Survey of Radiologists' Knowledge Regarding the Management of Severe Contrast Material–induced Allergic Reactions
Bibliographic record
Abstract
PURPOSE: To evaluate radiologists' knowledge of the appropriate management of severe contrast material-induced allergic reactions by means of a telephone survey. MATERIALS AND METHODS: Institutional research ethics board approval was obtained. Following verbal consent, a telephone survey of radiologists working in Canada's 13 English-speaking and 13 U.S. university-affiliated radiology departments was performed. Participants were selected by using a multistage sampling scheme and simple random sampling within departments. Given a severe contrast material-induced allergic reaction case scenario, radiologists were first asked their initial medication of choice, then questioned specifically on the use of epinephrine. The Canadian and U.S. cohorts were compared by using the chi(2) and Fisher exact tests, as appropriate, and proportions and 95% confidence intervals (CIs) were computed. RESULTS: A total of 253 (81%) of 311 radiologists from a 30% target population were surveyed. Ninety-one percent (231 of 253; 95% CI: 88%, 94%) of radiologists chose epinephrine as the most important initial medication. No radiologist gave the ideal response, but 41% (94 of 231; 95% CI: 35%, 47%) provided an acceptable administration route, concentration, and dose; 17% (n = 39; 95% CI: 12%, 22%) of radiologists provided an overdose. Only 11% (27 of 253; 95% CI: 7%, 15%) of radiologists knew what concentration of epinephrine was available in their drug kit and/or crash cart and what equipment would be required to administer it to a patient. CONCLUSION: Radiologists' knowledge of epinephrine for the management of severe contrast material-induced allergic reactions is deficient.
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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 | 0.016 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".