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Record W3085084170 · doi:10.1111/ene.14509

Predictive factors of functional independence after optimal reperfusion in anterior circulation ischaemic stroke with indication for intravenous thrombolysis plus mechanical thrombectomy

2020· article· en· W3085084170 on OpenAlexaboutno aff
Nolwenn Riou-Comte, Françis Guillemin, Benjamin Gory, Bertrand Lapergue, François Zhu, Marc Soudant, Michel Piotin, Lisa Humbertjean, Gioia Mione, Jonathan LaCour, René Anxionnat, Gabriela Hossu, Serge Bracard, Sébastien Richard

Bibliographic record

VenueEuropean Journal of Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombolysisOdds ratioModified Rankin ScaleConfidence intervalLogistic regressionInternal medicineStroke (engine)CardiologySurgeryIschemiaIschemic strokeMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Intravenous thrombolysis plus mechanical thrombectomy (IVT + MT) is the best current management of acute stroke due to large-vessel occlusion and results in optimal reperfusion for most patients. Nevertheless, some of these patients do not subsequently achieve functional independence. The aim was to identify baseline factors associated with 3-month independence after optimal reperfusion and to validate a prediction model. METHODS: All consecutive patients with intracranial anterior large-vessel occlusion, with indication for IVT + MT and achieving optimal reperfusion (defined as modified Treatment in Cerebral Ischaemia score 2b-3), from the THRACE trial and the ETIS registry, were included in order to identify a prediction model. The primary outcome was 3-month independence [modified Rankin Scale (mRS) score ≤ 2]. Multivariate inferences invoked forward logistic regression, multiple imputation and bootstrap resampling. Predictive performance was assessed by c-statistic. Model validation was conducted on patients from the ASTER trial. RESULTS: Amongst 139 patients (mean age 65.5 years; 54.3% female), predictors of 3-month mRS ≤ 2 (n = 82) were younger age [odds ratio 0.62 per 10-year increase; 95% confidence interval (CI) 0.53-0.72] and higher Alberta Stroke Program Early Computed Tomography Score (ASPECTS) (odds ratio 1.65 per 1-point increase; 95% CI 1.47-1.86) with c-statistic 0.77. Model validation (n = 104/181 patients with 3-month mRS ≤ 2) demonstrated a moderate discrimination (c-statistic 0.74; 95% CI 0.66-0.81) combining age and ASPECTS. The validation model was improved by the adjunction of three candidate variables that were found to be predictors. Addition of baseline National Institutes of Health Stroke Scale (NIHSS) score, history of vascular risk factor and onset-to-reperfusion time significantly improved discrimination (c-statistic 0.85; 95% CI 0.83-0.87). CONCLUSIONS: After optimal reperfusion, younger age, higher ASPECTS, lower NIHSS score, shorter onset-to-reperfusion time and absence of vascular risk factor were predictive of independence and could help to guide patient management.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.233
Teacher spread0.214 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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