CT perfusion and angiographic assessment of pial collateral reperfusion in acute ischemic stroke: the CAPRI study
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to evaluate the correlation between a novel angiographic score for collaterals and CT perfusion (CTP) parameters in patients undergoing endovascular treatment for acute ischemic stroke (AIS). METHODS: 103 patients (mean age 66.7±12.7; 48.5% men) with AIS in the anterior circulation territory, imaged with non-contrast CT, CT angiography, and CTP, admitted within 8 h from symptom onset and treated with any endovascular approach, were retrospectively included in the study. Clinical, neuroradiological data, and all time intervals were collected. Careggi Collateral Score (CCS) was used for angiographic assessment of collaterals and the Alberta Stroke Program Early CT Score (ASPECTS) for semiquantitative analysis of CTP maps. Two centralized core laboratories separately reviewed angiographic data, whereas CT findings were evaluated by an expert neuroradiologist. Univariate and multivariate analysis were performed considering CCS both as an ordinal and a dichotomous variable. RESULTS: 37/103 patients (35.9%) received intravenous tissue plasminogen activator. Median (IQR) ASPECTS was 9 (6-10) for admission CT, 9 (5-10) for cerebral blood volume (CBV) maps, 3 (2-3) for mean transit time maps, 3 (2-4), for cerebral blood flow maps, and 5 (3-7) for CTP mismatch. Univariate analysis showed a significant correlation between CCS and ASPECTS for all CTP parameters. Multivariate analysis confirmed an independent association only between CCS and CBV (p=0.020 when CCS was considered as a dichotomous variable, p=0.026 with ordinal CCS). CONCLUSIONS: A correlation between angiographic assessment of the collateral circulation and CTP seems to be present, suggesting that CCS may provide an indirect evaluation of the infarct core volume to consider for patient selection in AIS.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".