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Record W4398778410 · doi:10.1161/strokeaha.123.046056

Combining Early Ischemic Change and Collateral Extent for Functional Outcomes After Endovascular Therapy: An Analysis From AcT Trial

2024· article· en· W4398778410 on OpenAlexaffabout
Kõji Tanaka, Chitapa Kaveeta, Umberto Pensato, Jianhai Zhang, Fouzi Bala, Ibrahim Alhabli, MacKenzie Horn, Ayoola Ademola, Mohammed Almekhlafi, Aravind Ganesh, Brian Buck, Aleksander Tkach, Luciana Catanese, Dar Dowlatshahi, Jai Shankar, Alexandre Y. Poppe, Michel Shamy, Wu Qiu, Richard H. Swartz, Michael D. Hill, Tolulope T. Sajobi, Bijoy K. Menon, Andrew M. Demchuk, Nishita Singh

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Alberta HospitalOttawa HospitalHealth Sciences CentreManitoba HealthUniversity of OttawaMcMaster UniversityUniversity of ManitobaSunnybrook Health Science CentreKelowna General HospitalUniversité de MontréalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineModified Rankin ScaleInterquartile rangeComputed tomography angiographyStroke (engine)PopulationCollateral circulationRadiologyInternal medicineComputed tomographyIschemic strokeIschemia

Abstract

fetched live from OpenAlex

BACKGROUND: Early ischemic change and collateral extent are colinear with ischemic core volume (ICV). We investigated the relationship between a combined score using the Alberta Stroke Program Early Computed Tomography Score and multiphase computed tomography angiography (mCTA) collateral extent, named mCTA-ACE score, on functional outcomes in endovascular therapy–treated patients. METHODS: We performed a post hoc analysis of a subset of endovascular therapy–treated patients from the Alteplase Compared to Tenecteplase trial which was conducted between December 2019 and January 2022 at 22 centers across Canada. Ten-point mCTA collateral corresponding to M2 to M6 regions of the Alberta Stroke Program Early Computed Tomography Score grid was evaluated as 0 (poor), 1 (moderate), or 2 (normal) and additively combined with the 10-point Alberta Stroke Program Early Computed Tomography Score to produce a 20-point mCTA-ACE score. We investigated the association of mCTA-ACE score with modified Rankin Scale score ≤2 and return to prestroke level of function at 90 to 120 days using mixed-effects logistic regression. In the subset of patients who underwent baseline computed tomography perfusion imaging, we compared the mCTA-ACE score and ICV for outcome prediction. RESULTS: Among 1577 intention-to-treat population in the trial, 368 (23%; 179 men; median age, 73 years) were included, with Alberta Stroke Program Early Computed Tomography Score, mCTA collateral, and combination of both (mCTA-ACE score: median [interquartile range], 8 [7–10], 9 [8–10], and 17 [16–19], respectively). The probability of modified Rankin Scale score ≤2 and return to prestroke level of function increased for each 1-point increase in mCTA-ACE score (odds ratio, 1.16 [95% CI, 1.06–1.28] and 1.22 [95% CI, 1.06–1.40], respectively). Among 173 patients in whom computed tomography perfusion data was assessable, the mCTA-ACE score was inversely correlated with ICV (ρ=−0.46; P <0.01). The mCTA-ACE score was comparable to ICV to predict a modified Rankin Scale score ≤2 and return to prestroke level of function (C statistics 0.71 versus 0.69 and 0.68 versus 0.64, respectively). CONCLUSIONS: The mCTA-ACE score had a significant positive association with functional outcomes after endovascular therapy and had a similar predictive performance as ICV.

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)0.008
metaresearch head score (Gemma)0.010
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 score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.286
Teacher spread0.245 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

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