The Association of the Spatial Location of Contrast Extravasation withSymptomatic Intracranial Hemorrhage after Endovascular Therapy inAcute Ischemic Stroke Patients
Bibliographic record
Abstract
BACKGROUND: Contrast extravasation (CE) on brain non-contrast computed tomography (NCCT) after endovascular therapy (EVT) is commonly present in patients with acute ischemic stroke (AIS). Substantial uncertainties remain about the relationship between the spatial location of CE and symptomatic intracranial hemorrhage (sICH). Therefore, this study aimed to evaluate this association. METHODS: We performed a retrospective screening on consecutive patients with AIS due to LVO (AIS-LVO) who had CE on NCCT immediately after EVT for anterior circulation large vessel occlusion (LVO). We used the Alberta stroke program early CT Score (ASPECTS) scoring system to estimate the spatial location of CE. Multivariable logistic regression was performed to achieve the risk factors of sICH. RESULTS: In this study, 115 of 153 (75.1%) anterior circulation AIS-LVO patients had CE on NCCT. After excluding 9 patients, 106 patients were enrolled in the final analysis. In multivariate regression analysis, atrial fibrillation (AF) (adjusted OR [aOR] 6.833, 95% confidence interval [CI] 1.331-35.081, P = 0.021) and CE-ASPECTS (aOR 0.602, 95% CI 0.411-0.882 P = 0.009) were associated with sICH. In subgroup analysis, CE at the internal capsule (IC) region was an independent risk factor for sICH (aOR 5.992, 95% CI 1.010-35.543 P < 0.05). These and conventional variables were incorporated as a predict model, with AUC of 0.899, demonstrating good discrimination and calibration for sICH in this study cohort. CONCLUSION: The spatial location of CE on NCCT immediately after EVT was an independent and strong risk factor for sICH in acute ischemic stroke patients.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".