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Record W4297894296 · doi:10.1101/2022.09.21.22280142

The clinical performance and population health impact of birth weight-for-gestational age indices with regard to adverse neonatal outcomes in term infants

2022· preprint· en· W4297894296 on OpenAlexafffundabout
Sid John, K.S. Joseph, John Fahey, Shiliang Liu, Michael S. Kramer

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsMcGill UniversityCancer Care Nova ScotiaPublic Health Agency of CanadaUniversity of OttawaChildren's & Women's Health Centre of British ColumbiaUniversity of British Columbia
FundersBC Children's Hospital
KeywordsMedicineGestational agePopulationBirth weightApgar scoreSmall for gestational ageGestationLow birth weightOdds ratioObstetricsOddsPediatricsPregnancyLogistic regressionInternal medicineBiology

Abstract

fetched live from OpenAlex

Abstract Background Despite the recent creation of several birth weight-for-gestational age references and standards, none has proven superior. We identified birth weight-for-gestational age cut-offs, and corresponding United States population-based, Intergrowth 21 st and World Health Organization centiles associated with higher risks of adverse neonatal outcomes, and evaluated their ability to predict serious neonatal morbidity and neonatal mortality (SNMM). Methods and findings The study population comprised singleton live births at 37-41 weeks’ gestation in the United States, 2003-2017. Birth weight-specific SNMM, which included 5-minute Apgar score<4, neonatal seizures, assisted ventilation and neonatal death, was modeled by gestational week using penalized B-splines. We estimated the birth weights at which SNMM odds was minimized (and higher by 10%, 50% and 100%), and identified the corresponding population, Intergrowth 21 st and World Health Organization (WHO) centiles. We then evaluated the individual- and population-level performance of these cut-offs for predicting SNMM. The study included 40,179,663 live births at 37-41 weeks’ gestation and 991,486 SNMM cases. Among female singletons at 39 weeks’ gestation, SNMM odds was lowest at 3,203 g birth weight (population, Intergrowth and WHO centiles 40, 52 and 46, respectively), and 10% higher at 2,835 g and 3,685 g (population centiles 11 th and 82 nd , Intergrowth centiles 17 th and 88 th and WHO centiles 15 th and 85 th ). SNMM odds were 50% higher at 2,495 g and 4,224 g and 100% higher at 2,268 g and 4,593 g. Birth weight cut-offs were poor predictors of SNMM. For example, the birth weight cut-off associated with 10% higher odds of SNMM among female singletons at 39 weeks’ gestation resulted in a sensitivity of 12.5%, specificity of 89.4% and population attributable fraction of 2.1%, while the cut-off associated with 50% higher odds resulted in a sensitivity of 2.9%, specificity of 98.4% and population attributable fraction of 1.3%. Conclusions Birth weight-for-gestational age cut-offs and centiles perform poorly when used to predict adverse neonatal outcomes in individual infants, and the population impact associated with these cut-offs is also small. Funding Canadian Institutes of Health Research (MOP-67125 and PJT153439). Author summary Why was this study done Despite the recent creation of several birth weight-for-gestational age references and standards, no method has proved superior for identifying small-for-gestational age (SGA), appropriate-for-gestational age (AGA) and large-for-gestational age (LGA) infants. For instance, infants classified as AGA by the Intergrowth Project 21 st standard and SGA by national references have a higher risk of perinatal death compared with infants deemed AGA by both. What did the researchers do and find? Our study identified the birth weights at each gestational week at which the risk of serious neonatal morbidity and neonatal mortality (SNMM) was lowest and elevated to varying degrees, and showed that the corresponding Intergrowth and WHO centiles were right-shifted compared with population centiles. Outcome-based birth weight and centile cutoffs performed poorly for predicting serious neonatal morbidity and neonatal mortality (SNMM) at the individual level. The population attributable fractions associated with these Outcome-based birth weight and centile cutoffs cut-offs were also small. The birth weight distributions of live births and SNMM cases (at each gestational week) overlapped substantially, showing that birth weight-for-gestational age in isolation cannot serve as an accurate predictor of adverse neonatal outcomes, irrespective of the cut-off used to identify SGA and LGA infants. What do these findings mean? Using birth weight-for-gestational age cutoffs to identify SGA, AGA and LGA infants does not add significantly to individual- or population-level prediction of adverse neonatal outcomes. Birth weight-for-gestational age centiles are best suited for use in multivariable prognostic functions, in conjunction with other prognostic indicators of adverse perinatal outcomes.

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 score0.010
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.068
GPT teacher head0.449
Teacher spread0.381 · 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 routes3
Has abstractyes

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