MétaCan
Menu
Back to cohort
Record W4305082059 · doi:10.1161/strokeaha.122.037294

Recent Advances in Neuropsychological Outcomes and Intervention in Pediatric Stroke

2022· review· en· W4305082059 on OpenAlexaff
Lauren Krivitzky, Robyn Westmacott, Richard Boada, Leigh Sepeta, Lauren Reppert, Christine Mrakotsky

Bibliographic record

VenueStroke · 2022
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHospital for Sick Children
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineNeuropsychologyPediatric strokePsychosocialStroke (engine)Intervention (counseling)RehabilitationNeuroimagingCognitionPhysical medicine and rehabilitationNeuropsychological assessmentPsychiatryPhysical therapyIschemic stroke

Abstract

fetched live from OpenAlex

Over the past 15 years, there have been significant advances in the treatment of acute and chronic medical consequences of stroke in childhood. Given high rates of survival in pediatric stroke, practitioners are tasked with treating the ongoing motor and neuropsychological sequelae in patients over the course of their development. This article provides a review of the current literature on neuropsychological outcomes in pediatric stroke, including intelligence, academics, language, visual-spatial skills, attention, executive functions, memory, and psychosocial function. Recent developments in functional neuroimaging are discussed, with a particular focus on language outcomes. We further review the current research on cognitive and behavioral rehabilitation and introduce intervention models in pediatric stroke. In the final section, we discuss future directions for clinical practice and research in pediatric stroke.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.050
GPT teacher head0.373
Teacher spread0.323 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueStrokeSame topicCerebral Palsy and Movement DisordersFrench-language works237,207