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Record W4406993008 · doi:10.1161/str.56.suppl_1.153

Abstract 153: Thrombectomy Versus Medical Therapy In Patients With Acute Ischemic Stroke Irrespective of The Alberta Stroke Program Early Computed Tomography Score. A Systematic Review And Meta-Analysis.

2025· review· en· W4406993008 on OpenAlexaboutno aff
Deivyd Vieira Silva Cavalcante, Uchenna Nweze, Patricia Asonye, Timothy Lee

Bibliographic record

VenueStroke · 2025
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Meta-analysisComputed tomographyIschemic strokeMedical therapyCardiologyInternal medicineRadiologyIschemia

Abstract

fetched live from OpenAlex

Background: The efficacy and safety of thrombectomy compared to medical therapy in patients with acute ischemic stroke irrespective of the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) has been debated. Method: We systematically searched EMBASE, PubMed and Scopus for randomized controlled trials (RCTs) and observational studies evaluating the efficacy and safety of thrombectomy compared to medical therapy in patients with acute ischemic stroke irrespective of the ASPECTS score with primary outcomes of modified rankin scale (mRS) score 0-3 at 90 days, functional independence mRS score 0-2 at 90 days and symptomatic intracranial hemorrhage (sICH). Results: We included 20 RCTs and 6 observational studies containing 6580 patients comparing thrombectomy with medical therapy in patients with acute ischemic stroke irrespective of the ASPECTS scores. The pooled results showed that mRS score 0-3 at 90days (RR = 2.10; 95% CI [1.59; 2.77]; I 2 = 71%; p < 0.001; Figure 1A) and mRS score 0-2 at 90 days (OR = 2.48; 95% CI [1.97; 3.12]; I 2 = 64%; p < 0.001; Figure 1B) were significantly improved by thrombectomy compared to the medical therapy. Early neurologic worsening (RR = 0.93; 95% CI [0.57; 1.51]; I 2 = 63%; p = 0.770; Figure 1C) was not significantly different between groups. The safety outcome, sICH within 48hrs (RR = 1.82; 95% CI [1.25; 2.64]; I 2 = 50%; p = 0.002; Figure 2A) was significantly higher in thrombectomy group. The National Institutes of Health Stroke Scale (NIHSS) score at 24hrs (MD = -2.84; 95% CI [-4.11; -1.58]; I 2 = 65%; p < 0.001; Figure 2B) and mean change in infarct volume from baseline at 24hrs (MD = -26.10; 95% CI [-40.18; -12.02]; I 2 = 97%; p < 0.001; Figure 2C) were significantly reduced by thrombectomy. However, decompressive craniotomy (RR = 1.17; 95% CI [0.78; 1.75]; I 2 = 20%; p = 0.453; Figure 2D) did not show any difference between groups. Death within 90 days (OR = 0.71; 95% CI [0.61; 0.81]; I 2 = 22%; p < 0.001; Figure 3A) was significantly reduced by thrombectomy. The early neurologic improvement (SMD = 3.43; 95% CI [2.39; 4.93]; I 2 = 37%; p < 0.001) and median EuroQol Group 5 Dimension (EQ-5D) index at 90days (MD = 0.15; 95% CI [0.07; 0.23]; I 2 = 84%; p < 0.001; Figure 3C) were also improved by thrombectomy. Conclusion: Compared with medical therapy, thrombectomy may improve functional outcomes in patients with acute ischemic stroke irrespective of the ASPECTS scores, despite associated with an increased risk of sICH.

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)0.010
metaresearch head score (Gemma)0.022
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: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.030
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.030
GPT teacher head0.322
Teacher spread0.292 · 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
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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