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Record W2227417768 · doi:10.1161/str.43.suppl_1.a1911

Abstract 1911: Recanalization of Proximal Arterial Occlusion in the SENTIS Trial

2012· article· en· W2227417768 on OpenAlexaff
David S. Liebeskind, Ashfaq Shuaib, Martin Köhrmann, William P. Dillon, Songling Liu, Raul G. Nogueira, Peter D. Schellinger

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsDillon ConsultingUniversity of Alberta
Fundersnot available
KeywordsMedicineOcclusionStroke (engine)TIMIAngiographyLogistic regressionUnivariate analysisRandomized controlled trialCollateral circulationInternal medicineThrombolysisCardiologySurgeryMultivariate analysisMyocardial infarction

Abstract

fetched live from OpenAlex

Background: Collateral circulation may enhance recanalization in acute ischemic stroke. Augmentation of collaterals with partial aortic occlusion may promote recanalization and thereby influence outcomes in the SENTIS randomized controlled trial of the NeuroFlo device. We conducted a post hoc analysis of angiography acquired in SENTIS to evaluate potential differences in recanalization rates between NeuroFlo-treated and non-treated arms, accounting for site of arterial occlusion. Methods: Blinded imaging expert review of baseline and 6-hour follow-up angiography (CTA, MRA, or DSA) from the core lab was conducted for evaluation of recanalization. Recanalization was defined as TIMI 2-3 in the arterial segment distal to baseline occlusion. Baseline demographics, stroke presentation characteristics, and medical history variables were analyzed with respect to recanalization in univariate and subsequent multivariable logistic regression models after adjusting by treatment arm. Results: Serial angiography was available in 109/515 SENTIS subjects, including 56 in the treatment arm and 53 in the non-treated arm. Baseline demographics, stroke presentation characteristics, and medical history variables did not differ statistically between arms. Across all sites of arterial occlusion, recanalization occurred in 25.7% of cases, with similar rates between device (25.0%) and medical therapy (26.4%) arms. Age and baseline stroke severity (NIHSS score) were significant predictors of recanalization in univariate analyses. Multivariable logistic regression analyses confirmed that baseline NIHSS score was the sole predictor of recanalization (OR 0.90, p=0.0458) per one unit increase, with decreased recanalization in more severe strokes. Device treatment was not associated with significant increases in recanalization rates (p=NS). Recanalization of terminal internal carotid artery (12.5%), proximal MCA or M1 (17.9%) and M2 (46.7%) occlusions was not different between arms (all p=NS). Recanalization of proximal arterial occlusion in acute ischemic stroke cases enrolled in SENTIS was more frequent in M2 occlusions. Conclusions: More severe strokes at baseline were less likely to recanalize and device therapy did not increase recanalization rates. Treatment with the NeuroFlo device may invoke mechanisms of collateral perfusion distinct from direct arterial recanalization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.021
GPT teacher head0.286
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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