Factors associated with early reperfusion improvement after intra-arterial fibrinolytics as rescue for mechanical thrombectomy
Bibliographic record
Abstract
Objective:To identify factors associated with early angiographic reperfusion improvement (EARI) following intra-arterial fibrinolytics (IAF) after failed or incomplete mechanical thrombectomy (MT).Methods:A subset of patients treated with MT and IAF rescue after incomplete reperfusion included in the INFINITY (INtra-arterial FIbriNolytics In ThrombectomY) multicenter observational registry was analyzed. Multivariable logistic regression was used to identify factors associated with EARI. Heterogeneity of the clinical effect of EARI on functional independence (defined as modified Rankin Score ≤2) was tested with interaction terms.Results:A total of 228 patients (median age: 72 years, 44.1% female) received IAF as rescue for failed or incomplete MT and had a post-fibrinolytic angiographic control run available (50.9% EARI). A cardioembolic stroke origin (adjusted odds ratio (aOR) 3.72, 95% confidence interval (CI) 1.39–10.0) and shorter groin puncture to IAF intervals (aOR 0.82, 95% CI 0.71–0.95 per 15-min delay) were associated with EARI, while pre-interventional thrombolysis showed no association (aOR 1.15, 95% CI 0.59–2.26). The clinical benefit of EARI after IAF seemed more pronounced in patients without or only minor early ischemic changes (Alberta Stroke Program Early Computed Tomography Score (ASPECTS) ≥9, aOR 4.00, 95% CI 1.37–11.61) and was absent in patients with moderate to severe ischemic changes (ASPECTS ≤8, aOR 0.94, 95% CI 0.27–3.27, <i>p</i> for interaction: 0.095).Conclusion:Early rescue and a cardioembolic stroke origin were associated with more frequent EARI after IAF. The clinical effect of EARI seemed reduced in patients with already established infarcts. If confirmed, these findings can help to inform patient selection and inclusion criteria for randomized-controlled trials evaluating IAF as rescue after MT.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".