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Record W2996598467 · doi:10.7939/r3rx93v96

Effects of Perinatal Stroke on Executive Functioning in Children

2018· article· en· W2996598467 on OpenAlexaboutno aff
Wanqing Li

Bibliographic record

VenueUniversity of Alberta Library · 2018
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyStroke (engine)Developmental psychologyPhysical medicine and rehabilitationMedicineCognitive psychology

Abstract

fetched live from OpenAlex

Background: Individuals with childhood stroke often experience neurological injury that manifests as lifelong cognitive and behavioural impairment; however, research is scarce regarding the neurobehavioural outcomes of children with perinatal stroke. One important aspect of neurobehavioural functioning and cognitive development is executive functioning (EF). EF is predictive of functional life outcomes across many domains, of which include social and cognitive development, and behavioural, emotional, and mental health. EF is poorly understood in the childhood stroke population, and particularly in those with perinatal stroke (which occurs during pregnancy or within the first month after birth). Goals: The objectives of this research project were to: 1) elucidate the EF profiles of children with perinatal stroke from a cool and hot EF model, and 2) describe the association between demographic and clinical factors associated with EF outcomes following stroke. Participants: Eighteen children aged 6-16 with a diagnosis of perinatal stroke were recruited through the Alberta Perinatal Stroke Project (APSP) in Edmonton, Alberta. Participants were identified through the IRB-approved APSP stroke registry or by patient care clinics of pediatric neurologists. Method: Children underwent a neurobehavioural assessment, which was a measure of cool EF outcomes. Parents/guardians completed behavioural rating measures regarding their child’s EF in real-life situations, which was a measure of hot EF outcomes. Additionally, parents/guardians also filled out questionnaires that captured the child’s demographic background (age, sex, ethnicity, and family socioeconomic status) as well as medical characteristics (lesion size, lesion location, epilepsy presence). Results: On measures of cool EF, children with perinatal stroke were more impaired than the normative sample on almost all measures, including Animal Sorting, Response Set, Design Fluency, and Inhibition-Naming, Inhibition-Inhibition, and Inhibition-Switching (all p < 0.05). Auditory Attention was not significantly impaired in the perinatal stroke group. With regards to measures of hot EF, children with perinatal stroke were rated as significantly more impaired than the normative sample on domains of Shift, Working Memory, Task-Monitoring, Organization/Planning, and the Cognitive Regulation Index (all p < 0.05). Male children and children with a history of epilepsy demonstrated worse performance on several cool EF measures; age did not have a significant impact. At the group level, children with perinatal stroke performed within the low-average range on measures of global intellectual functioning (IQ), which was significantly lower than the normative population. Additionally, children with perinatal stroke who had a global IQ score in the below-average range had significantly worse EF outcomes than those with global IQ scores in the average range. Conclusions: Children with perinatal stroke demonstrated significantly more deficits than the normative population on measures of cool and hot EF. Additionally, children who were male and/or had comorbid epilepsy had more impairments in cool EF domains.

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)0.004
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 score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.174
Teacher spread0.171 · 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
Published2018
Admission routes1
Has abstractyes

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