Injection rates for neuroangiography: results of a survey.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Injection rates have attracted scrutiny because of an incident of an aneurysm rupturing during arteriography. We sought to determine the current injection rates for neuroangiography in the setting of aneurysm evaluation. METHODS: An e-mail survey was distributed to 90 neuroradiology program directors within the United States and Canada. The injection rates and total volumes of contrast material injected for the common carotid, internal carotid, and vertebral arteries were provided for an "average" adult individual evaluated for intracranial aneurysms. RESULTS: Sixty-three (70.0%) program directors replied to the survey. Of these, five perform hand injections only and provided approximate values. The mean injection rates (SD) and total volumes (SD) for common carotid arteries were 7.2 cm(3)/s (1.8) and 9.9 cm(3) (2.0), respectively; for internal carotid arteries, 5.8 cm(3)/s (1.4) and 7.9 cm(3) (1.5); and for vertebral arteries, 5.4 cm(3)/s (1.2) and 7.8 cm(3) (1.7). The modes (rate/total) for the common carotid, internal carotid, and vertebral arteries were 7/12, 6/8, and 5/8, respectively. Forty-eight (81.4%) of 59 respondents did not believe a reduction in current injection rates would lead to a diminution in complications of arteriography. CONCLUSION: The rates of injection of contrast material in the United States for neuroradiologic studies show great variability. It does not seem that reducing arteriographic complications is an impetus to reduce injection rates. The values in this survey can provide "industry norms" for injections in the common carotid, internal carotid, and vertebral arteries if these rates are challenged.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".