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Record W4412514341 · doi:10.1002/uog.29298

Adverse neonatal outcomes in small‐for‐gestational age twins identified using twin <i>vs</i> singleton growth charts: systematic review and meta‐analysis

2025· review· en· W4412514341 on OpenAlexaboutno aff
Sara Sorrenti, Daniele Di Mascio, Asma Khalil, Fabrizio Zullo, Elena D’Alberti, Valentina D’Ambrosio, Ilenia Mappa, A. Giancotti, Giuseppe Rizzo

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2025
Typereview
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsnot available
Fundersnot available
KeywordsSingletonMeta-analysisObstetricsSmall for gestational ageMedicineGestational agePregnancyInternal medicineBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the use of twin vs singleton growth charts for detecting small-for-gestational-age (SGA) twins at risk of adverse neonatal outcomes. METHODS: MEDLINE, EMBASE, CINAHL, Cochrane and Scopus databases were searched electronically from inception to May 2024. The primary outcome of this meta-analysis was the risk of composite adverse neonatal outcome in SGA fetuses in a twin pregnancy diagnosed using twin or singleton charts. The secondary outcomes included: neonatal intensive care unit (NICU) admission, oxygen supplementation or continuous positive airway pressure, mechanical ventilation, respiratory distress syndrome, intraventricular hemorrhage, necrotizing enterocolitis, neonatal sepsis and neonatal mortality. Prospective and retrospective studies on neonatal outcomes of monochorionic or diamniotic twins diagnosed with SGA using both singleton and twin charts based on estimated fetal weight or birth weight were considered suitable for inclusion. Quality assessment of the included studies was performed using the Newcastle-Ottawa Scale for cohort studies. Random-effects head-to-head meta-analyses were used to analyze the data. RESULTS: Six studies were included in the systematic review and five studies, including 10 554 twin pregnancies, were included in the meta-analysis. The risk of composite adverse neonatal outcome (OR, 3.11 (95% CI, 1.83-5.26)) and that of most secondary outcomes was significantly higher in SGA fetuses diagnosed using twin charts compared with those diagnosed using singleton charts. Conversely, the risk of composite adverse neonatal outcome (OR, 1.22 (95% CI, 0.73-2.04)) and most secondary outcomes was similar when comparing SGA fetuses diagnosed using singleton charts vs non-SGA fetuses diagnosed using twin charts, except for the risk of NICU admission, which was significantly higher in SGA fetuses diagnosed using singleton charts. When comparing non-SGA fetuses diagnosed using twin charts vs non-SGA fetuses diagnosed using singleton charts, the risk of composite adverse neonatal outcome was significantly lower when using twin charts (OR, 0.90 (95% CI, 0.83-0.97)). Finally, when comparing SGA vs non-SGA fetuses diagnosed using singleton charts, there was no significant difference for the primary or secondary outcomes, except for a higher risk of NICU admission in the SGA group (OR, 1.54 (95% CI, 1.11-2.12)). Twin charts had lower sensitivity than singleton charts in predicting adverse neonatal outcome (14% (95% CI, 7-26%) vs 32% (95% CI, 24-41%)), but higher specificity (95% (95% CI, 86-98%) vs 71% (95% CI, 63-77%)). CONCLUSIONS: Twin charts increase the specificity but reduce the sensitivity for the detection of SGA compared with singleton charts. Nevertheless, twin charts detect cases at higher risk of adverse neonatal outcome, which may be the cases that require intervention. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

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)0.011
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.031
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0210.036
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.051
GPT teacher head0.330
Teacher spread0.279 · 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 designMeta-analysis
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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