a 1-tie demonstrated the most favorable combination of small outer diameter and high tensile strength, suggesting that it may offer the optimal balance of rail strength and sheath compatibility.
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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 | 0.000 |
| 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) | 0.000 | 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 it