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Estimated fetal weight percentiles and kindergarten-age child development: evaluating the predictive ability of the INTERGROWTH-21st and WHO fetal growth charts a cohort study

2022· preprint· en· W4295538076 on OpenAlexaffabout
Ariadna Fernandez, Jessica Liauw, Chantal Mayer, Arianne Albert, Jennifer A. Hutcheon

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPercentileMedicineGrowth chartConfidence intervalPediatricsCohortGeneration RRetrospective cohort studyPopulationCohort studyObstetricsStatisticsInternal medicineMathematicsEnvironmental health

Abstract

fetched live from OpenAlex

Objectives: To estimate the association between estimated fetal weight (EFW) percentiles on the INTERGROWTH-21st and WHO fetal growth charts and kindergarten-age childhood development, and identify the charts’ percentile cut-offs that best predict kindergarten-age developmental challenges. Design: Retrospective cohort linkage study. Setting: Obstetrical ultrasound department of BC Women’s Hospital, Vancouver, Canada. Population or Sample: Non-anomalous, singleton fetuses scanned ≥ 28 weeks’ gestation, 2000-2011 (n=3418). Methods: We classified EFWs into percentiles using the INTERGROWTH-21st and WHO charts. We used generalized additive modelling to link EFW percentile with routine province-wide kindergarten readiness test results. We calculated the AUC, as well as other measures of diagnostic accuracy with 95% confidence intervals (CI) at select percentile cut-points of the charts. Main Outcome Measures: Total Early Development Instrument (EDI) score (/50). Secondary outcomes: EDI sub-domain scores for language and cognitive development, and for communication skills and general knowledge; designation of ‘developmentally vulnerable’ or ‘special needs’. Results: Fetuses with lower EFW percentiles had systematically lower EDI scores and increased risks of developmental vulnerability. However, the clinical significance of differences was modest in magnitude: e.g., total EDI score -2.8 [95% CI: -5.1, -0.5] in children with an EFW 3-9th percentile of INTERGROWTH chart (vs. reference of 31-90th). The charts’ predictive abilities for adverse child development were limited (e.g., AUC<0.53 for both charts). Conclusions: Lower EFW percentiles on the INTERGROWTH-21st and WHO charts indicate increased risks of adverse kindergarten-age child development at the population level, but are not accurate individual-level predictors of adverse child development.

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)0.005
metaresearch head score (Gemma)0.018
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 score0.086
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.054
GPT teacher head0.375
Teacher spread0.321 · 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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