Renal Safety of CT Angiography and Perfusion Imaging in the Emergency Evaluation of Acute Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Multimodal CT imaging with contrast-enhanced CT angiography (CTA) and CT perfusion (CTP) is increasingly being used to guide emergency management of acute stroke. However, little has been reported about the safety of intravenous contrast administration associated with these studies in the acute stroke population, including cases in which baseline creatinine values are unknown. We investigated the incidence of contrast-induced nephropathy (CIN), defined as a 25% or more increase in baseline creatinine levels within 72 hours of contrast administration and chronic kidney disease in patients receiving CTA+/-CTP at our regional stroke center. MATERIALS AND METHODS: We analyzed 198 patients who underwent contrast CT studies for evaluation of acute ischemic or hemorrhagic stroke at our center (2003-2007). Through retrospective chart abstraction, we analyzed serial creatinine levels (baseline to day 3) and later values (>/=day 4) where available. The incidences of CIN and/or chronic kidney disease were documented. After power analysis, CIN and non-CIN groups were compared by using the unpaired t test, Wilcoxon rank sum test, or Fisher exact test. RESULTS: None of the 198 patients developed chronic kidney disease or required dialysis. Of 175 patients with serial creatinine measurements between baseline and day 3, 5 (2.9%) developed CIN. The incidence of CIN was 2% in patients who were scanned before a baseline creatinine level was available. CONCLUSION: The incidence of renal sequelae is relatively low in acute stroke patients undergoing emergent multimodal CT scanning. Prompt CTA/CTP imaging of acute stroke, if indicated, need not be delayed in those with no history of renal impairment.
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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".