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Thrombolysis in the Developing World: Is There a Role for Streptokinase?

2013· review· en· W2024485514 on OpenAlexaff
Kenneth Butcher, Ashfaq Shuaib, Jeffrey L. Saver, Geoffrey A. Donnan, Stephen M. Davis, Bo Norrving, Ka Sing Wong, Foad Abd-Allah, Rohit Bhatia, Adnan Khan

Bibliographic record

VenueInternational Journal of Stroke · 2013
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineStreptokinaseThrombolysisAntithromboticFibrinolytic agentIntensive care medicineMyocardial infarctionStroke (engine)Clinical trialConcomitantTissue plasminogen activatorCardiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Intravenous thrombolysis with tissue plasminogen activator is the only proven acute therapy for ischemic stroke. This therapy has not been translated into clinical practice in the developing world primarily due to economic constraints. Streptokinase, a lower cost alternative thrombolytic agent, is widely available in developing countries where it is utilized to treat patients with acute coronary syndromes. Although this drug has previously been found to be ineffective in ischemic stroke, the lack of benefit may have been related to a number of factors related to trial design rather than the drug itself. Specific features of prior trial designs that may have adversely affected outcomes include a prolonged treatment window, inclusion of patients with established infarction on computed tomography scan, failure to treat excessive arterial pressures, a fixed dose of streptokinase, and concomitant use of antithrombotic medications. Given the lack of therapeutic alternatives in developing countries, a new trial of streptokinase in acute stroke, utilizing stricter inclusion criteria similar to those in more recent thrombolytic studies, appears 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.366
Teacher spread0.318 · 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 designSystematic review
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

Citations27
Published2013
Admission routes1
Has abstractyes

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