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Record W2292282021 · doi:10.1161/str.44.suppl_1.a11

Abstract 11: Comparison Of Various Methods Of Assessment Of Intracranial Collaterals On The Pretreatment Ct-angiograms To Predict Outcomes In Acute Anterior Circulation Ischemic Stroke

2013· article· en· W2292282021 on OpenAlexaboutno aff
Leonard L.L. Yeo, Benjamin R. Wakerley, Aftab Ahmad, Prakash Paliwal, Kay Wei Ping Ng, ong C chong, Teoh Hock Luen, Bernard Chan, Raymond C.S. Seet, narayanaswamy venketsubramanian, Rahul Rathakrishnan, Yohanna Kusuma, Vijay K. Sharma

Bibliographic record

VenueStroke · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCollateral circulationMiddle cerebral arteryModified Rankin ScaleStroke (engine)ThrombolysisDiabetes mellitusRadiologyDemographicsCardiologyInternal medicineSurgeryNuclear medicineIschemic strokeIschemia

Abstract

fetched live from OpenAlex

Background: The presence of effective collateral blood flow patterns may influence response to intravenously administered tissue plasminogen activator (IV-tPA) in acute ischemic stroke (AIS). We compared various existing methods of scoring collaterals on the pre-treatment computed tomographic angiogram (CTA) of the brain for a reliable prediction of functional outcome in AIS patients. Methods: Consecutive AIS patients treated with IV-tPA within 4.5 hours of symptom-onset during 2007-2011 were included. Data were collected for demographics, vascular risk factors, National Institute of Health Stroke Scale (NIHSS) scores and stroke subtypes. Intracranial collaterals were evaluated by 2 independent blinded neuroradiologists via 4 predefined criteria- Miteff’s system that grades middle cerebral artery (MCA) collateral branches with respect to the sylvian fissure; Maas system that compares collaterals on the affected hemisphere against the unaffected side; modified Tan’s scale where collaterals in 50% or more of the MCA territory are classified as good; and a 20-point collateral grading scale in regions corresponding to Alberta Stroke Program Early CT score (ASPECTS) methodology. Good functional outcomes at 3-months were determined by modified Rankin scale (mRS) scores of 0-1. Results: CTA was performed in 115 patients with anterior circulation AIS before IV-tPA bolus. Median age 66yrs (range 35-92), 42% males, median NIHSS 19 points (range 3-30) and median onset-to-treatment time 155 minutes. Overall, 52 (45.2%) patients achieved good functional outcome at 3-months. Univariable analysis revealed younger age, absence of diabetes, lower pre-tPA NIHSS scores and good collaterals according to ASPECTS methodology as significantly associated with good functional outcomes. On multivariable logistic regression, only lower NIHSS (OR 1.111 per NIHSS point; 95% CI 1.023-1.206, p=0.013) and good collaterals by ASPECTS methodology (OR 1.117 per point; 95%CI 1.006-1.241, p=0.039) were found as independent predictors of good outcomes. Conclusion: Of the existing intracranial collaterals scoring systems, only the ASPECTS methodology serves as a reliable predictor of favorable outcomes at 3-months in patients with anterior circulation AIS.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.361
Teacher spread0.338 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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