The radiation burden from increasingly complex endovascular aortic aneurysm repair
Bibliographic record
Abstract
OBJECTIVES: With increasing experience, endovascular aortic aneurysm repair (EVAR) has been extended to patients with less suitable aorto-iliac anatomy in an attempt to reduce peri-operative mortality. However, more complex EVAR procedures may take longer and can result in higher rates of complications, additional interventional procedures and more frequent radiological imaging, which may offset some of the benefit. This study determined the radiation burden for standard EVAR, as determined by the EVAR-1 trial criteria, and more complex EVAR. METHODS: A total of 123 elective patients aged >60, with aneurysms >5.5 cm who received a bifurcated stent-graft were allocated into a group based on whether or not they fulfilled strict EVAR-1 trial criteria. The mean radiation dose was calculated for each group, together with the additional radiation burden from routine pre- and post-EVAR CT examinations and pre-EVAR iliac artery embolisation. RESULTS: Patients not meeting the EVAR-1 trial criteria had significantly longer fluoroscopic screening times and higher radiation doses. The radiation burden in all patients was higher following exposure from routine CT examinations and following pre-EVAR iliac artery embolisation. CONCLUSION: Whilst the radiation from standard EVAR is acceptable, more complicated and challenging EVARs, accompanied with additional radiological investigations and procedures, can significantly increase the radiation burden.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".