Risk Evaluation of Endoscopic Retrograde Cholangiopancreatography-Related Contrast Media Allergic-Like Reaction: A Single Centre Experience
Bibliographic record
Abstract
Background and Aims.Few cases of endoscopic retrograde cholangiopancreatography- (ERCP-) related contrast media (CM) adverse reactions have been reported in the current literature. There is a lack of standardisation in practice regarding premedication prophylaxis for at-risk patients undergoing ERCP and there are few data to guide the practitioners. Our goal is to evaluate the risk of CM adverse reaction in a group of patients with a past history of allergic-like reaction to iodine product undergoing ERCP.Methods.A retrospective chart review study was performed of patients who underwent ERCP at our single centre from January 2010 to December 2015.Results.2295 ERCPs were performed among 1766 patients. No anaphylactoid or severe adverse reaction occurred. One (0.04%) ERCP-related CM benign reaction was reported in a patient known for penicillin allergy. Among 127 ERCPs performed on patients with a prior adverse reaction to iodine, 121 procedures were done without and 6 with a premedication prophylaxis. In both groups, no ERCP-related CM reaction occurred.Conclusions.To our knowledge, we report the largest cohort of iodine allergic patients undergoing ERCP ever published. These results suggest that ERCP-related CM adverse reactions are very rare even among patients at risk for CM reaction.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".