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Record W3182858056 · doi:10.3389/fneur.2021.685454

Outcomes and Treatment Complications of Intravenous Urokinase Thrombolysis in Acute Ischemic Stroke in China

2021· article· en· W3182858056 on OpenAlexaff
Rongrong Zhang, Hui Wei, Yu Ren, Yanping Wu, Yetao Luo, Lei Zhang, Yingchao Huo, Jinzhou Feng, Philippe P. Monnier, Xinyue Qin

Bibliographic record

VenueFrontiers in Neurology · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Natural Science Foundation of China
KeywordsMedicineUrokinaseThrombolysisUnivariate analysisOdds ratioMultivariate analysisStroke (engine)Retrospective cohort studyInternal medicineSurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

Background: Intravenous thrombolysis with alteplase benefits eligible patients with acute ischemic stroke. However, in some countries such as China, alteplase may be too expensive for low-income patients, and also for regions with low economic development. Urokinase is much less expensive than alteplase. This study aimed to assess the outcomes and treatment complications of urokinase in acute ischemic stroke patients, which are poorly understood. Methods: This multicenter retrospective study included acute ischemic stroke patients who received intravenous urokinase or alteplase from January 2014 to January 2018 at 21 centers in China. Outcomes and treatment complications were analyzed by univariate and multivariate analyses. Results: Among the 618 patients included in this study, 489 were treated with urokinase and 129 were treated with alteplase. Functional independence, no/minimal disability, mortality, intracranial hemorrhage (ICH), and symptomatic ICH did not significantly differ between the urokinase and alteplase groups in the univariate and multivariate analyses. However, the patients who received alteplase had a lower odds ratio (OR) of extracranial bleeding in the univariate analysis and a lower adjusted OR (aOR) in the multivariate analysis than the patients who received urokinase (OR = 0.410 [95% CI, 0.172–0.977], p = 0.038; aOR = 0.350 [95% CI, 0.144–0.854], p = 0.021). Furthermore, in patients treated with urokinase, the patients who received high-dose urokinase had a higher OR of extracranial bleeding in the univariate analysis and a higher aOR of extracranial bleeding in the multivariate analysis than patients who received low-dose urokinase (OR = 3.046 [95% CI, 1.696–5.470], p < 0.001; aOR = 3.074 [95% CI, 1.627–5.807], p = 0.001). Moreover, patients who received low-dose urokinase had similar outcomes and complications compared to patients treated with alteplase. Conclusions: Patients treated with urokinase had similar outcomes but a higher risk of extracranial bleeding compared to patients treated with alteplase. The risk of extracranial bleeding was higher in the patients treated with high-dose urokinase than in the patients treated with low-dose urokinase. Patients who received low-dose urokinase had similar outcomes and complications compared to patients treated with alteplase. In countries such as China where some acute ischemic stroke patients cannot afford alteplase, urokinase may be a good alternative to alteplase for intravenous thrombolysis.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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 designObservational
Domainnot available
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".

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Citations24
Published2021
Admission routes1
Has abstractyes

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