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Effect of dipyridamole during acute stroke: exploring antithrombosis and neuroprotective benefits

2010· review· en· W1569841568 on OpenAlexaff
Christopher D. d’Esterre, T‐Y Lee

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2010
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsRobarts Clinical TrialsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsDipyridamoleMedicineAntithromboticStroke (engine)NeuroprotectionThrombosisInflammationRegimenEndotheliumCardiologyAnesthesiaPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Currently, many stroke-prone individuals take antithrombotic drugs, which have known antiplatelet properties, to decrease stroke incidence. There is now evidence that this regimen could also reduce stroke severity through neuroprotective, nonplatelet mechanisms that include anti-inflammatory processes. Inflammation was found to play an important role in atherosclerosis/thrombosis development and acute stroke progression. In light of these findings, prevention strategies that target inflammatory mediators are under investigation. A common secondary stroke prevention therapeutic, dipyridamole, has shown promise for reducing stroke recurrence without increasing bleeding. In addition to its antiplatelet ability, dipyridamole has positive effects on vascular endothelium and inflammation. This review explores the effect of dipyridamole during acute stroke, revealing its potential use for improving poststroke clinical outcome.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.115
GPT teacher head0.366
Teacher spread0.251 · 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 designNot applicable
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

Citations16
Published2010
Admission routes1
Has abstractyes

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Same venueAnnals of the New York Academy of SciencesSame topicAntiplatelet Therapy and Cardiovascular DiseasesFrench-language works237,207