One‐year results of the <scp>ICON</scp> (ionic versus non‐ionic contrast to obviate worsening nephropathy after angioplasty in chronic renal failure patients) Study
Bibliographic record
Abstract
BACKGROUND: Long-term clinical outcomes after exposure to non-ionic iso-osmolar contrast medium (IOCM) or ionic low-osmolar CM (LOCM) in patients with chronic kidney disease (CKD) undergoing coronary angiography are unclear. METHODS: The ICON trial was a prospective, double-blinded, multicentre study that randomly assigned 146 patients with CKD undergoing coronary angiography with or without percutaneous coronary intervention to the non-ionic IOCM Iodixanol or the ionic LOCM Ioxaglate. We report the 1-year clinical outcomes. RESULTS: After randomization, baseline and procedural characteristics were well-matched between the two groups. At 1 year, three deaths (4.1%) occurred in the ioxaglate and nine deaths in the iodixanol group (13.6%, P = 0.07). The cardiac death rate at 1 year was 2.7% in the ioxaglate group and 9.1% in the iodixanol group (P = 0.07). There were no significant differences in the rates of myocardial infarction (1.4% vs. 1.5%; P = 1.00) and repeated revascularization (6.8% vs. 9.1%; P = 0.75). CONCLUSIONS: The use of ionic LOCM ioxaglate was associated with a numerically lower mortality at 1 year as compared to iodixanol in patients who underwent cardiac catheterization. Future studies evaluating long-term safety following exposure to different types of CM are warranted.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.002 |
| 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".