Extraction of radiolucent fractured wire components using intracardiac ultrasound during pulmonary vein isolation procedure
Bibliographic record
Abstract
Key Teaching Points•New curved wires such as the ProTrack transseptal wire (Baylis Medical, Toronto, Canada) can be subject to fracture owing to their more complex construction.•Fractured wire components may be invisible to standard fluoroscopy, despite the presence of substantial amounts of stainless steel wire as a result of very-thin-diameter components that constitute the wire itself.•Intracardiac ultrasound remains an effective tool for visualizing all fragments of metal, as the thin-diameter metal components remain clearly visible on ultrasound imaging.•Consideration of ultrasound scanning should be made in situations where retained wire fragments are suspected but not seen on fluoroscopic imaging.•In the course of transseptal puncture, the use of high-quality intracardiac ultrasound imaging should be considered to ensure that the entirety of the interatrial septum is crossed by the transseptal sheath prior to removal of the transseptal needle. •New curved wires such as the ProTrack transseptal wire (Baylis Medical, Toronto, Canada) can be subject to fracture owing to their more complex construction.•Fractured wire components may be invisible to standard fluoroscopy, despite the presence of substantial amounts of stainless steel wire as a result of very-thin-diameter components that constitute the wire itself.•Intracardiac ultrasound remains an effective tool for visualizing all fragments of metal, as the thin-diameter metal components remain clearly visible on ultrasound imaging.•Consideration of ultrasound scanning should be made in situations where retained wire fragments are suspected but not seen on fluoroscopic imaging.•In the course of transseptal puncture, the use of high-quality intracardiac ultrasound imaging should be considered to ensure that the entirety of the interatrial septum is crossed by the transseptal sheath prior to removal of the transseptal needle.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".