Adverse Events with Universal Use of Iodixanol for CT
Bibliographic record
Abstract
OBJECTIVE: To evaluate the incidence of adverse events with the universal use of iodixanol for computed tomography (CT) and compare it with periods when iohexol was used exclusively. METHODS: Iodixanol was used for CT in 15,142 consecutive patients and compared with 22,044 patients who received iohexol. RESULTS: Adverse events were observed in 116 patients (0.77%) who received iodixanol and in 54 patients (0.25%) who received iohexol (P < 0.001). Immediate and delayed adverse events were seen in 76 and 40 patients (0.50% and 0.26%, respectively) who received iodixanol and in 52 and 2 patients (0.24% and 0.01%, respectively) who received iohexol, respectively (immediate, P = 0.002; delayed, P < 0.001). Adverse events with iodixanol and iohexol were as follows: mild, 89% and 98%; moderate, 10% and 2%; and severe, 1% and 0%, respectively. CONCLUSIONS: Adverse events occurred in less than 1% of patients receiving either contrast agent. However, the incidence of immediate and delayed adverse events was significantly higher with iodixanol than iohexol.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".