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E-081 Prognostic role of parameters acquired by multiphase computed tomography angiography in acute stroke patients treated with endovascular reperfusion therapies

2018· article· en· W2905633382 on OpenAlexaboutno aff
Jin Wook Choi, Sukhyang Lee, Min-Ho Choi, Jehee Lee, Jeong Yeon Hong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombolysisReceiver operating characteristicAngiographyThrombusStroke (engine)Computed tomography angiographyConfidence intervalRadiologyCollateral circulationMultivariate analysisInternal medicineMyocardial infarction

Abstract

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Purpose We planned to compare the prognostic value of CT based parameters of infarct volume, collateral status, and thrombus burden in acute stroke patients treated with endovascular reperfusion therapy. Methods Consecutive patients treated with anterior circulation occlusions confirmed by multiphase CT angiography (mCTA) that performed endovascular reperfusion therapy were included. MCTA was performed as previously reported. Collaterals were evaluated by single phase CT angiography (sCTA) and mCTA. Alberta Stroke program early CT score (ASPECTS) was analyzed for infarct burden measurement. Clot burden score was assessed for thrombus burden. Factors associated with good outcome (3 month mRS of 0˜2) and poor outcomes (3 month mRS of 5˜6) were analysed. Results 84 patients were included. Intravenous thrombolysis was performed in 25%. Recan success was achieved in 75/84 (89.3%). A total of 49/84 (58.3%) were functionally independent at 3 months. For receiver operating curve analysis of good outcomes, C-statistics for sCTA was 0.683, followed by mCTA 0.645, and ASPECTS 0.620. However, when collateral status was incorporated in a multivariate analysis for predicting good outcomes including ASPECTS among other parameters, its significance faltered, while the significance of ASPECTS remained. For receiver operating curve analysis of good outcomes, c-statistics for sCTA was 0.758, followed by mCTA 0.740, and ASPECTS 0.603. In the multivariate analysis, both sCTA (odd ratio: 0.225, 95% confidence interval: 0.082–0.617, p=0.004) and mCTA (0.123, 0.027–0.565. p=0.007) predicted poor outcomes including ASPECTS among other parameters. Thrombus burden did not correlate with 3 month functional status. Conclusions Infarct volume accessed by ASPECTS strongly predict positive outcome, while collateral status accessed by CT are better markers of negative outcomes. The added benefit of multiphase CT in grading of collaterals for prognostication is not evident in this study. Disclosures J. Choi: None. S. Lee: None. M. Choi: None. S. Lee: None. J. Lee: None. J. Hong: None.

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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)0.003
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.212
Teacher spread0.206 · 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
Published2018
Admission routes1
Has abstractyes

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