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Record W2913815268 · doi:10.1161/str.50.suppl_1.wmp116

Abstract WMP116: Acute Infarct Volume in Childhood Stroke Can Be Accurately Estimated by Modelling Contraction of Chronic Infarction

2019· article· en· W2913815268 on OpenAlexaff
Kartik Reddy, David M. Mirsky, Amanda Kenny, Dianne Thornhill, Timothy J. Bernard, Nicholas Stence

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsThornhill Medical (Canada)
Fundersnot available
KeywordsMedicineIntraclass correlationBrain sizeInfarctionMagnetic resonance imagingCardiologyAcute strokeInternal medicineNuclear medicineMyocardial infarctionRadiology

Abstract

fetched live from OpenAlex

Introduction: Arterial ischemic stroke (AIS) occurs in 1-2 children/100,000/year. Most children have neurologic deficits post-AIS, but the influence of infarct volume on neurologic outcome is understudied. While acute infarct volume {best measured as a percentage of total brain volume infarcted (%aTBVi) in the growing brain} likely predicts outcome, acute scans are not always available in children. Chronic infarct volumes are underestimated by direct measurement due to contraction. A method for estimating acute infarct volumes from chronic scans is needed. We developed and compared the reliability of three methods for estimating the %aTBVi from values measured on chronic images. Methods: A retrospective IRB-approved study studying children (age 1 month-17 years) with AIS enrolled 158 patients. Those with acute (<3 days) and chronic (>90 days) MRIs were manually segmented by a pediatric neuroradiologist. Method 1 (direct method, used as control) estimated %aTBVi by measuring chronic infarct volume (cVI) and dividing by total brain volume. Method 2 (OFC method) estimated %aTBVi by subtracting the total non-infarcted brain volume from an extrapolated total brain volume based on orbitofrontal circumference (OFC). Method 3 (contraction method, Figure 1) used a regression model to apply a correction factor to the direct measurement of cVI that was then divided by total brain volume to estimate %aTBVi. Intraclass correlation compared estimated %aTBVi of the three methods to the gold standard %aTBVi calculated from manual segmentation of acute scans. Results: Inclusion criteria were met by 86 patients. The control direct method had excellent reliability (ICC 0.79), although it was exceeded by the contraction method (Figure 1, ICC=0.86), while the OFC method reliability was poor (ICC=0.42). Conclusion: %aTBVi is reliably estimated in children with AIS with only chronic imaging via the contraction method.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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 designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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