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Record W4306403434 · doi:10.1161/strokeaha.122.039717

Comparison of Three Scores of Collateral Status for Their Association With Clinical Outcome: The HERMES Collaboration

2022· article· en· W4306403434 on OpenAlexaffabout
Henrik Gensicke, Fahad Al-Ajlan, Joachim Fladt, Bruce Campbell, Charles B.L.M. Majoie, Serge Bracard, Michael D. Hill, Keith W. Muir, Andrew M. Demchuk, Luís San Román, Aad van der Lugt, David S. Liebeskind, Scott Brown, Phil White, Françis Guillemin, Antoni Dávalos, Tudor G. Jovin, Jeffrey L. Saver, Diederik W.J. Dippel, Mayank Goyal, Peter Mitchell, Bijoy K. Menon

Bibliographic record

VenueStroke · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
FundersNational Institute for Health and Care Research
KeywordsMedicineModified Rankin ScaleStroke (engine)RadiologyCollateral circulationAngiographyLogistic regressionComputed tomographic angiographyOcclusionComputed tomography angiographyNuclear medicineInternal medicineIschemic strokeIschemia

Abstract

fetched live from OpenAlex

Background: Leptomeningeal collateral status on baseline computed tomographic angiography (CTA) is associated with clinical outcome after acute ischemic stroke treatment. However, assessment of collateral status is not uniform. To compare 3 different CTA collateral scores (CS) and imaging techniques about their association with clinical outcome. Methods: Pooled analysis of patient-level data from the Highly Effective Reperfusion Using Multiple Endovascular Devices collaboration. Patients with large vessel occlusion from 7 randomized controlled trials that compared endovascular thrombectomy with standard medical care were included. Three different CS (Tan CS, regional CS [rCS], and regional Alberta Stroke Program Early CT Score CS) and 2 imaging techniques (single-phase [sCTA] and multiphase/dynamic CTA) were evaluated. Functional independence (modified Rankin Scale score 0–2) at 3 months poststroke was the primary outcome. Furthermore, we assessed the effect of sCTA image acquisition time on collateral status assessment using an adjusted ordinal logistic regression model to obtain predicted values for the trichotomized rCS. Results: Among 1147 pooled patients, 948 (82.7%) had sCTA and 199 (17.3%) multiphase/dynamic CTA as baseline angiography. With all 3 collateral scales, better CSs were associated with better 3-month functional outcome. With sCTA images, the rCS (area under the curve [AUC] 0.63) and regional Alberta Stroke Program Early CT Score CS (AUC 0.62) better predicted functional outcome than the Tan CS (AUC 0.60, respectively; P <0.001 and P =0.02). With multiphase/dynamic CTA images, all collateral scales performed similarly in predicting functional outcome (rCS [AUC 0.61]; regional Alberta Stroke Program Early CT Score CS [AUC 0.61] versus Tan CS [AUC 0.61], respectively; P =0.93 and P =0.91). Overall, no endovascular thrombectomy treatment effect modification by collateral status (rCS) was demonstrated ( P =0.41). sCTA timing independently influenced CS assessment. On earlier timed sCTA, the predicted proportions of scans with poor collaterals was higher and vice versa. Conclusions: In this data set of highly selected patients with stroke, using a regional CS on sCTA likely allows for the most accurate prediction of functional outcome while on time-resolved CTA, the type of CS did not matter. Patients across all collateral grades benefit from endovascular thrombectomy. sCTA timing independently influenced CS assessment.

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)0.041
metaresearch head score (Gemma)0.038
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 score0.041
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.038
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.371
Teacher spread0.320 · 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

Citations33
Published2022
Admission routes2
Has abstractyes

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