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Record W3173393343 · doi:10.1161/str.51.suppl_1.wp103

Abstract WP103: Re-Examining the Exclusion Criterion of Early Recurrent Ischemic Stroke in Intravenous Thrombolysis: A Meta-Analysis

2020· article· en· W3173393343 on OpenAlexaff
Katrina Hannah D. Ignacio, Jose Danilo Bengzon Diestro, Adrian I. Espiritu, Julian Spears, María José

Bibliographic record

VenueStroke · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineThrombolysisStroke (engine)Meta-analysisObservational studyConfidence intervalModified Rankin ScaleFibrinolytic agentInternal medicineTissue plasminogen activatorIschemic strokeSurgeryIschemiaMyocardial infarction

Abstract

fetched live from OpenAlex

Background: Current guidelines for intravenous tissue plasminogen activator for acute ischemic stroke preclude the administration of the drug in patients with a history of recent stroke. Objectives: Our meta-analysis aims to determine the safety and efficacy of thrombolysis in patients with early recurrent ischemic stroke (within 3 months of initial stroke). Methods: Pubmed, Cochrane, Scopus, Embase, Clinicaltrials.gov , and HERDIN were searched for studies comparing the outcomes of acute stroke patients undergoing intravenous thrombolysis between those with early recurrent stroke (ERS) and those without. Random-effects meta-analysis was used to evaluate the outcomes in terms of symptomatic intracranial hemorrhage, mortality and good functional outcomes at 3 months (modified Rankin Score < 2 ) Results: Three observational studies with a total of 48,459 thrombolysed patients (824 with ERS and 47,635 without) were included in the study. There was no significant difference between patients with ERS and those without in terms of symptomatic intracranial hemorrhage (OR 1.39, 95% Confidence Interval [CI] 0.75-2.58), mortality (OR 1.36, 95% CI 0.60-3.09) and good functional outcomes at 3 months (OR 0.74, 95% CI 0.47-1.16). Conclusion: Our meta-analysis suggests that there is insufficient evidence to substantiate excluding patients with ERS from receiving thrombolysis. Further studies to re-examine ERS as an exclusion criterion for receiving thrombolysis are warranted.

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)0.064
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.339

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.112
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0210.095
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0040.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.076
GPT teacher head0.308
Teacher spread0.232 · 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
DomainMethods
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
Published2020
Admission routes1
Has abstractyes

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