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E-024 Aspiration thrombectomy on acute ischemic stroke patients with a low alberta stroke program early computerized tomography score

2021· article· en· W3183724614 on OpenAlexaboutno aff
Johanna T Fifi, Ameer E Hassan, O Zaidat

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePenumbraStroke (engine)OcclusionProspective cohort studyIschemic strokeSurgeryInternal medicineIschemia

Abstract

fetched live from OpenAlex

Introduction/Purpose For patients who receive endovascular therapy for acute ischemic stroke (AIS), a lower Alberta Stroke Program Early CT Score (ASPECTS) correlates with worse outcomes. However, AIS patients with a low ASPECTS may still have a better outcome after endovascular therapy than after best medical therapy. The purpose of this study was to determine the outcome of AIS patients with a low ASPECTS who undergo aspiration thrombectomy. Materials and Methods This is a subset analysis of a global prospective multicenter registry (COMPLETE) that enrolled adults with large vessel occlusion AIS and a pre-stroke mRS of 0-1 who underwent first-line aspiration thrombectomy with the Penumbra System. Data for patients with ASPECTS 2-5 were compared across lower and higher ASPECTS, patient age, baseline collateral flow (ASITN/SIR grade), and time to puncture groups. Results Of the 650 patients enrolled, 73 had ASPECTS 2-5. No significant difference was detected between ASPECTS 2-3 and ASPECTS 4-5, ≤ 80 and > 80 years old, collateral flow groups, or ≤ 6 and > 6 hours to puncture for rates of mTICI 2b-3 post-procedure, mRS 0-2 at 90 days, or symptomatic ICH at 24 hours. All-cause mortality rate at 90 days was significantly higher for ASPECTS 2-3 than for ASPECTS 4-5. There was a trend for higher sICH for time to puncture > 6 hours (p=0.09). mRS 0-2 at 90 days was achieved in only 18.8% of patients with ASITN 0-1 and in no patients > 80 years old. Conclusion Even in AIS patients with low ASPECTS, aspiration thrombectomy treatment can achieve a good functional outcome in some patients and should be considered. Disclosures J. Fifi: 1; C; Microvention, Penumbra, Stryker. 2; C; Microvention, Stryker. 4; C; Imperative Care. A. Hassan: 2; C; GE Healthcare, Genentech, Medtronic, Microvention, Penumbra, Stryker, Cerenovus, Viz.ai, Balt, Scientia. 3; C; GE Healthcare, Genentech, Medtronic, Microvention, Penumbra, Stryker, Cerenovus, Viz.ai, Balt, Scientia. O. Zaidat: 1; C; Genentech, Medtronic Neurovascular, Stryker. 2; C; Codman, Medtronic Neurovascular, National Institutes of Health StrokeNet, Penumbra, Stryker. 4; C; Galaxy Therapeutics, Inc.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.234
Teacher spread0.227 · 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 designObservational
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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