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Perinatal and neonatal predictors of developmental coordination disorder in very low birthweight children

2012· article· en· W2170844411 on OpenAlexafffundabout
Jill G. Zwicker, Seongmin Yoon, Mark T. Mackay, Julie Petrie‐Thomas, Margaret Rogers, Anne Synnes

Bibliographic record

VenueArchives of Disease in Childhood · 2012
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsB.C. Women's Hospital & Health CentreUniversity of British ColumbiaChild and Family Research Institute
FundersCanadian Child Health Clinician Scientist ProgramMichael Smith Health Research BCChild and Family Research Institute
KeywordsMedicinePediatricsLow birth weightPregnancy

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify perinatal and neonatal risk factors associated with developmental coordination disorder (DCD) in very low birthweight children (VLBW: <1250 g). DESIGN: Retrospective design with prospectively collected cohort. SETTING: Neonatal Follow-Up Program, Vancouver, Canada. PATIENTS: 157 VLBW children assessed at 4-5 years who were free of cerebral palsy or major neurological impairment and had full-scale IQ >70. MAIN OUTCOME MEASURE: Movement assessment battery for children (MABC). RESULTS: Using ≤15th percentile on the MABC as the cut-off, 42% of our cohort developed DCD. Perinatal variables significantly associated with DCD were male sex, lower gestational age and lower birth weight, but only male sex and low birth weight independently predicted DCD, accounting for 20% of the variance in MABC scores. Compared with children without motor impairment, children with DCD had greater postnatal steroid exposure, longer duration of ventilation, more days on oxygen and significant retinopathy of prematurity, but only postnatal steroid exposure was significant, accounting for an additional 3% of the variance in MABC scores. Boys performed more poorly than girls on all subtests of the MABC. CONCLUSIONS: Male sex and low birth weight were significant predictors of DCD, suggesting that these infants should be followed for detection of this common, but under-recognised disorder. Future research aimed at identifying neural underpinnings of DCD and possible antecedents to the disorder is warranted.

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)0.003
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 score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.004
GPT teacher head0.217
Teacher spread0.213 · 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

Citations98
Published2012
Admission routes3
Has abstractyes

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