Impact of Center Experience on Patient Radiation Exposure During Transradial Coronary Angiography and Percutaneous Intervention: A Patient‐Level, International, Collaborative, Multi‐Center Analysis
Bibliographic record
Abstract
BACKGROUND: The adoption of the transradial (TR) approach over the traditional transfemoral (TF) approach has been hampered by concerns of increased radiation exposure-a subject of considerable debate within the field. We performed a patient-level, multi-center analysis to definitively address the impact of TR access on radiation exposure. METHODS AND RESULTS: Overall, 10 centers were included from 6 countries-Canada (2 centers), United Kingdom (2), Germany (2), Sweden (2), Hungary (1), and The Netherlands (1). We compared the radiation exposure of TR versus TF access using measured dose-area product (DAP). To account for local variations in equipment and exposure, standardized TR:TF DAP ratios were constructed per center with procedures separated by coronary angiography (CA) and percutaneous coronary intervention (PCI). Among 57 326 procedures, we demonstrated increased radiation exposure with the TR versus TF approach, particularly in the CA cohort across all centers (weighted-average ratios: CA, 1.15; PCI, 1.05). However, this was mitigated by increasing TR experience in the PCI cohort across all centers (r=-0.8; P=0.005). Over time, as a center transitioned to increasing TR experience (r=0.9; P=0.001), a concomitant decrease in radiation exposure occurred (r=-0.8; P=0.006). Ultimately, when a center's balance of TR to TF procedures approaches 50%, the resultant radiation exposure was equivalent. CONCLUSIONS: The TR approach is associated with a modest increase in patient radiation exposure. However, this increase is eliminated when the TR and TF approaches are used with equal frequency-a guiding principle for centers adopting the TR approach.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".