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Abstract 10072: Stroke Topology and Neurodevelopment in Infants with Congenital Heart Disease: Does it Differ by Cardiac Physiology?

2021· article· en· W4226380900 on OpenAlexaff
Thiviya Selvanathan, Ting Guo, Min Sheng, Mike Seed, Anne Synnes, Shabnam Peyvandi, Liza Pulcine, Vann Chau, Linh Ly, James Barkovich, Patrick S. McQuillen, Steven P. Miller

Bibliographic record

VenueCirculation · 2021
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsTrillium Health CentreBC Children's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineLesionStroke (engine)CardiologyOdds ratioGreat arteriesHeart diseaseVentricleInternal medicineCognitionPediatricsPathologyPsychiatry

Abstract

fetched live from OpenAlex

Objectives: Vulnerability to brain injury in infants with congenital heart disease (CHD) may differ by CHD lesion. However, the link between arterial ischemic stroke (AIS) and neurodevelopment, and whether it differs by CHD lesion, is unknown. We sought to determine whether: (1) Stroke topology differs between infants with Transposition of the Great Arteries (TGA) and single ventricle physiology (SVP), and relationship with neurodevelopment;(2) Associations between stroke volume and neurodevelopment are CHD lesion specific. Methods: 64 of 312 CHD infants (TGA n=38, SVP n=26) studied prospectively with pre- and/or post-operative brain MRIs had AIS. AIS were segmented on 3DT1 and/or ADC images. 39 infants completed 18-month neurodevelopmental assessments with Bayley Scales (2 nd or 3 rd Edition); scores were adjusted to account for differences between versions. Adverse neurodevelopment was defined as <85 points. We used multivariable linear regression models to study associations between AIS volume and neurodevelopment, stratifying by CHD lesion and adjusting for study site. Probability maps demonstrating areas vulnerable to AIS and odds ratio maps reflecting likelihood of a lesion predicting adverse outcomes were developed. Results: Most AIS were in MCA territories, with a left-sided predominance (Fig 1A). Stroke volume did not differ between CHD groups (p=0.8). Basal ganglia lesions were most predictive of cognitive (max OR=11) and motor (max OR=6) outcomes (Fig 1B). Stratifying by CHD lesion, AIS volume predicted 18-month cognitive outcomes in infants with TGA (β=-0.6, 95%CI -1.0-(-0.1), p=0.02) but not SVP (β=7.9, 95%CI -72-88). AIS volume did not predict motor outcomes in infants with TGA (β=-0.6, 95%CI -1.6-0.3) or SVP (β=-19.7, 95%CI -91-52). Conclusions: Neonatal AIS topology does not differ between infants with TGA and SVP. AIS location and size are important predictors of neurodevelopment at 18 months though this association differs by CHD lesion.

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)0.005
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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
Published2021
Admission routes1
Has abstractyes

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