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Record W4417329870 · doi:10.1590/1806-9282.20250918

Echocardiographic predictors of futile recanalization in acute ischemic stroke

2025· article· en· W4417329870 on OpenAlexaboutno aff
Özgür Ertuğrul, Fırat Karaaslan, Rasih Yılmaz, Mehmet Cudi Tuncer

Bibliographic record

VenueRevista da Associação Médica Brasileira · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)Ejection fractionStroke volumeAcute strokeComputed tomography

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the study was to investigate the relationship between echocardiographic parameters and clinical outcomes in acute ischemic stroke patients undergoing mechanical thrombectomy, aiming to identify predictors of poor prognosis despite successful recanalization. METHODS: This retrospective, single-center study included 320 acute ischemic stroke patients treated with mechanical thrombectomy for large vessel occlusion. Demographic, clinical, and echocardiographic data were collected. Univariable and multivariable logistic regression and receiver operating characteristic analyses were used. Futile recanalization was defined as achieving modified Thrombolysis in Cerebral Infarction 2b-3 with a poor functional outcome (mRS 3-6). RESULTS: Of the 320 patients, 176 (55%) were classified as favorable and 144 (45%) as futile recanalization. The futile group had a higher mean age (77.3±12.7 vs. 67.6±12.8; p<0.001), National Institutes of Health Stroke Scale score (median 17 vs. 14; p=0.007), and puncture-to-recanalization time (47.5 vs. 30 min; p=0.017), and lower Alberta Stroke Program Early Computed Tomography score (7.5 vs. 10; p<0.001). Echocardiographically, they had lower left ventricular ejection fraction (55 vs. 57.5%; p=0.036) and larger left ventricular end-diastolic diameter (4.8 vs. 4.5 cm; p=0.002). Multivariable analysis identified low Alberta Stroke Program Early Computed Tomography score (OR 0.192; p=0.002), high National Institutes of Health Stroke Scale (OR 1.212; p=0.029), and low left ventricular ejection fraction (OR 0.919; p=0.047) as independent predictors. Alberta Stroke Program Early Computed Tomography had the highest predictive value (area under the curve : 0.851), followed by left ventricular ejection fraction (area under the curve: 0.631), while National Institutes of Health Stroke Scale showed lower predictive power (area under the curve: 0.326). CONCLUSION: Poor outcomes after mechanical thrombectomy are associated with low Alberta Stroke Program Early Computed Tomography scores, high National Institutes of Health Stroke Scale, and reduced left ventricular ejection fraction. Echocardiographic evaluation, particularly of left ventricular ejection fraction, may aid in prognostication and treatment planning in acute ischemic stroke.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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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Citations0
Published2025
Admission routes1
Has abstractyes

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