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Record W3191621811 · doi:10.1080/17518423.2021.1960918

Utility of the Ages and Stages Questionnaires 3rd Edition for Developmental Screening in Children with Surgically Repaired Congenital Heart Disease

2021· article· en· W3191621811 on OpenAlexafffund
Julien Lépine, Karine Gagnon, Joëlle Prud’homme, Marie Claude Vinay, Amélie Doussau, Solène Fourdain, Sarah Provost, Véronique Belval, Catherine Bernard, Anne Gallagher, Nancy Poirier, Marie‐Noëlle Simard

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2021
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersUniversité de MontréalHeart and Stroke Foundation of Canada
KeywordsBayley Scales of Infant DevelopmentToddlerPediatricsMedicineHeart diseaseChild developmentPsychologyDevelopmental psychologyInternal medicineCognitionPsychomotor learningPsychiatry

Abstract

fetched live from OpenAlex

Aim: This study sought to evaluate the accuracy of the Ages and Stages Questionnaires 3rd Edition (ASQ-3) in identifying developmental delay (DD) in children with congenital heart disease (CHD) born at term who underwent surgical repair.Methods: Participants had to complete ASQ-3 and Bayley Scales of Infant and Toddler Development 3rd Edition (BSID-III) at 12 and 24 months. A child was considered at risk of DD for a ASQ-3 domain when he scored below the cutoff (≤-1SD or ≤-2SD). A child had a DD in a BSID-III domain when the score was ≤-1SD. The validity for each ASQ-3 domain and for overall ASQ-3 was measured.Results: At 12 months (n = 64), overall ASQ-3 (≤-2SD) sensitivity was 88%, specificity 74%. At 24 months (n = 82), overall ASQ-3 (≤-2SD) sensitivity was 74%, specificity 88%.Conclusion: The results support the utility of the ASQ-3 for screening the overall risk of DD in children with CHD.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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

Citations12
Published2021
Admission routes2
Has abstractyes

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