Abstract TMP11: Leptomeningeal Collaterals Predict Infarct Growth And 90 Day Clinical Outcome In Acute Ischemic Strokes Given Intra Arterial Therapy.
Bibliographic record
Abstract
Introduction: We tried to explore the role of lepto meningeal collaterals, baseline imaging to recanalization time in predicting infarct growth and final clinical outcome in acute ischemic strokes. Methods: Data is from a prospective study of consecutive acute stroke patients (2005-2009) from Keimyung University, Daegu,South Korea analysed at University of Calgary. Only patients with M1 MCA+/- intracranial ICA on baseline CT-angio, known stroke onset time with MR DWI at baseline and follow-up were included for analyses. Baseline infarct volume on DWI was calculated using Quantomo, a validated in house software. Infarct growth was calculated as difference in DWI volume between 24 hrs and baseline. Lepto meningeal collaterals at baseline CT-angio assesed using a previously published scale. Results: Of the 264 patients analysed 84 patients were eligible for the study. Of 84 patients [mean age 65.2 +/- 13 yrs, 52.4% male, median NIHSS 14 IQR=8.5, median time from onset of stroke symptom to baseline MR 164 mins, IQR 100.5) in the study, 59.5% achieved TIMI 2-3 recanalization and 35.7% good clinical outcome (mRS 0-2). Median baseline DWI volume was 31.6 ml (IQR 75); median infarct growth 29.8 ml (IQR 64.1). We noted significant correlation (spearman’s r=-0.68, p<0.001) between baseline DWI volume and collateral status and between infarct growth and collateral status (r=-0.38, p<0.01). No correlation (r=0.1, p=0.34) was noted between infarct growth and baseline MR to recanalization time. In patients with baseline DWI volume <=18 ml (group 1), 61.3% of patients achieved good clinical outcome when compared to 26.7% in patients with volume 18-80 ml (group 2) and 13% with volume >80 ml (group 3). Median infarct growth was lowest in group 1 (5.9 ml, IQR 52.7) followed by group 2 (30.5 ml, IQR 70.6) and group 3 (63 ml, IQR 108.1). Conclusion: Leptomeningeal collateral status determines baseline infarct volume and the extent of infarct growth until recanalization is 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 | 0.002 |
| 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) | 0.003 | 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".