Abstract 12595: Vascular and Cardiac Ultrasound as the Primary Imaging Tool to Safely Deliver Pacing Leads While Implanting Single Chamber Cardiac Implantable Electronic Devices. RADICAI USE Investigators
Bibliographic record
Abstract
Introduction: Conventional Cardiac implantable electronic devices (CIEDs) implantation requires fluoroscopy. Risks involved with implantation include pneumothorax, lead dislodgement, and perforation of the right ventricular wall. In addition, there are long-term risks of malignancy associated with prolonged and repeated use of radiation over the decades of operators’ employment and mechanical injuries related to heavy personal protection equipment. To reduce these risks, we aimed to study the utilization and safety of ultrasound (US) for the entire procedure to implant single-chamber devices. Methods: The RADICAI USE study (Reduction or Elimination of Radiation Use in Single Chamber Cardiac Devices using ultrasound) is a prospective, single-arm and multi-operator case series enrolled patients awaiting a single-chamber CIED. A fluoroscopic cut-off time of 20 seconds was used to define the success (Group A) or failure (Group B) of using the US for the entire implant duration. Patients were followed up at 1 week, 1 month and 1-year post-implant. Results: The study enrolled 63 patients, with 50 pacemakers and 13 ICDs, a mean age of 79.5 ± 13.8 years (95% CI = 76.1 - 82.9), and a mean weight of 74.1 ± 14.6 (95% CI = 70.5 - 77.7). Overall, 53 (84.1%) CIEDs were successfully implanted with a radiation time of less than 20 seconds (Group A). Fluoroscopic over 20 seconds was required due to poor echocardiographic windows, challenging access, or anatomy. No iatrogenic new or worsening of tricuspid regurgitation was noted. The mean procedure time including US setup time was 65.2 ± 20.2 (95% CI = 60.2 -70.2) minutes. Fluoroscopic time was significantly reduced in Group A compared to Group B (5.8 ± 4.5s vs 109.5 ± 92.9s, p = 0.004). Follow-up showed no device-related complications, with only two patients requiring lead revisions due to poor sensitivity, one unrelated to US use and another probably related. Conclusions: US-guided implantation of single-chamber CIEDs is feasible and safe, reducing the need for fluoroscopic guided implantation and subsequent risks of higher radiation exposure. Further studies are required to evaluate the cost-effectiveness and to explore fluoroscopic-free single-chamber CIED implantations using the US.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".