Abstract 2: Extensive Collateral Recruitment after Intravenous Thrombolysis in Acute Ischemic Stroke is Associated with Symptomatic Intracranial Haemorrhage
Bibliographic record
Abstract
Background: Various collateral channels are recruited to provide alternative pathways in acute ischemic stroke (AIS), however the relationship with patient outcomes remain unclear. We compared various existing methods of scoring collaterals on the pre-treatment and day-2 computed tomographic angiogram (CTA) of the brain in thrombolyzed AIS patients. Methods: We included 115 consecutive patients in whom CTA was performed both pre-tPA and on day-2. Intracranial collaterals were evaluated by 2 independent neuroradiologists using 4 existing and one modified method- Miteff’s system (grades middle cerebral artery (MCA) collateral branches with respect to sylvian fissure); Maas system (compares collaterals in affected hemisphere against the contralatral side); Modified Tan’s scale (collaterals in 50% or more of MCA territory classified as good); and 20-point collateral grading scale by Alberta Stroke Program Early CT score (ASPECTS) methodology. For the modified scoring system we adapted ASPECTS methodology into a 14 point score for cortical and internal cerebral veins (ICV) and removing basal ganglia area from scoring. Symptomatic intracranial hemorrhage (SICH) was defined by new bleeding on the CT scan and an increase in NIH stroke scale (NIHSS) by 4 points or more. Results: On univariate analysis collateral recruitment via the Tan scoring system, ASPECTS method (improvement of ≥6 points), modified scoring system (improvement ≥7 points), hypertension and higher NIHSS score were associated with SICH. On multivariate analysis only collateral recruitment on the Tan scoring system (OR 3.286 95% CI 1.014-11.025, p =0.049), Collateral recruitment on ASPECTS ≥6 points (OR 2.839 95% CI 1.064- 7.576, p = 0.037) and collateral recruitment on the modified scoring system ≥ 7 (OR 4.174 95% CI 1.212-14.372, p = 0.023) were independent predictors of SICH. Interestingly, collateral failure on the day-2 CTA did not show any association with SICH. Conclusion: Large recruitment of the collateral channels on the day-2 CTA is strongly associated with SICH after thrombolysis . Perhaps, an unregulated cerebral hyperperfusion contributed to SICH and close monitoring along with aggressive blood pressure control might prevent complications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".