P.120 Contrast induced encephalopathy following endovascular therapy for the treatment of cerebrovascular disease
Bibliographic record
Abstract
Background: Contrast induced encephalopathy (CIE) is an underrecognized, adverse effect of contrast administration during endovascular procedures. A paucity of literature exists regarding CIE following treatment of cerebrovascular disease. As such, we sought to describe our institutional experience with this entity. Methods: We searched our neurovascular database for instances of CIE following endovascular therapy for cerebrovascular disease. We extracted patient data, including demographics, comorbidities, procedural data, symptoms, radiological findings, and treatment. Informed consent was obtained in all cases. Data was analyzed using descriptive statistics. Results: Two patients underwent coiling of cerebral aneurysms; four were treated for ischemic stroke (thromboembolism or large artery atherosclerosis). Mean age was 67.2 years. Risk factors for microvascular dysfunction were identified for most patients: hypertension (100%), obesity (83%), dyslipidemia (83%), prior stroke (83%), renal disease (80%), and connective tissue disorders (33%). Mean operative duration: 284.5 minutes. Mean contrast volume: 285.7 mL. Decreased level of consciousness and lateralizing neurological deficits were the most common CIE-related symptoms. Treatments included intravenous fluids, corticosteroids, and anti-hypertensives. Radiographic findings included effaced cortical sulci, parenchymal edema, and cortical/subarachnoid contrast enhancement. Conclusions: Here, we describe our institutional experience with CIE following endovascular therapy for cerebrovascular disease. We hypothesize that CIE may be facilitated by pre-existing microvascular pathology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".