Contrast-Induced Encephalopathy: A Case Series Analysis
Bibliographic record
Abstract
BACKGROUND: Contrast-induced encephalopathy (CIE) is a rare adverse event linked to intravascular use of iodine-containing contrast media. The prevalence of CIE could increase in the future due to growing numbers of endovascular procedures. We provide insights from a case series of 7 patients. METHODS: Cases from 3 centers were collected based on existing academic collaborations, and key factors were extracted to illustrate development and management of CIE. RESULTS: In our retrospective case-series analysis of 7 cases from 3 countries, affected patients had an equal distribution of sex (4 women, 3 men) and a median age of 75 (IQR 63-77). Common risk factors included hypertension (5/7), hyperlipidemia (5/7), previous stroke (3/7), and type 2 diabetes (3/7). CIE developed in 3 cases after endovascular thrombectomy (EVT) for stroke, in 2 cases after aneurysm treatment, in 1 case after cardiac catheterization, and in 1 case after diagnostic computed tomography (CT) angiography without an endovascular procedure. The median procedure time was 48 min (IQR 40-81). All patients received non-ionic, low-osmolar contrast agents with volumes ranging from 100-300 ml. Symptom onset was close to contrast administration, with stroke-like neurological deficits being most common (4/7). Prednisolone was the most frequently used medication to treat the symptoms (4/7). Symptom resolution occurred in 4 out of 7 patients within two to several days, and 1 patient died, but without clear connection to CIE. CONCLUSION: CIE is a rare and possibly underrecognized condition, but fortunately, with a favorable outcome in most cases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".