MétaCan
Menu
Back to cohort
Record W2103751774 · doi:10.1177/0883073811408609

Predictors of Quality of Life in Pediatric Survivors of Arterial Ischemic Stroke and Cerebral Sinovenous Thrombosis

2011· article· en· W2103751774 on OpenAlexaff
Sharon Friefeld, Robyn Westmacott, Daune MacGregor, Gabrielle deVeber

Bibliographic record

VenueJournal of Child Neurology · 2011
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsQuality of life (healthcare)MedicineStroke (engine)PediatricsThrombosisPediatric strokeSocioeconomic statusArterial Ischemic StrokePhysical therapyInternal medicineIschemic strokeIschemiaPopulation

Abstract

fetched live from OpenAlex

Predictors of quality of life can define potentially modifiable factors to increase favorable outcomes after pediatric stroke. Quality of life was measured using the Centre for Health Promotion's Quality of Life Profile (CHP-QOL) in 112 children surviving arterial ischemic stroke or cerebral sinovenous thrombosis at mean 3 years after stroke. Overall quality of life was poor in 17.8% children despite mean scores (3.52) in the "adequate" range. Quality of life related to school and play was most problematic and that related to physical and home environment was least problematic. Female gender, cerebral sinovenous thrombosis stroke, and older age at testing predicted reduced overall and domain-specific quality of life (P < .05), whereas neurological outcome and family socioeconomic status did not. Cognitive/behavioral deficit and low Verbal IQ adversely affected socialization and quality of life, especially among older children and females. Altered cognition/behavior has a major impact on quality of life after pediatric stroke. Implementation of ameliorative strategies warrants further study.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.248
Teacher spread0.225 · 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 teacher head, 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

Citations51
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Child NeurologySame topicNeonatal and fetal brain pathologyFrench-language works237,207