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Spectrum of neurodevelopmental disabilities in children with cerebellar malformations

2011· article· en· W1562623763 on OpenAlexafffund
Marie-Ève Bolduc, Adré J. du Plessis, Nancy Sullivan, Omar Khwaja, Xun Zhang, Katherine Barnes, Richard L. Robertson, Catherine Limperopoulos

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2011
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsMontreal Children's HospitalMcGill University Health CentreMcGill University
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of HealthMcGill University Health CentreCanada Research ChairsMcGill University
KeywordsPediatricsAutismGross motor skillNeurodevelopmental disorderChild Behavior ChecklistAutism spectrum disorderCerebellumCognitive disabilitiesNeuroimagingMedicinePsychologyVineland Adaptive Behavior ScaleGestational ageGlobal developmental delayIntellectual disabilityMagnetic resonance imagingCognitionMotor skillPregnancyClinical psychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

AIM: Advances in perinatal care and neuroimaging techniques have increased the detection of cerebellar malformations (CBMs) in the fetus and young infant. As a result, this has necessitated a greater understanding of the neurodevelopmental consequences of CBMs on child development. The aim of this study was to delineate the impact of CBMs on long-term neurodevelopmental outcomes. METHOD: We conducted a cross-sectional study and systematically identified children with CBMs born between December 2000 and December 2006. We then performed follow-up magnetic resonance imaging studies, neurologic examination, and standardized neurodevelopmental outcome testing (Mullen Scales of Early Learning, Vineland Adaptive Behavior Scale, Child Behavior Checklist, Modified Checklist for Autism in Toddlers, and the Pediatric Quality of Life Inventory). RESULTS: Our sample comprised 49 children (29 males, 20 females; mean age, 28.4 mo, SD 16.4) with a CBM. Infants with evidence of acquired fetal or neonatal brain injury, intracranial birth trauma, inherited metabolic disease, or major pre- or postnatal cerebral ischemia were excluded. Our findings highlight that children with CBMs experience a high prevalence of neurologic, developmental, and functional disabilities including motor, cognitive, language, and social-behavioral deficits, as well as poor quality of life. The associated supratentorial anomalies, chromosomal findings, and malformations affecting the cerebellar vermis were significant independent predictors of neurodevelopmental disabilities in young children with CBMs. The associated supratentorial anomalies and chromosomal findings were also predictive of global developmental delay (p=0.01), cognitive impairment (p=0.03), gross and fine motor delay (p=0.02 and p=0.01 respectively), and positive screening for autism spectrum disorder (p=0.01). Additionally, malformations affecting the cerebellar vermis were significant independent predictors of expressive language (p=0.04) and gross motor delays (p=0.02). INTERPRETATION: Developmental surveillance and early intervention programs should be an integral part of the long-term follow-up of survivors of CBM.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.019
GPT teacher head0.210
Teacher spread0.191 · 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

Citations99
Published2011
Admission routes2
Has abstractyes

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