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Record W6992586940

Longitudinal Neurocognitive Trajectories In Perinatal Arterial Ischemic Stroke

2024· other· en· W6992586940 on OpenAlexafffund

Bibliographic record

VenueYork University Digital Library (York University) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchFondation Brain Canada
KeywordsNeurocognitiveNeuropsychologyStroke (engine)Longitudinal studyLesionPediatric stroke
DOInot available

Abstract

fetched live from OpenAlex

Perinatal stroke occurs between 20 weeks gestation and 28 days postnatally, with arterial ischemic strokes (AIS) the most common subtype. Research regarding neurocognitive outcomes following perinatal AIS has been primarily cross-sectional with contradictory results given methodological variability (small cohorts, varying age at assessment, differing/non-standardized measures, limited follow-up, mixed populations). No research has characterized neurocognitive trajectories across multiple time points spanning critical developmental periods. Methods: These studies were the first evaluation of neurocognitive trajectories for individuals followed longitudinally at The Hospital for Sick Children across: 1) infancy and early childhood (Study 1; N=40; neonatal AIS), and 2) early and late childhood, adolescence, and early adulthood (Study 2; N=208; perinatal AIS). For Study 1, children underwent developmental assessment(s) at 18- and/or 36-months (Bayley) and neuropsychological assessment(s) from ages 4-13 years (WPPSI/WISC/WASI). For Study 2, individuals underwent neuropsychological assessment(s) from ages 2-25 years (WPPSI/WISC/WASI/WAIS). Predictors included sex, lesion volume, lesion laterality, seizure disorder, neurological diagnoses, medical comorbidities, perinatal AIS type, and early screening. Exploratory multilevel growth curve modelling was used to assess longitudinal neurocognitive trajectories, and to examine main or moderating effects of predictors. Results: Despite age-appropriate functioning statistically extrapolated at stroke occurrence, neurocognitive decline was found across 1) infancy and early childhood and 2) early and late childhood, adolescence, and early adulthood. For neonatal AIS and perinatal AIS, lesion volume moderated neurocognitive change. For neonatal AIS, medical comorbidities (congenital heart disease, genetic conditions) negatively impacted neurocognition at stroke occurrence (main effect) and early screening in infancy positively impacted neurocognition over time. For perinatal AIS, seizure disorder status and perinatal AIS type moderated neurocognitive change. Conclusions: In keeping with the early vulnerability hypothesis, neurocognitive decline was observed across development following perinatal AIS. Lesion volume and seizure disorders had moderating effects on neurocognition whereas medical comorbidities had a main effect; however, differences were apparent for perinatal AIS types. Perinatal AIS type moderated neurocognition such that presumed perinatal AIS involved rapid neurocognitive decline initially followed by improvements relative to neonatal AIS, which demonstrated consistent decline. Understanding neurocognitive trajectories and relevant predictors will inform the early identification of high-risk groups and the implementation of precision-based interventions.

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)0.007
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 score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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
Published2024
Admission routes2
Has abstractyes

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