Early post-endovascular treatment contrast extravasation on dual-energy CT is associated with clinical and radiological stroke outcomes: A 10-year single-centre experience
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To determine the association between early post-endovascular treatment (EVT) contrast extravasation (CE) on dual-energy CT (DECT) and stroke outcomes. METHODS: EVT records in 2010-2019 were screened. Exclusion criteria included the occurrence of immediate post-procedural intracranial haemorrhage (ICH). Hyperdense areas on iodine overlay maps were scored according to the Alberta Stroke Programme Early CT Score (ASPECTS), thus forming a CE-ASPECTS. Maximum parenchymal iodine concentration and maximum iodine concentration relative to the torcula were recorded. Follow-up imaging was reviewed for ICH. The primary outcome measure was the modified Rankin Scale (mRS) at 90 days. RESULTS: Out of 651 records, 402 patients were included. CE was found in 318 patients (79%). Thirty-five patients developed ICH on follow-up imaging. Fourteen ICHs were symptomatic. Stroke progression occurred in 59 patients. Multivariable regression showed a significant association between decreasing CE-ASPECTS and the mRS at 90 days (adjusted (a)cOR: 1.10, 95% CI: 1.03-1.18), NIHSS at 24-48 h (aβ: 0.57, 95% CI: 0.29-0.84), stroke progression (aOR: 1.14, 95% CI: 1.03-1.26) and ICH (aOR: 1.21, 95% CI: 1.06-1.39), but not symptomatic ICH (aOR 1.19, 95% CI: 0.95-1.38). Iodine concentration was significantly associated with the mRS (acOR: 1.18, 95% CI: 1.06-1.32), NIHSS (aβ: 0.68, 95% CI: 0.30-1.06), ICH (aOR: 1.37, 95% CI: 1.04-1.81) and symptomatic ICH (aOR: 1.19, 95% CI: 1.02-1.38), but not stroke progression (aOR: 0.99, 95% CI: 0.86-1.15). Results of the analyses with relative iodine concentration were similar and did not improve prediction. CONCLUSIONS: CE-ASPECTS and iodine concentration are both associated with short- and long-term stroke outcomes. CE-ASPECTS is likely a better predictor for stroke progression.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it