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Record W2150649620 · doi:10.1161/jaha.113.000511

Clinical and Magnetic Resonance Imaging Predictors of Very Early Neurological Response to Intravenous Thrombolysis in Patients With Middle Cerebral Artery Occlusion

2013· article· en· W2150649620 on OpenAlexaboutno aff
Marion Apoil, Guillaume Turc, Marie Tisserand, David Calvet, Olivier Naggara, Valérie Domigo, Jean‐Claude Baron, Catherine Oppenheim, Emmanuel Touzé

Bibliographic record

VenueJournal of the American Heart Association · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombolysisMagnetic resonance imagingModified Rankin ScaleMiddle cerebral arteryStroke (engine)AntithromboticFibrinolytic agentOcclusionLeukoaraiosisInternal medicineLogistic regressionCardiologySurgeryRadiologyIschemiaIschemic strokeHyperintensity

Abstract

fetched live from OpenAlex

BACKGROUND: The early identification of patients who are unlikely to respond to intravenous recombinant tissue plasminogen activator (IV-tPA) could help select candidates for additional intra-arterial therapy or add-on antithrombotic drugs during the acute stage of stroke. Given that very early neurological improvement (VENI) is a reliable surrogate of early recanalization, we assessed the clinical and magnetic resonance imaging predictors of lack of VENI. METHODS AND RESULTS: We reviewed consecutive ischemic stroke patients with middle cerebral artery occlusion and treated within 4.5 hours by IV-tPA between 2003 and 2012 in our center, where magnetic resonance imaging is systematically implemented as first-line diagnostic workup. Lack of VENI was defined as a <40% decrease in baseline National Institutes of Health Stroke Scale (NIHSS) score 1 hour after start of IV-tPA. Poor outcome was defined as a 3-month modified Rankin scale ≥2. Associations between lack of VENI and potential determinants were assessed in logistic regression models. In all, 186 patients were included (median baseline NIHSS score, 16; median onset to treatment time, 155 minutes). One hundred forty-three patients (77%) had no VENI. The variables significantly associated with lack of VENI in multivariable analysis were baseline NIHSS (OR, 1.08; 95% CI, 1.01 to 1.16 per 1-point increase; P=0.03), onset to treatment time >120 minutes (OR, 2.94; 95% CI, 1.31 to 6.63; P=0.009) and diffusion weighted imaging--Alberta Stroke Programme Early CT Score ≤5 (OR, 3.60; 95% CI, 1.14 to 11.35; P=0.03). Patients without VENI were more likely to have a modified Rankin Scale ≥2 than those without VENI (68% versus 24%; OR, 5.01; 95% CI, 2.12 to 11.82) and less likely to have recanalization after 24 hours (OR, 0.41; 95% CI, 0.19 to 0.88). CONCLUSIONS: Lack of VENI provides an early estimate of 3-month outcome and recanalization after IV-tPA. Baseline NIHSS, onset to treatment time, and diffusion weighted imaging--Alberta Stroke Programme Early CT Score could help to predict lack of VENI and, in turn, might help early selection of candidates for complementary reperfusion strategies.

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)0.005
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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".

Quick stats

Citations18
Published2013
Admission routes1
Has abstractyes

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