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Record W7115017990 · doi:10.1093/pch/pxaf116.094

94 School readiness in very preterm infants in Ontario: a pilot database study

2025· article· en· W7115017990 on OpenAlexaffabout

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsInstitute for Christian StudiesMcMaster University
Fundersnot available
KeywordsToddlerBayley Scales of Infant DevelopmentGestational agePercentileChild developmentCognitive developmentCompetence (human resources)Percentile rank

Abstract

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Abstract Background Studies have shown that neurodevelopmental impairment (NDI) at 18-24 months corrected age in children born preterm is associated with school-age academic skills. The major limitation of these studies is that they do not address school readiness, which informs the degree of support needed in school and helps develop early interventions. Objectives To describe the school readiness profile of children born very preterm and to determine its association with the neurodevelopment at 18-24 months corrected age (CA). Design/Methods A pilot database study retrospectively analyzing prospectively collected, standardized data was conducted on preterms born at < 29 weeks’ gestational age between 2009 and 2012 who completed the Bayley Scales of Infant and Toddler Development between 18 and 24 months CA. These data were linked using deterministic linkage with the Early Development Instrument (EDI) in Ontario, Canada. Neonatal and neurodevelopmental characteristics and school readiness were described and compared between children identified as having NDI and those without. Results Of 684 eligible infants, 112 (16%) had available EDI data (Figure 1). Children with NDI (N = 50, 45%) were more preterm, had lower birthweight, and had more frequent, significant brain injury and bronchopulmonary dysplasia. Compared to the general population, more children born very preterm with NDI were considered vulnerable, defined as scoring below the 10th percentile distribution cut-off, across all domains of the EDI (Table 1). On the other hand, more children without NDI showed vulnerability in the domains of social competence and language and cognitive development versus the general population. Thirty-four percent of very preterm children were vulnerable in 2 or more domains compared to 14% in the general population (p < 0.0001). The Bayley language score was most statistically significantly associated with vulnerability in physical health and well-being, language and cognitive development, and communication and general knowledge. None of the Bayley subtests were associated with emotional maturity or social competence. Conclusion Neurodevelopmental impairment at 18-24 months was associated with all school readiness markers, while being born very preterm without NDI was still associated with vulnerability in two or more domains. Findings in this study may indicate that a focus on early language skills is needed to promote school readiness in children born very preterm. Other assessments may be needed for earlier insight into social competence and emotional maturity.

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)0.004
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 score0.094
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.020
GPT teacher head0.299
Teacher spread0.278 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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