Improving the Evaluation of Collateral Circulation by Multiphase Computed Tomography Angiography in Acute Stroke Patients Treated with Endovascular Reperfusion Therapies
Bibliographic record
Abstract
Good collateral circulation (CC) is associated with favorable outcomes in acute stroke, but the best technique to evaluate collaterals is controversial. Single-phase computed tomography angiography (sCTA) is widely used but lacks temporal resolution. We aim to compare CC evaluation by sCTA and multiphase CTA (mCTA) as predictors of outcome in endovascular treated patients. Methods: Consecutive endovascular treated patients with M1 middle cerebral artery (MCA) or terminal intracranial carotid artery (TICA) occlusion confirmed by sCTA were included. Two more CTA acquisitions with 8- and 16-second delays were performed for mCTA. Endovascular thrombectomy was performed independently of the CC status according to a local protocol [Alberta Stroke Program Early CT score (ASPECTS) >6, modified Rankin scale (mRS) score <3]. CC on sCTA and mCTA were compared. Results: 108 patients were included. Their mean age was 69.6 ± 13 years and their median National Institutes of Health Stroke Scale (NIHSS) score was 17 (interquartile range 8). 79 (73.1%) had M1 MCA and 29 (26.9%) TICA occlusions. The mean time from symptom onset to CTA was 146.8 ± 96.5 min. On sCTA, 50.9% patients presented good CC vs. 57.5% on mCTA. Good CC status in both sCTA and mCTA had a lower 24-hour infarct volume (27.4 vs. 74.8 cm3 on sCTA, p = 0.04; 17.2 vs. 97.8 cm3 on mCTA, p < 0.01). However, only good CC on mCTA was associated with lower 24-hour (5 vs. 8.5, p = 0.04) and median discharge NIHSS (2 vs. 4.5, p = 0.04) scores and functional independency (mRS score <3) at 3 months (76.9 vs. 23.1%, p < 0.01). In a logistic regression model including age, NIHSS, ASPECTS and recanalization, only age (OR 0.96, 95% CI 0.93-0.99, p = 0.02) and good CC on mCTA (OR 5, 95% CI 1.99-12.6, p < 0.01) were independent predictors of functional outcome at 3 months. Conclusion: CC evaluation by mCTA is a better prognostic marker than CC evaluation by sCTA for clinical and functional endpoints in acute stroke patients treated with endovascular thrombectomy.
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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 | 0.002 |
| 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".