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Record W4205449456 · doi:10.4103/0028-3886.333473

Assessment of Collaterals Using Multiphasic CT Angiography in Acute Stroke

2021· article· en· W4205449456 on OpenAlexaboutno aff
Santhosh Kumar Kannath, Bejoy Thomas, Enakshy Rajan Jayadevan, PN Sylaja, Chandrasekharan Kesavadas

Bibliographic record

VenueNeurology India · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiologyAngiographyConfidence intervalStroke (engine)Computed tomography angiographyGrading (engineering)Logistic regressionMiddle cerebral arteryCerebral angiographyInternal medicineIschemia

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The aim of the research was to compare the efficiency of multiphase and single-phase computed tomography (CT) angiography in assessing the leptomeningeal collaterals and in predicting the long-term clinical outcome as well as the risk of hemorrhagic transformation. MATERIALS AND METHODS: A prospective study was conducted from October 2016 to May 2018 in consecutive patients who presented within 8 hours of the onset of acute anterior circulation ischemic strokes, with NIHSS (National Institutes of Health Stroke Scale) scores ≥5. They underwent triple-phase cerebral CT angiography, and the collaterals were assessed separately using both single-phase and multiphase techniques. The ability of the collaterals to predict the 24-hour CT ASPECTS (Alberta Stroke Program Early CT score), risk of cerebral hemorrhagic transformation, and 90-day clinical outcome was assessed. RESULTS: Fifty-six patients, which included 42 with an involvement of the middle cerebral artery and 14 with mixed occlusions, were assessed. In the multivariate logistic analysis, multiphase CT angiography collateral grading is one of the independent predictors of favorable outcomes. Area under the curve (AUC) was 0.853 (95% confidence interval [CI; 0.73, 0.97]) for multiphase CT collateral scoring in predicting the long-term functional independence, whereas single-phase CT (sCT) scoring displayed an AUC value of only 0.609 (95% CI [0.43, 0.78]). Eighty-two percent of the patients with good multiphase CT collaterals were functionally independent. CT ASPECTS at 24 hours was significantly better in patients with a good multiphase CT collateral score than in those with a good single-phase score. None of the patients with good collaterals in multiphase CT angiography had a significant hemorrhagic transformation. Good multiphase CT collaterals demonstrated 78% sensitivity, 81% specificity, and 80% accuracy in predicting the functional outcome. CONCLUSION: Multiphase CT collateral system was superior to single-phase angiography in predicting the long-term functional outcomes. Prediction of the hemorrhagic transformation risk was also observed to be better for multiphase CT.

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)0.003
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.309
Teacher spread0.294 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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