Supplementary Material for: Early Anticipation of Candidacy for Intra-Arterial Reperfusion Therapy Based on Baseline Clinical Stroke Subtypes: Comparison with Multiparametric MRI Taken within 4.5 Hours from Stroke Onset
Bibliographic record
Abstract
Background: The decision to proceed with intra-arterial (IA) reperfusion therapy is typically made late in the course of in-hospital treatment for acute ischemic stroke. Early anticipation of candidacy for IA reperfusion therapy based on clinical stroke subtypes would be useful for guiding stroke management. The aim of this study was to investigate the relationship between the clinical Oxfordshire Community Stroke Project (OCSP) classification and MRI results taken within a 4.5-hour time window from stroke onset, with the hypothesis that the persistence of major arterial occlusion and extended ischemic penumbra, key criteria for proceeding with IA reperfusion therapy, would be distinctive between the clinical stroke subtypes. Methods: A total of 161 patients with acute ischemic stroke in the anterior circulation were included in this study. All patients were treated with intravenous alteplase, and MRI scans were performed following alteplase initiation. Prior to treatment, the patients were categorized, based on the OCSP classification scheme, as having total anterior circulation infarcts (TACI), partial anterior circulation infarcts (PACI), or lacunar infarcts (LACI). The relationship between OCSP subtypes, MRI parameters, and clinical variables was analyzed. Results: Overall, 40/161 patients (24.8%) were candidates for IA rescue reperfusion. With respect to the classification, 30/69 TACI (43.5%), 6/33 PACI (18.2%), and 4/59 LACI patients (6.8%) were candidates (p < 0.001). Major arterial occlusion was found in 56/161 patients (34.8%), and 46/69 TACI (66.7%), 6/33 PACI (18.2%), and 4/59 LACI patients (6.8%) had a major arterial occlusion (p < 0.001). A perfusion-diffusion mismatch greater than 20% was found in 85/161 patients (52.8%). More specifically, 40/69 TACI (58.0%), 25/33 PACI (75.8%), and 20/59 LACI patients (33.9%) had a perfusion-diffusion mismatch (p < 0.001). However, in terms of the total area of mismatch, 66.0% of patients with ASPECTSDWI-PWI ≥2 (Alberta Stroke Program Early CT Score) were classified as TACI patients (p < 0.001) and of the patients with ASPECTSDWI-PWI ≥3, 74.3% were classified as TACI patients (p < 0.001). Relative to candidates for IA rescue reperfusion, the clinical TACI group showed 75.0% sensitivity, 67.8% specificity, a positive predictive value of 43.5%, and a negative predictive value of 89.1%. Conclusions: In this study, patients classified as having clinical TACI were significantly more likely to be candidates for IA rescue reperfusion. Additionally, they incurred a higher incidence of persistent major arterial occlusion and had a penumbra area that was significantly larger than normal. Therefore, clinical OCSP can be used as an ‘early warning system' for IA reperfusion candidacy, which can allow for advanced preparation of IA therapy and theoretically shorten treatment time and reduce infarction.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.794 | 0.174 |
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".