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Record W2070987355 · doi:10.1080/09297049.2014.969694

Determinants of cognitive outcomes of perinatal and childhood stroke: A review

2014· review· en· W2070987355 on OpenAlex
Amanda Fuentes, Angela Deotto, Mary Desrocher, Gabrielle deVeber, Robyn Westmacott

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChild Neuropsychology · 2014
Typereview
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsHospital for Sick ChildrenYork University
Fundersnot available
KeywordsPediatric strokeStroke (engine)CognitionPsychosocialPsychologyEtiologyLateralityPsychological interventionLesionDevelopmental psychologyPopulationClinical psychologyPhysical medicine and rehabilitationMedicinePsychiatryIschemic stroke

Abstract

fetched live from OpenAlex

Our understanding of cognitive and behavioral outcomes of perinatal and childhood stroke is rapidly evolving. A current understanding of cognitive outcomes following pediatric stroke can inform prognosis and direct interventions and our understanding of plasticity in the developing brain. However, our understanding of these outcomes has been hampered by the notable heterogeneity that exists amongst the pediatric stroke population, as the influences of various demographic, cognitive, neurological, etiological, and psychosocial variables preclude broad generalizations about outcomes in any one cognitive domain. We therefore aimed to conduct a detailed overview of the published literature regarding the effects of age at stroke, time since stroke, sex, etiology, lesion characteristics (i.e., location, laterality, volume), neurologic impairment, and seizures on cognitive outcomes following pediatric stroke. A key theme arising from this review is the importance of interactive effects among variables on cognitive outcomes following pediatric stroke. Interactions particularly of note include the following: (a) age at Stroke x Lesion Location; (b) Lesion Characteristics (i.e., volume, location) x Neurologic Impairment; (c) Lesion Volume x Time Since Stroke; (d) Sex x Lesion Laterality; and (e) Seizures x Time Since Stroke. Further, it appears that these relationships do not always apply uniformly across cognitive domains but, rather, are contingent upon the cognitive ability in question. Implications for future research directions are discussed.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.374
Teacher spread0.336 · 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