Abstract WP62: Favorable Clot Characteristics Predict Smaller Infarct Volume in Acute Ischemic Stroke Patients Treated With Reperfusion Therapy
Bibliographic record
Abstract
Introduction: Multiple studies have correlated larger final infarct volume (FIV) with worse clinical outcomes. In INTERRSeCT , an international multicenter prospective cohort study, we sought to determine the favorable intracranial clot characteristics predicting smaller infarct volumes. Methods: FIV was measured (24 ±12 hours after baseline imaging) in 605 patients from INTERRSeCT study by blinded readers using Quantomo (Cybertrial Inc, Calgary). Clot Burden Score (CBS) is a 10-point scale with 10 referring to a completely patent ipsilateral anterior circulation from ICA to both M2 arteries, whereas 0 refers to a completely occluded ipsilateral anterior circulation. Residual Flow Grade (RFG) assesses the radiological permeability of the clot to contrast, with grade 0, 1, and 2 defined as no contrast, diffuse ghosting, and hairline lumen, respectively. Both of these scores were assessed by a blinded reader to the FIV. Using ordinal logistic regression, FIV was divided into deciles as the outcome. CBS and RFG were analyzed from 0 to 10, and 0 to 2, respectively. Two models were used, the first has no recanalization status, while the second included it. Results: The median FIVs with and without recanalization were 12.34 ml (IQR: 32.3 ml) and 22.15 ml (IQR: 60.12ml), respectively. CBS and RFG were independently predictive of FIV (p-value= <0.001 and 0.003, respectively). The common ORs for having one decile higher FIV for 1 point increase in CBS and RFG were 0.82 (CI: 0.77, 0.87) and 0.66 (CI: 0.51, 0.86), respectively. After adjusting for recanalization, the common ORs for having one decile higher FIV for 1 point increase in CBS and RFG were 0.83 (CI: 0.78, 0.88) and 0.72 (CI: 0.54, 0.94), respectively. Conclusions: Residual flow grade and clot burden score are fast and practical techniques for practitioners treating acute ischemic stroke patients. Favorable RFG and CBS independently, predict lower infarct volumes regardless of whether recanalization achieved.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".