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Record W4402959629 · doi:10.1111/aogs.14965

Outcomes of pregnancies with varying levels of nuchal translucency measurements: A population‐based retrospective study in Ontario, Canada

2024· article· en· W4402959629 on OpenAlexafffundabout
Kara Bellai‐Dussault, Shelley Dougan, Deshayne B. Fell, Carolina Lavín Venegas, Julian Little, Lynn Meng, Nanette Okun, Mark Walker, Christine M. Armour, Beth K. Potter

Bibliographic record

VenueActa Obstetricia Et Gynecologica Scandinavica · 2024
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsOttawa HospitalSunnybrook Health Science CentreNewborn Screening OntarioHealth Sciences CentreChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineObstetricsPregnancyNuchal Translucency MeasurementGestational agePoisson regressionNuchal translucencyConfidence intervalPopulationRetrospective cohort studyRelative riskSingletonGynecologyGestationFirst trimesterSurgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Nuchal translucency prenatal ultrasound is widely used to screen for chromosomal abnormalities. An elevated nuchal translucency has been associated with adverse outcomes such as pregnancy loss; however, extant studies investigating these associations have had important limitations, including selection bias. This study aimed to investigate the association between nuchal translucency measurements and pregnancy outcome, specifically, a composite of pregnancy loss, termination, stillbirth, or neonatal death. MATERIAL AND METHODS: This was a population-based retrospective cohort study conducted with data from the prescribed perinatal registry in Ontario, Canada, Better Outcomes Registry & Network. All singleton pregnancies with an estimated date of delivery from September 1, 2016, to March 31, 2021, and multiple marker screening including a nuchal translucency were included. Pregnancies with measurements 2.0- < 2.5 mm, 2.5- < 3.0 mm, 3.0- < 3.5 mm, 3.5- < 5.0 mm, 5.0- < 6.5 mm, and ≥6.5 mm were compared to a reference group with measurements <2.0 mm. We used multivariable modified Poisson regression models with robust variance estimation to estimate associations between nuchal translucency measurement and pregnancy outcome, with adjustment for age at estimated date of delivery and gestational age at screening. RESULTS: There were 414 268 singleton pregnancies included in the study. The risk of pregnancy loss, termination, stillbirth, or neonatal death increased with increasing levels of nuchal translucency measurements, with an adjusted risk ratio (aRR) of 11.9 (95% confidence interval (CI) 9.9, 14.3) in the group with measurements 3.5- < 5.0 mm. When pregnancies with diagnosed chromosomal abnormalities were excluded, this association remained strong, with an aRR of 6.4 (95% CI 4.8, 8.5). Among pregnancies with a live birth, those with a higher nuchal translucency measurement (>5.0 mm vs. <2.0 mm) were also at increased risk of adverse perinatal outcomes such as admission to the neonatal intensive care unit and APGAR score <7. CONCLUSIONS: In this population-based study using robust methods to reduce the risk of selection bias, we found that pregnancies with increased nuchal translucency measurements are less likely to result in a live birth, even with the exclusion of chromosomal abnormalities. Pregnancies with increased nuchal translucency measurements that resulted in a live birth may also be at increased risk 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)0.001
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 score0.025
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.052
GPT teacher head0.289
Teacher spread0.237 · 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

Citations3
Published2024
Admission routes3
Has abstractyes

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