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Record W4392478793 · doi:10.1161/svin.03.suppl_2.230

Abstract 230: Endovascular therapy for large core ischemic strokes: Meta‐analysis of randomized clinical trials

2023· article· en· W4392478793 on OpenAlexaff
Mohammad Hossein Abbasi, Ashkan Shoamanesh, David S. Liebeskind, Steven Warach, Hamidreza Saber

Bibliographic record

VenueStroke Vascular and Interventional Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineRandomized controlled trialMeta-analysisCore (optical fiber)Ischemic strokeInternal medicineIschemiaComputer science

Abstract

fetched live from OpenAlex

Introduction Background: Patients with acute strokes with large infarct size are traditionally excluded from endovascular therapies, as like as clinical care. However, questions remain with respect to the safety and efficacy of EVT in these patients. Methods We conducted a meta‐analysis based on pooled data from SELECT 2 trial [1], ANGEL‐ASPECT trial [2], RESCUE Japan [3], and HERMES study [4]. We explored the efficacy of EVT for large infarcts to achieve a favorable 90‐day modified Rankin Scale. Also, we compared favorable outcomes following EVT in those with a core infarct at baseline of more than 70 ml, delayed thrombectomy of more than 6 hours, older than 75 years, and those who received concomitant IV thrombolysis. We also examined the pooled rate of hemorrhagic transformation following EVT in large core strokes. Results This meta‐analysis showed a statistically significant higher rate of favorable outcome in subjects with extremely large infarct size who undergone EVT compared to those who were managed by medical therapy alone (RR: 1.41, 95% CI: [1.05‐1.98], p: 0.03). In the subgroups of patients with core size > 70ml (RR: 1.51, 95% CI: [1.23‐1.87]), late window presentation (LKN to randomization ≥ 6 hours), (RR: 1.53, 95% CI: [1.27‐1.84]), or those 75 or older than 75 years old (RR: 1.43, 95% CI: [1.12‐1.84]), EVT was associated with higher rates of favorable 90‐day mRS score of 0‐3 compared to medical therapy alone. However, EVT was not associated with better outcomes in those who received IV thrombolysis (RR: 1.37, 95% CI: [0.93‐2.01]. Based on pooled data from SELECT‐2, ANGEL‐ASPECT, and RESCUE Japan trials, the overall rate of early symptomatic hemorrhagic transformation among cases with ASPECT 0‐5 in the thrombectomy group was not significantly higher compared to patients who were managed non‐surgically (OR 1.75, 95% CI: [0.89‐3.47]). Conclusion Endovascular therapy is a reasonable option for the management of large infarcts. EVT results in favorable outcome by a delayed thrombectomy for a large core infarct and in older patients.

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)0.020
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.036
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0140.034
Bibliometrics0.0050.006
Science and technology studies0.0000.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.125
GPT teacher head0.410
Teacher spread0.285 · 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 designMeta-analysis
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
Published2023
Admission routes1
Has abstractyes

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