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Record W4406994709 · doi:10.1161/str.56.suppl_1.tp15

Abstract TP15: Argatroban Among Patients with Acute Ischemic Stroke: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

2025· review· en· W4406994709 on OpenAlexaff
Adelina Dobromir Angheluta, Tetiana Zolotarova, Jeremy Y. Levett, Tara Seirafi, Kristian B. Filion, Mark J. Eisenberg

Bibliographic record

VenueStroke · 2025
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineMeta-analysisArgatrobanStroke (engine)Randomized controlled trialIschemic strokeSystematic reviewInternal medicineIntensive care medicineMEDLINEEmergency medicineIschemia

Abstract

fetched live from OpenAlex

Introduction: Argatroban, a direct thrombin inhibitor, is currently being investigated as a potential adjunct to the standard of care for the treatment of acute ischemic stroke (AIS). However, data regarding its impact on functional neurological outcomes have been inconclusive. Our objective was to compare neurological outcomes at 90 days among individuals with AIS randomized to argatroban with standard of care versus standard of care alone. Methods: We systematically searched MEDLINE, EMBASE, and Cochrane CENTRAL databases from their inception to July 2024 for randomized controlled trials of argatroban. The primary outcome was excellent functional outcome, as defined by a modified Rankin Scale (mRS) score of 0-1 at 90 days. The secondary endpoints were favorable functional outcome, defined by a mRS score of 0-2 at 90 days, and repeat stroke or other vascular events within 90 days. Safety endpoints included symptomatic intracranial hemorrhage and parenchymal hematoma at 90 days. Risk of bias was assessed using the Cochrane Risk of Bias Tool (RoB 2). Random-effects meta-analytic models were used to estimate pooled risk ratios (RRs) and 95% confidence intervals (CIs). Our protocol was preregistered on Open Science Framework (https://osf.io/tygwx/). Results: Four randomized controlled trials were included. A total of 1,595 participants were randomized to receive either argatroban with standard of care (n=807) or standard of care alone (n=788). Participants were mostly male (67.1%), and their median/mean age ranged from 57 to 69 years. When data were pooled across trials, the impact of argatroban on the likelihood to have a mRS score of 0-1 was inconclusive due to a wide CI (RR: 1.12; 95% CI: 0.88-1.41; I 2 : 63%) (Figure 1). Similar trends were observed for the other predefined outcomes. The RRs were 1.00 (95% CI: 0.87-1.14) for a mRS score of 0-2 (Figure 2) and 0.79 (95% CI: 0.44-1.44) for stroke or other vascular events. The pooled RRs for symptomatic intracranial hemorrhage and parenchymal hematoma were 1.09 (95% CI: 0.73-1.63) and 0.84 (95% CI: 0.48-1.47), respectively. Conclusions: Results were inconclusive due to small sample sizes. Currently, there is insufficient data to support the addition of argatroban to standard of care for the treatment of AIS. Evidence from available trials in this area supports the conduct of larger trials to determine the clinical value of argatroban.

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)0.018
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.041
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0230.029
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
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 head0.034
GPT teacher head0.330
Teacher spread0.296 · 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.

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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