Occult Anterograde Flow Is an Under-Recognized but Crucial Predictor of Early Recanalization With Intravenous Tissue-Type Plasminogen Activator
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Thrombolysis depends on the ability of blood and thrombolytic agents to permeate thrombus. We devised a novel technique to quantify blood permeating through thrombi and determine whether this parameter predicts early recanalization with intravenous tissue-type plasminogen activator. METHODS: Intravenous tissue-type plasminogen activator-treated patients with stroke and complete occlusion on computed tomographic angiography were analyzed using perfusion computed tomography and a delay insensitive algorithm. We generated maps that measure delay in arrival time of contrast within the intracranial arterial tree (T0 maps). A positive sloped regression line of T0 values measured along artery silhouette distal to thrombus was defined as marker of permeable thrombus (occult anterograde flow). Median T0 values at proximal and distal thrombus interface were measured. Early recanalization was assessed on first angiography of subsequent intra-arterial procedure or on a 4-hour computed tomographic angiography. RESULTS: Of 66 patients, occult anterograde flow was detected in 17 (25.8%). Early recanalization was more in patients with occult anterograde flow versus not (66.7 versus 29.7%; P=0.031). Median T0 value (in s) at distal thrombus interface (1.5 versus 3.8; P=0.006) and difference in median T0 value between proximal and distal thrombus interface (1.3 versus 3.7; P=0.014) were less in early recanalizers versus in nonrecanalizers. In multivariable analysis, patients with occult anterograde flow and T0 value difference between proximal and distal thrombus interface ≤2 s recanalized most (71.4%; odds ratio, 12.15; 95% confidence interval, 2.05-71.91), whereas patients with retrograde flow and T0 value difference >2 s recanalized least (25.9%; odds ratio, 1). CONCLUSIONS: Occult anterograde flow through thrombus can be assessed by perfusion computed tomography T0 maps and predicts early recanalization with intravenous tissue-type plasminogen activator robustly.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".