A Randomized Trial Comparing Dual Axis Rotational Versus Conventional Coronary Angiography in a Population with a High Prevalence of Coronary Artery Disease
Bibliographic record
Abstract
OBJECTIVES: To compare the safety, radiation dose, and contrast volume between dual axis rotational coronary angiography (DARCA) and conventional coronary angiography (CCA). BACKGROUND: CCA is performed in multiple, predefined stationary views, at different angulations around the patient, for both the left and right coronary arteries. DARCA (AlluraXperSwing™, Philips, the Netherlands) involves a pre-set rotation of the C-arm around the patient and allows for the visualization of each coronary artery in different views, using a single automatic pump contrast injection. METHODS: From November 2012 to February 2013, 201 patients were randomly assigned to either CCA (n = 100) or DARCA (n = 101). Exclusion criteria included acute coronary syndrome (ACS), prior PCI or CABG. CCAs were performed in 4 acquisition runs for the left coronary artery and 2 to 3 acquisition runs for the right coronary artery, whereas DARCAs were performed in a single run for each coronary artery. RESULTS: Baseline demographics and clinical characteristics were similar for both groups. The overall prevalence of CAD was 77.6%. The DARCA group had a significant reduction in the amount of contrast, 60 ml (IQR: 52.5-71.5 ml) versus 76 ml (IQR: 68-87 ml), P < 0.0001; and radiation dose by Air Kerma, 269.5 mGy (IQR: 176-450.5) versus 542.1 mGy (IQR: 370.7-720.8), P < 0.0001. There were fewer patients requiring additional projections in the DARCA group: 54.0% versus 75.0%; P = 0.002. CONCLUSIONS: In a population with a high prevalence of CAD, DARCA was safe and resulted in a significant decrease in contrast volume and radiation dose.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".