Radiation Reduction in Paediatric Cardiac Catheterization: We Can Go Even Lower
Bibliographic record
Abstract
Background Radiation reduction is an integral component in the management of a pediatric cardiac catheterization laboratory. Simple and easily implementable protocol changes and technical upgrades have been shown to significantly reduce radiation exposure. Methods Radiation exposures (2020-2022) at Safra Children's Hospital, Sheba Medical Center, Israel (Unit A: n=672) were retrospectively reviewed, including DAP (μGy·m 2 ), DAP/kg, Air Kerma (mGy) and fluoroscopy time (minutes) for 16 procedural types. Median doses were compared with those measured ( 2011-2014) at the Hospital for Sick Children, Toronto, Canada (Unit B: n=2033). Radiation reduction techniques included fluoroscopy acquisition at 7.5 frames/second, removal of anti-scatter grids for children <30 kg, limiting field of view, use of Philips ClarityIQ technology and an institutional culture of radiation mindedness. Results Exposure was significantly lower in Unit A in 14 of 16 procedure types. Total median doses were lower in Unit A (DAP 91.4(44.7-205.4) vs. 387(138.2-1339) μGy·m 2 , (p<0.001), DAP/kg 9.33(4.3-16.4) vs. 29.22(12.8-65.9) μGy·m2/kg, (p<0.001), Air Kerma 14.9(7.8-29) vs. 61(23-176.4) mGy, (p<0.001)) despite higher fluoroscopy time (14.1(4.2-24.6) vs. 12.3(6.8-23.3) minutes, (p=0.03)). DAP was lower for specific procedures including pulmonary valvuloplasty 46.3(14.3-219.3) vs. 127(60-323) μGy·m2, (p<0.001) and PDA closure 51.9(18.8-111.8) vs. 178(96-410) μGy·m2, (p<0.001). Conclusions Enhanced radiation reduction techniques can lead to lower than previously published exposure levels across a wide range of procedure types when employing dose-limiting protocols and radiation-reduction technology.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".