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Record W4416293347 · doi:10.1016/j.ajogmf.2025.101845

Fetal growth velocity as a predictor of small for gestational age at birth and adverse perinatal outcomes: systematic review and meta-analysis

2025· article· en· W4416293347 on OpenAlexaboutno aff
Elena D’Alberti, Daniele Di Mascio, A. Giancotti, Lawrence Impey, Guglielmo Stabile, Aris T. Papageorghiou, Giuseppe Rizzo, Tamara Stampalija

Bibliographic record

VenueAmerican Journal of Obstetrics & Gynecology MFM · 2025
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
Fundersnot available
KeywordsFetal growthGestational ageSmall for gestational ageFetusRisk factorPregnancyRisk assessmentPerinatal mortality

Abstract

fetched live from OpenAlex

OBJECTIVE This study aimed to evaluate the role of fetal growth velocity in predicting small-for-gestational-age at birth and adverse perinatal outcomes. DATA SOURCES A systematic review and meta-analysis was conducted through an electronic search of PubMed, Embase, and CINAHL, including studies published between January 2000 and February 2025. STUDY ELIGIBILITY CRITERIA Both prospective and retrospective studies of pregnancies undergoing longitudinal growth assessment, from the second to the third trimester or within the third trimester, were included. METHODS This study was registered with PROSPERO (International Prospective Register of Systematic Reviews) (CRD42025642750). Pooled sensitivity and pooled specificity with 95% confidence interval and pooled risk estimates were synthesized using random- and fixed-effects models, respectively. Risk of bias was assessed using the Newcastle–Ottawa scale and the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies), whereas certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. RESULTS The electronic search yielded 5.440 citations. Following full-text review of the potentially eligible studies, 21 studies were included. The predictive and risk stratification value of fetal growth velocity for small-for-gestational-age at birth and adverse perinatal outcomes was assessed across cohorts of 185.441 and 164.341 singleton pregnancies, respectively. Slowing fetal growth velocity showed suboptimal predictive performance for small-for-gestational-age at birth, with pooled sensitivity and specificity for abdominal circumference and estimated fetal weight growth velocity (defined as z-scores divided by interval time in days) of 0.22 (95% CI, 0.09–0.44) and 0.92 (95% CI, 0.92–0.95), and 0.55 (95% CI, 0.53–0.56) and 0.96 (95% CI, 0.96–0.96), respectively (GRADE: low). Slowing fetal growth velocity showed a moderate association with adverse perinatal outcomes: abdominal circumference growth velocity <10 th centile was associated with composite adverse perinatal outcome among fetuses predicted to be small-for-gestational-age (pooled odds ratio, 2.47; 95% CI, 1.69–3.82), whereas a fixed centile drop in abdominal circumference/estimated fetal weight ≥50 significantly increased the risk of perinatal death, irrespective of estimated fetal weight (pooled odds ratio, 3.92; 95% CI, 2.03–7.58) (GRADE: moderate). CONCLUSION Fetal growth velocity might be considered a moderate risk factor for adverse outcomes, but it did not improve prediction over cross-sectional biometry, either at 32 or 36 weeks of gestation, even when implemented in multivariable models. Its clinical utility may lie in complementing third-trimester biometry and maternal/fetal Dopplers in risk stratification. However, standardized definitions and formulas are urgently needed to improve reproducibility and guide implementation in antenatal care.

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)0.021
metaresearch head score (Gemma)0.056
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 score0.026
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.056
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0260.041
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.299
Teacher spread0.271 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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