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Record W4282928545 · doi:10.1161/strokeaha.121.038088

TAGE Score for Symptomatic Intracranial Hemorrhage Prediction After Successful Endovascular Treatment in Acute Ischemic Stroke

2022· article· en· W4282928545 on OpenAlexaboutno aff
Paul Janvier, Basile Kerleroux, Guillaume Turc, Marco Pasi, Wassim Farhat, Nicolas Bricout, Joseph Benzakoun, Laurence Legrand, Frédéric Clarençon, Serge Bracard, Catherine Oppenheim, Grégoire Boulouis, Hilde Hénon, Olivier Naggara, Wagih Ben Hassen

Bibliographic record

VenueStroke · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)CohortOdds ratioIschemic strokeInternal medicineSurgeryIschemia

Abstract

fetched live from OpenAlex

Background: Determine if early venous filling (EVF) after complete successful recanalization with mechanical thrombectomy in acute ischemic stroke is an independent predictor of symptomatic intracranial hemorrhage (sICH) and integrate EVF into a risk score for sICH prediction. Methods: Consecutive patients with anterior acute ischemic stroke treated by mechanical thrombectomy issued from patients enrolled in the THRACE trial (Thrombectomie des Artères Cérébrales) and from 2 prospective registries were included and divided into a derivation (Center I; n=402) and validation cohorts (THRACE and center 2; n=507). EVF was evaluated by 2 blinded readers. sICH was defined according to the modified European cooperative acute stroke study II. Clinical and radiological data were analyzed in the derivation cohort (C1) to identify independent predictors of sICH and construct a predictive score test on the validation cohort (THRACE + C2). Results: Symptomatic ICH rate was similar between the two cohorts (9.9% and 8.9% respectively, P =0.9). Time from onset-to-successful recanalization >270 minutes (odds ratio [OR], 7.8 [95% CI, 2.5–24]), Alberta Stroke Program Early CT Score (≤5 [OR, 2.49 (95% CI, 1.8–8.1) or 6–7 [OR, 1.15 (95% CI, 1.03–4.46)]), glucose blood level >7 mmol/L (OR, 2.92 [95% CI, 1.26–6.7]), and EVF presence (OR, 11.9 [95% CI, 3.8–37.5]) were independent predictors of sICH and constituted the Time–Alberta Stroke Program Early CT–Glycemia–EVF score. Time–Alberta Stroke Program Early CT–Glycemia–EVF score was associated with an increased risk of sICH in the derivation cohort (OR increase per unit, 1.99 [95% CI, 1.53–2.59]; P <0.001) with area under the curve, 0.832 [95% CI, 0.767–0.898]. The score had good performance in the validation cohort (area under the curve, 0.801 [95% CI, 0.69–0.91]). Conclusions: Time–Alberta Stroke Program Early CT–Glycemia–EVF score is a simple tool with readily available clinical variables with good performances for sICH prediction after mechanical thrombectomy. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01062698.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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

Citations25
Published2022
Admission routes1
Has abstractyes

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