Reducing Radiation Exposure during CRT Implant Procedures: Early Experience with a Sensor‐Based Navigation System
Bibliographic record
Abstract
BACKGROUND: Cardiac resynchronization therapy (CRT) implant procedures are often complex and prolonged, resulting in significant ionizing radiation (IR) exposure to the patient and operator. We report our early experience working with a novel sensor-based electromagnetic tracking system (MediGuide™, MDG, St. Jude Medical Inc., St. Paul, MN, USA), in terms of procedural IR exposure reduction. METHODS AND RESULTS: Information regarding patient demographics, procedural details, procedural duration, and IR exposure were prospectively collected on 130 consecutive CRT procedures performed between January 2013 and January 2014. Sixty procedures were performed with MDG guidance, and 70 were performed without MDG guidance. Despite a nonsignificant trend toward shorter procedure duration with the use of MDG (120 minutes vs 138 minutes with non-MDG, P = 0.088), a 66% reduction in total IR exposure (median 769 μGray · m(2) vs 2,608 μGray · m(2), P < 0.001) was found. This reduction was primarily driven by a >90% reduction in IR dose required to cannulate the coronary sinus (median 80 μGray · m(2) vs 922 μGray · m(2), P < 0.001), and to a lesser extent from a reduction in IR dose required for LV lead placement (median 330 μGray·m(2) vs 737 μGray · m(2), P = 0.059). In addition, a significant learning curve effect was observed with a significantly shorter procedural duration for the last 15 cases compared to the first 15 cases (median 98 minutes vs 175 minutes, P < 0.001). CONCLUSION: The nonfluoroscopic MDG positioning system is associated with a dramatic reduction in exposure to IR during CRT implant procedures, with a 90% decrease in the IR dose required to cannulate the coronary sinus. A steep learning curve was quantified.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".